On Thursday, Microsoft unveiled a new division named Microsoft Frontier, dedicated to enhancing enterprise AI implementations using its current suite of AI tools. To support this initiative, the tech giant is investing $2.5 billion and enlisting a team of 6,000 professionals specializing in various industries and engineering fields.

In his announcement, Judson Althoff, CEO of Microsoft's Commercial Business, emphasized that this initiative transcends traditional Forward Deployed Engineering (FDE) concepts. He stated, "This goes beyond what has been labeled as Forward-Deployed Engineering,” asserting that it aims to create the largest and most skilled, outcome-focused engineering team in the industry.

However, this new venture shares notable similarities with multiple FDE-focused AI initiatives launched recently. Just two days prior, Amazon Web Services revealed its own $1 billion commitment to AI deployment, clearly aligned with the FDE approach. Similarly, OpenAI and Anthropic have initiated comparable projects, which also attract investment from private equity firms.

Microsoft's established relationships with its clients provide an advantageous starting point for this initiative, as the company has already positioned engineers within a significant portion of the Fortune 500. The announcement highlights initial collaborations with companies such as the London Stock Exchange Group, Unilever, Land O’Lakes, and Accenture, further signaling the extensive potential and reach of Microsoft Frontier.

Microsoft establishes its own AI implementation firm with a $2.5 billion investment.

A modern glass headquarters bathed in warm morning sunlight, its facade dominated by a large Microsoft logo above the entrance. In front, corporate executives in business attire cut a red ribbon stretched between two sleek pillars labeled “AI Deployment Co.” Beside them stands an artistic sculpture of glowing glass tubes twisting like neural-network pathways. A slim digital display board near the steps reads “$2.5 B Commitment” in elegant lettering.

Microsoft launches its own AI deployment company with $2.5 billion commitment - TechCrunch

- Microsoft launched Microsoft Frontier company, focusing on enterprise AI deployments with a $2.5 billion investment.  
- The venture aims to create the largest outcome-driven engineering organization in the industry.  
- Existing partnerships with major firms like Unilever and Accenture provide a competitive advantage.  

On Thursday, Microsoft announced a new operating business called Microsoft Frontier company, focused on delivering successful enterprise AI deployments with Microsoft’s existing AI tools. The project will be backed by a $2.5 billion investment from Microsoft, as well as 6,000 industry and engineering experts.

In a statement announcing the venture, Microsoft’s Commercial Business CEO Judson Althoff resisted the Forward Deployed Engineer (FDE) label that is often applied to these ventures. “This goes beyond what has been labeled as Forward-Deployed Engineering,” Althoff wrote, “and will be the largest, most capable, outcome-driven engineering organization in the industry.”

Nonetheless, the venture bears a striking similarity to a number of FDE-based AI ventures announced in recent months. Just two days earlier, Amazon Web Services announced an internal commitment of $1 billlion for its own AI deployment venture, explicitly embracing the FDE model. Both OpenAI and Anthropic have launched joint ventures along similar lines, although those efforts also involve outside capital from private equity firms.

Microsoft’s existing client base will give the new effort a significant head start, as the company has already deployed engineers to much of the Fortune 500. The announcement cites an early partnership with the London Stock Exchange Group, as well as Unilever, Land O’Lakes, and Accenture.

Microsoft launches its own AI deployment company with $2.5 billion commitment

I had always believed that software engineers were inherently curious, eager to dive headfirst into the latest technological advancements. However, my recent experiences have shown me that this isn't universally true.

I posed a question to a developer colleague regarding her experience with Claude Code or Codex, even just for a brief weekend trial. Her response? A resounding, "Nope," delivered with pride. This individual is a highly qualified and seasoned software engineer engaged in extensive, long-term projects.

It appears that some tech professionals can be just as resistant to change as anyone else.

This phenomenon isn't isolated; it's occurring within a critical software initiative that underpins much of our digital infrastructure.

Linux, the operating system that drives a vast array of services—from cloud platforms to smartphones and numerous enterprise systems—is also one of the largest open-source projects in existence, developed by countless volunteers. Surprisingly, some of these programmers advocate for restrictions on using artificial intelligence for coding and code reviews.

Linus Torvalds, who is credited with creating Linux, recently addressed this pushback decisively. He contended that AI is merely another tool that has matured significantly in its ability to write, review code, and identify software defects.

For those who choose not to embrace AI, Torvalds humorously suggested they could "fork" themselves, making a play on words that references the practice of copying existing software to create a separate version.

"This is NOT some kind of 'social warrior' initiative, and it never will be," Torvalds clarified on a Linux mailing list. "Our decisions are grounded in technical capabilities, not in a fear of novel tools."

A year ago, there was uncertainty about the true utility of AI, but Torvalds asserts that this question has been decisively answered.

He acknowledged that while AI can sometimes be "painful" to work with—especially as it frequently uncovers bugs in human-written code, which can be a source of embarrassment for developers—the appropriate response isn't to ignore the technology. "The solution isn't to bury your head in the sand and sing 'La La La, I can't hear you,'" he wrote, alluding to some individuals’ dismissive attitudes toward AI.

If you're interested in staying informed, be sure to subscribe to BI's Tech Memo newsletter. For any direct inquiries, feel free to reach out to me at abarr@businessinsider.com.

Not a fan of AI? The creator of Linux suggests you should fork your own version.

A warm, sunlit workshop: Linus Torvalds seen from behind in a casual sweater stands at a sturdy wooden table facing a small, smirking AI robot in a metal chair. He raises a gleaming silver fork defiantly toward the robot. Carved into the tabletop are branching lines of code. A weathered Linux penguin sticker peels off an old toolbox nearby. Natural morning light streams through a dusty window, casting a spirited, rebellious glow over the scene.

Don't like AI? Linux's creator says go fork yourself - Business Insider

- Many software engineers are resistant to embracing new AI technologies despite their benefits.  
- Linus Torvalds insists AI is a valuable tool for code writing and bug checking.  
- Torvalds criticizes developers who refuse to adapt to AI advancements in software development.

I always assumed software engineers were naturally curious people who couldn't wait to try the latest technology. Lately, I'm realizing that's not always true.

I recently asked a developer friend whether she'd tried Claude Code or Codex, even for a few minutes over a weekend.

"Nope," she said proudly. This is a highly educated, experienced software engineer who works on big long-term projects.

Some techies, it turns out, are just as resistant to change as everyone else.

It's not just her. This is happening inside one of the most important software projects on earth.

Related video Sam Altman explains why AI will replace 40% of your work

Linux is the operating system that powers much of the internet, from cloud computing to smartphones and countless business systems.

It's also a huge open-source project, built by thousands of volunteers. Some of these developers want limits on using AI to write and review code.

Linus Torvalds, the creator of Linux, shut that down hard recently. AI, he argued, is simply another tool, which has gotten very good at writing and checking code and finding software bugs.

If folks don't want to use AI, they can go fork themselves, Torvalds quipped. (I'm here for the open-source dad jokes. A fork is when someone copies an existing piece of software and starts developing it separately as their own version).

"This is NOT some kind of 'social warrior' project, never has been, and never will be," Torvalds wrote on a Linux mailing list. "We make decisions primarily based on technical merit. Not fear of new tools."

A year ago, it was unclear whether AI would be this useful, but that's no longer in question, he said.

Torvalds admitted that AI can be "painful" to use sometimes, partly because it keeps finding bugs in software code written by humans, which can be embarrassing for software engineers.

"But the solution is not to put your head in the sand and sing 'La La

La, I can't hear you' at the top of your voice like some people seem

to do," he wrote.

Sign up for BI's Tech Memo newsletter here. Reach out to me via email at abarr@businessinsider.com.

Don't like AI? Linux's creator says go fork yourself

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AI is quietly becoming an unofficial and potentially unwanted 'third' in relationships - Yahoo

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Three years back, Microsoft CEO Satya Nadella propelled the company into the forefront of the AI landscape, earning accolades and comparisons to a "superhero" from a former executive. In February 2023, after early investments in OpenAI paid off, Nadella introduced an AI-enhanced Bing search engine at a Seattle event, signaling a challenge to Google's dominance. "A race starts today," he proclaimed, receiving waves of praise. Later that year, amidst a crisis within OpenAI's board, Bill Gurley highlighted Nadella's role in transforming the company’s reputation, and CNN Business awarded him "CEO of the Year."

However, as the tech industry shifts, Nadella's legacy is now on the line. Microsoft's stock has declined over 24% in the past year, far worse than other major tech players. There’s increasing investor skepticism over whether the company’s massive investment in AI will yield returns. For instance, Copilot, Microsoft’s leading AI offering, is falling behind rivals like ChatGPT and Claude. On another front, LinkedIn faces backlash due to an influx of AI-generated content, and Xbox is reportedly struggling, leading to layoffs and a reorganization following its record $69 billion acquisition of Activision Blizzard.

Internally, employees are questioning the rationale behind a planned $190 billion investment this year in AI infrastructure, particularly as generative AI transforms workplaces, software development, and information consumption. The effectiveness of three of Microsoft's key businesses—Microsoft 365, GitHub, and Azure—hangs in the balance. Investors are anxiously awaiting Wednesday's fourth-quarter earnings report to gauge the situation.

As generative AI becomes ubiquitous in corporate America, software companies are scrambling to avoid what many are calling a SaaSpocalypse. This predicament is particularly daunting for Microsoft, which boldly staked its future on AI. What was once a guiding star could now pose a risk.

For decades, Microsoft’s productivity tools, including Word, Excel, and PowerPoint, have been staples for knowledge workers. Now, many are beginning to utilize AI tools for these tasks. Gartner analysts warned early this year that AI might disrupt traditional productivity suites like Microsoft 365 and Google Workspace, impacting a $58 billion market.

Microsoft leaders cite ongoing adoption of Microsoft 365 and Copilot as evidence of continued customer interest. "The M365 business is seeing tons of new adoption and M365 Copilot usage," one executive noted, emphasizing the push for capacity to accommodate demand.

GitHub, the software development platform acquired in 2018, is experiencing similar challenges. Although it has maintained its stronghold among developers and capitalized on early AI coding advantages, competition is fierce. Emerging tools like Cursor—recently targeted for acquisition by SpaceX for $60 billion—and Anthropic’s Claude Code have gained traction, leading Microsoft to contemplate substantial overhauls to GitHub to remain competitive. Increased AI demand has also led to numerous outages this year.

In the cloud computing segment, Microsoft is grappling to meet skyrocketing demand for Azure. Despite this year’s heavy investments aimed at expanding data center capacity for AI workloads, executives indicate that building new capacity remains a challenge. As a result, the company has raised sales quotas for its Azure sales team by as much as 30%.

While Azure continues to be the fastest-growing segment within Microsoft, executives reveal that balancing demand with production capabilities has become increasingly difficult. Chief Financial Officer Amy Hood acknowledged that the company is prioritizing its own AI products over cloud services for external customers. In doing so, Azure growth could have surpassed 40%, instead of a reported 39%, had resources been allocated differently, Hood suggested.

Consequently, Microsoft has been sourcing additional cloud capacity from competitors. Following outages at GitHub, Amazon provided temporary assistance. Microsoft also explored leasing Oracle's cloud infrastructure but ultimately withdrew due to compliance and security concerns. Now, the company is in talks with providers like Amazon and Google to alleviate constraints, indicating, "We are shopping for capacity everywhere," according to insiders.

This strategy of prioritizing internal services has drawn mixed responses from Wall Street but remains a clear focus within Microsoft. Internally, conversations have shifted toward the implications of these choices, especially decisions like prioritizing Adobe's growth over that of M365, leading to confusion about how to communicate these strategies externally.

As Nadella faces rising pressure on core business areas, he has been reshaping the company’s leadership structure. He promoted Judson Althoff to oversee Microsoft's commercial sector to allow for more direct leadership in AI initiatives. Althoff's previous role in sales now gives him a prominent position. This reorganization is described by Nadella as part of a major transition into an AI-centric approach.

Significant changes are unfolding throughout Microsoft, including adjustments to its performance review system to better align with current goals. These revisions, perceived as a return to the competitive practices of the Steve Ballmer era, aim to boost accountability but have raised concerns about a renewed culture of fear.

For years, Microsoft has thrived on controlling the workspace environment for both users and developers. However, the rise of AI threatens to disrupt those foundations. Now, Nadella's legacy may hinge not on the quest to develop superior AI, but on his ability to safeguard the essential businesses that have historically contributed to Microsoft's standing as one of the world’s most valuable enterprises.

Exploring Nadella's Most Challenging Year

A shadowy office at night: Satya Nadella seen from behind, standing before a bank of flickering screens showing plunging stock charts, urgent cloud-outage alerts, and AI ethics headlines. The Microsoft logo looms large, softly backlit on the wall. Deep shadows, a single overhead warm spotlight, tense and cinematic.

Inside Nadella's hardest year: Is Microsoft's North Star also a noose? - Business Insider

- Satya Nadella's leadership is under scrutiny as Microsoft faces AI growth challenges.  
- Microsoft's stock has dropped 24%, raising investor concerns about its AI investments.  
- Internal restructuring and pressure reflect the urgency to maintain Microsoft's competitive edge in AI.  

Three years ago, Satya Nadella catapulted Microsoft to the front of the AI race and became "like a superhero," one recent former Microsoft executive said.

In February 2023, after betting early on OpenAI, the CEO unveiled Microsoft's AI-powered Bing search engine before a packed audience outside Seattle, and declared a war on Google's search dominance. "A race starts today," he said. Waves of adulation followed. When Nadella helped navigate OpenAI's board crisis later that year, Bill Gurley called it an "amazing shift in corporate reputation." CNN Business chose Nadella as the CEO of the Year.

Inside Microsoft and across the tech industry, Nadella was hailed for seizing the future. Now, his legacy is at stake.

Microsoft's stock is down more than 24% from 12 months ago, significantly worse than the rest of the Magnificent 7. Investors have grown increasingly skeptical that the company's multibillion-dollar AI bet will deliver. Copilot, Microsoft's flagship AI product, lags behind other AI tools like ChatGPT and Claude. LinkedIn has drawn criticism for becoming flooded with AI-generated hustleporn. Xbox's business is "not healthy," its CEO recently said, and undergoing layoffs and restructuring as it tries to justify the company's record-breaking $69 billion Activision Blizzard acquisition.

And inside the company, employees are questioning Microsoft's plans to spend a record $190 billion this year to build AI infrastructure. As generative AI changes how people work, write software, and consume information, three of the company's core businesses hang in the balance: Microsoft 365, GitHub, and Azure. Investors will get a report card on these challenges on Wednesday, when the company releases its fourth-quarter earnings results.

As AI adoption spreads through corporate America, every software company is fighting to fend off the so-called SaaSpocalypse. But the battle is particularly fraught for Nadella's Microsoft, which made an early and loud bet on AI to propel the company's future. Now the company's north star has also become a potential noose.

For decades, Microsoft's productivity software has been the default homeroom where knowledge workers start their day. They opened Word to write, Excel to analyze data, and PowerPoint to build presentations. Now, millions of those workers are beginning to do all these things directly inside AI tools. Gartner analysts earlier this year predicted AI would threaten to dethrone traditional productivity suites like Microsoft 365 and Google Workspace in a $58 billion market shakeup.

Microsoft executives point to continued growth in Microsoft 365 and increasing Copilot adoption as evidence customers still want Microsoft's products at the center of their workdays. "The M365 business is seeing tons of new adoption and M365 Copilot usage," one executive said, who said the company is specifically chasing computing capacity to meet the demand.

GitHub faces a similar challenge. Since acquiring the software development platform in 2018, the company has held a dominant position with developers and had an early advantage in AI coding through GitHub Copilot. And it continues to grow: The platform recently had its "best month ever," an executive told employees in internal meeting comments viewed by Business Insider, though he didn't say by what measure.

But upstarts have swarmed in, as millions of engineers have adopted Cursor — which SpaceX recently announced plans to acquire for $60 billion — and Anthropic's Claude Code. As Business Insider previously reported, executives have discussed internally the need to overhaul GitHub to better compete with those AI-native coding tools. AI demand has also strained Github. As AI usage surged GitHub has experienced dozens of major outages this year.

The company is also struggling broadly to keep up with the demand for compute capacity. Despite this crunch, Microsoft is raising salespeople quotas for selling its cloud computing platform, Azure, some by 30% this year, according to people familiar with the change.

Azure remains Microsoft's fastest-growing strategic business, but internally executives say it has become a constant balancing act. Demand for computing infrastructure has outpaced the company's ability to build new capacity, forcing Microsoft to make difficult decisions about where its resources go. Even with this year's $190 billion capital expenditures — largely to expand data-center capacity for AI workloads — executives say the company is still constrained.

Earlier this year, Chief Financial Officer Amy Hood suggested Microsoft was prioritizing scarce computing resources for its own AI products before allocating the remaining capacity to Azure customers.

"The first thing we're doing is solving for the increased usage in sales and the accelerating pace of M365 Copilot, as well as GitHub Copilot, our first-party apps," Hood said during Microsoft's January earnings call. "Then we make sure we're investing in the long-term nature of R&D and product innovation... Then what you end up with is the remainder going towards serving the Azure capacity that continues to grow in terms of demand."

Why would Satya prioritize growing Adobe over growing M365? Microsoft executive

If Microsoft had allocated the GPUs that came online during the first half of its fiscal year to Azure instead of its own AI products, Azure growth would have exceeded 40% instead of 39%, Hood said. Microsoft previously reported $75 billion in Azure revenue for its 2025 fiscal year.

That earnings report triggered one of Microsoft's biggest post-earnings stock declined by more than 10% as investors questioned the company's slower Azure outlook despite record AI spending and growing concerns that Microsoft was diverting capacity away from cloud customers.

Executives who spoke to Business Insider say those tradeoffs have intensified.

Microsoft is so desperate for capacity that it's turning to competitors to help relieve some of those constraints. Following a series of GitHub outages, Amazon bailed Microsoft out. The company also explored leasing Oracle cloud infrastructure but Microsoft walked away due to security and compliance concerns.

Microsoft is now seeking additional cloud capacity from other providers, including evaluating Amazon and Google, according to people familiar with the discussions. "We are shopping for capacity everywhere," one of those people said.

While prioritizing internal services has a mixed reception on Wall Street, the strategy is clear within Microsoft.

"All of the supply is gone once you solve for frontier labs and our internal businesses like M365 and Microsoft AI," one executive said.

Those decisions have created difficult conversations internally.

"Why would Satya prioritize growing Adobe over growing M365?" the person said. "I have no idea how we're going to land that message with customers."

As the pressure on Microsoft's core businesses mounts, Nadella has been bearing that pressure down on his workforce, and reshaping the structure of the company and its leaders.

As Business Insider previously reported, Nadella promoted Judson Althoff to CEO of Microsoft's commercial business to free himself and the company's engineering leaders to focus more directly on AI. Althoff was previously Microsoft's longtime sales boss but the role gave him a bigger profile. In an internal memo viewed by Business Insider at the time, Nadella described the moment as "a tectonic AI platform shift."

The mounting pressure on Nadella has trickled down through Microsoft's ranks from the executive suite to the rank-and-file employee.

At the same time, Nadella has remade his inner circle. Business Insider previously reported that Microsoft effectively retired its traditional senior leadership team structure in favor of smaller, flatter leadership groups. AI CEO Mustafa Suleyman has narrowed his focus to Microsoft's superintelligence efforts, top Nadella lieutenant Rajesh Jha retired, longtime product and marketing leader Yusuf Mehdi is preparing to leave the company, and more executive changes are expected.

According to people familiar with the succession planning, Hayete Gallot, who recently returned to Microsoft from Google to lead the company's security business, is viewed internally as the long-term successor to Althoff as sales chief. Gallot previously worked for Althoff and left in what one executive told Business Insider was "not an amicable departure." Nadella recruited Gallot back to replace Charlie Bell, who moved into an individual contributor role focused on engineering quality. Rodrigo Kede Lima, who Microsoft just put in charge of a $2.5 billion AI sales unit, is also a rising star, one of the people said.

The changes extend beyond the executive suite. Business Insider has learned that Microsoft overhauled its performance review system this year, simplifying ratings into five categories while making performance distinctions significantly sharper.

Executives say the new process feels like a return to "stack ranking," the controversial system that evaluated employees relative to one another during the Steve Ballmer era. At the same time, managers have been instructed to reduce the number of employees in higher-level engineering roles as Microsoft continues flattening parts of the organization, emblematic of a broader hardcore work culture that's spread across Big Tech in the last few years.

"It's almost like the old era of Microsoft is back," one former executive said. "The old Windows era where you lead with a lot of fear and a billy club in your hand."

For years, Microsoft's greatest strength was that it owned where people worked and where developers built software. AI is beginning to challenge both assumptions at once. Now Nadella's legacy won't be defined by whether Microsoft can build the best AI, but by whether it can keep AI from eroding the businesses that made it one of the world's most valuable companies.

Ashley Stewart is a chief technology correspondent at Business Insider.

Inside Nadella's Hardest Year

In today's era dominated by hyperscalers, a growing apprehension about data centers is closely tied to concerns over escalating utility costs. A YouGov survey conducted last year with a sample of 1,000 Americans revealed that over 66% anticipated an increase in electricity costs if a data center were established nearby. Furthermore, Goldman Sachs forecasted earlier this year that the expansion of AI infrastructure could lead to a 6% rise in electricity prices from 2026 to 2027, with an additional 3% increase expected by 2028.

However, a recent working paper from the Electric Power Research Institute has introduced a more nuanced perspective on the connection between the AI surge and its impact on electric bills for consumers. The study indicates that through at least 2024, the operational activity of data centers may not only allay consumer fears but could actively drive down retail electricity prices. Analyzing data from the Federal Energy Regulatory Commission (FERC) alongside retail revenue from the U.S. Energy Information Administration from 2015 to 2024, the findings demonstrated a causal link: for each doubling of data center capacity, average retail electricity prices dropped by 3.5%. On a state level, this reduction reached about 6%.

This phenomenon can largely be explained through the concept of economies of scale. 

“Electricity markets operate differently compared to many other industries,” remarked Asa Watten, coauthor of the study and researcher at EPRI, speaking to Fortune.

In contrast to commodities like soybeans or gasoline, where prices fluctuate based on production costs, electricity prices hinge on cost recovery, which depends on the volume of consumption. As fixed costs are spread over a larger consumer base and increased kilowatt-hour usage, the distribution of these fixed expenses leads to lower prices. Additionally, heightened data center activity encourages more energy-efficient generators to activate due to increasing loads.

Yet, there is a caveat to this trend: its sustainability is uncertain. A reversal could herald larger issues for the future of AI. Recent reports from PJM, the nation’s largest power grid operator, anticipate a $6.3 billion rise in consumer electricity expenses over the next three years, primarily driven by growing data center energy demands. The accelerated construction of data centers, which is projected to reach $7 trillion in investments by 2030, is already linked to rising power costs. For instance, Virginia, home to the highest number of data centers, has seen residential electricity prices surge by over 13% in the past year, based on data from the U.S. Energy Information Administration.

The future dynamics between data centers and electricity pricing hinge on several factors.

Watten notes that the critical factor will be whether the rapid expansion of AI fulfills expectations.

“If the grid enhances capacity in anticipation of substantial demand from data centers that fails to materialize, it could significantly alter the outlook, potentially leading to higher prices in the future,” he warned.

Data centers are likely to encounter substantial fixed overheads, and if demand from clients does not match projections, “your denominator will be smaller than anticipated,” Watten explained. “This means those fixed costs would be divided among fewer consumers, contrary to the desired outcome, potentially driving prices up.”

As discussions about an anticipated AI bubble circulate, skepticism among investors is starting to surface. Notably, shares of Tesla and Alphabet fell following announcements regarding increased capital spending related to AI.

Mark Cuban, a billionaire investor, also weighed in on the matter during an episode of the All-In podcast, suggesting that many data centers could ultimately be repurposed for far less high-tech uses, such as pickleball courts. He pointed out that while hyperscalers may rightly predict continued AI adoption, the technology is expected to become less expensive to use due to improved energy efficiency, indicating that the extensive capacity being built might not be necessary.

Nonetheless, there is a glimmer of hope, according to Watten. While he refrains from making predictions about the future of AI and its implications for data center development, he remains optimistic about ongoing advancements in energy efficiency. The growth of electrification, spurred by factors like electric vehicles and electric heat pumps, coupled with data center expansion, could potentially lead to reduced household energy costs independent of an AI surge.

“Efficiencies and overall cost reductions could benefit not just individuals but their communities as well,” Watten stated. “A rise in electric vehicle usage, done effectively, might ensure that prices decrease or at least stabilize.”

Data centers are lowering your electric bill, but decreasing AI demand may alter this.

A warm golden-hour scene: a sleek data-center building bathed in natural sunlight, rows of illuminated server windows glowing softly. From its base, thick cables fan out like roots toward a cozy suburban home whose electric meter reads “LOW.” In the distance, stormy clouds gather with a subtle, shadowy downward-sloping line hinting at sinking AI demand—cinematic, story-driven, warm tones.

Data centers are actually making your electric bill cheaper—but sinking AI demand could change that - Fortune

- The rise of data centers raises concerns about increasing electricity prices among Americans.  
- Data centers may lower retail electricity costs through economies of scale until at least 2024.  
- Future electricity prices depend on whether AI demand materializes as anticipated by investors.  

In the era of hyperscalers, the rising unpopularity of data centers has become inextricably linked with the fear of skyrocketing utility prices. A YouGov poll administered last year found that among 1,000 Americans, more than two-thirds expected electricity prices to rise if a data center was built in their area. Earlier this year, Goldman Sachs projected the AI infrastructure buildout to increase electricity costs by 6% between 2026 and 2027, and an additional 3% by 2028.

But a recent working paper from the Electric Power Research Institute is complicating the relationship between the AI boom and what it means for Americans’ electric bill. The research suggested that up until at least 2024, data center operations defied consumer anxieties and actually caused retail electricity costs to decrease. Using data from the Federal Energy Regulatory Commission (FERC) and retail revenue from the U.S. Energy Information Administration between 2015 and 2024, researchers found a causal relationship between data center demand and electricity prices: For every doubling of data center capacity, average retail electricity prices decreased by 3.5%. On a statewide level, this decrease was about 6%.

Much of this relationship can be understood through economies of scale.

“Electricity markets are different than a lot of markets that they interact with,” Asa Watten, the study’s coauthor and EPRI researcher, told Fortune.

Unlike soybeans or gasoline, where prices are determined by the cost of production, electricity prices are based on cost recovery, or how much of it is consumed. As fixed costs are divided among more consumers and kilowatt hours (the standard unit of energy), more kilowatt hours mean a greater division of fixed costs and lower prices. That’s in addition to load increases from increased data center usage, which causes more generators to come online, many of which are becoming more energy efficient.

There’s a catch to this pattern: It’s not guaranteed to continue, and if the trend reverses, it could signal a broader and bigger problem with the future of AI. The writing may already be on the wall. PJM, the largest power grid operator in the country, projected in a report this week that a $6.3 billion increase in consumer electricity costs over the next three years can be mostly attributed to increased data center power demands. The rise in data center construction—expected to reach $7 trillion in spending by 2030—is already correlated with increased power costs. In Virginia, the state with the most data centers, residential electricity prices have increased by more than 13% in the last year, according to data from the U.S. Energy Information Administration (EIA).

What will determine the future relationship between data centers and electricity costs?

Watten explains that the largest determinant of future electricity prices will be if the rapid and rampant AI buildout lives up to the hype.

“If the grid builds capacity, expecting a lot of demand from data centers, and that doesn’t show up, that could be a clear story of how data centers could increase prices in the future in a way that they did not do in the past,” he said.

Data centers are expected to incur a great deal of fixed costs, and if customers for those data centers aren’t there, “then your denominator is less than you thought it would be,” Watten continued. “You’re spreading those fixed costs amongst fewer people. It’s the opposite of what we want to be doing, so that could increase prices.”

Amid a debate of an AI bubble and when it will pop, there are some signs that investors are growing more skeptical of the technology’s promise. On Thursday, share prices for Tesla and Alphabet took a tumble following both companies announcing an increase in AI capital expenditures.

In an episode of the All-In podcast this week, billionaire investor Mark Cuban warned “a lot of data centers…are going to be turned into pickleball courts” because while hyperscalers are correctly assuming AI adoption will continue to increase, AI will become cheaper to use because of increased power efficiency, meaning all of the capacity being created through data centers will not be necessary.

But there is an optimistic read here, Watten said. He doesn’t like to speculate on what the future of AI holds and what that means for the data center buildout, but generally speaking, energy will continue to become more efficient. Electrification, though more electric vehicles and electric heat pumps in addition to data center growth, could continue to reduce household energy costs in a way that could happen independent from an AI boom.

“This clearly efficiency-increasing thing or total budget-reducing thing could have positive spillovers to your neighbors,” Watten said, “such that more electric cars means that if done well, prices are also going down—or at least not going up.”

Data centers are actually making your electric bill cheaper—but sinking AI demand could change that

HONG KONG (AP) — Artificial intelligence from China is making waves in the United States marketplace.

Raffi Krikorian, the chief technology officer at Mozilla, based in San Francisco, started using the new Kimi K3 model from Chinese startup Moonshot for his regular work shortly after its release last week. He remarked on its responsiveness, finding it quicker than the more established and pricier Claude Fable chatbot from Anthropic. Before K3, he was utilizing another strong Chinese model, Z.ai’s GLM-5.2, for tasks like managing his calendar and emails.

Krikorian's switch to Chinese AI reflects a broader trend among Americans who are increasingly picking Chinese AI solutions that offer higher efficiency at lower costs. Companies such as Coinbase, a cryptocurrency exchange based in the U.S., are turning to these models as a means to cut expenses.

The rise of these Chinese systems has generated concern among some U.S. tech leaders, yet unless there is a broad ban, their appeal to independent developers both in the U.S. and globally is likely to persist.

U.S. policy has restricted China’s access to some advanced technologies, including state-of-the-art AI chips. Treasury Secretary Scott Bessent has suggested that additional sanctions could be implemented to safeguard American intellectual property.

The administration of former President Donald Trump accused Moonshot of potentially using "covert" methods to develop K3, implying some reliance on Anthropic’s Fable. Meanwhile, some U.S. politicians and AI firms, notably Anthropic, have accused Chinese startups of illegally using techniques to replicate their models—a claim that China refutes as unfounded.

The emergence of powerful Chinese AI models this year indicates a shift in the U.S.-China AI rivalry, following the disruptive entry of DeepSeek’s AI model early last year that demonstrated performance similar to U.S. offerings but at a lower cost.

Recent models from startups such as Z.ai (released in June) and Moonshot (released in July) are becoming nearly as capable as leading models from OpenAI and Anthropic. Additionally, Alibaba showcased its Qwen 3.8 Max AI model in July, while DeepSeek revealed a preview of its V4 model earlier in April.

These advancements are yielding tangible results. Curt Meinhold, a technology executive from Greensboro, North Carolina, noted his growing preference for DeepSeek for its utility in generating sales leads and conducting business.

“Most of us don’t really need cutting-edge models like Anthropic’s Mythos or Fable,” he commented. “We just want something that works well enough.”

A July report from Goldman Sachs characterized the Chinese AI models as being at a pivotal moment for broader adoption, spurred by a rising global demand for "agentic" AI that can efficiently manage complex tasks. 

As AI services often charge based on output token counts, the cost differences with Chinese models are significant, as noted by analysts including Alex Colville of the Australian Strategic Policy Institute. “The Chinese models are quite competitive in quality,” Meinhold pointed out, emphasizing the financial advantages.

Currently, the Kimi K3 model from Moonshot is leading in popularity, with recent tracking data showing that the five most utilized models on OpenRouter are Chinese. According to Sensor Tower, K3 amassed over 930,000 downloads shortly after its July debut, marking a staggering 200% increase from the previous week, with around 86,000 of those downloads occurring in the United States—an impressive jump of 387%.

So much interest in K3 led Moonshot to temporarily halt new subscriptions due to overwhelming demand.

Nevertheless, while Chinese AI systems are advancing rapidly, experts indicate they still fall short when it comes to comprehensive capabilities compared to their American counterparts. Anastasios Angelopoulos, co-founder and CEO of Arena, noted that American firms are also exploring competitive models to drive down prices.

The advantage of open-source development is another aspect where Chinese models are thriving, allowing anyone to modify and improve them, in stark contrast to the closed-source models from U.S. companies like Anthropic and OpenAI. Chinese developers could capitalize on this openness to enhance their global reach and adoption, according to Lian Jye Su from the advisory group Omdia.

As the quality of Chinese open-source AI models increasingly rivals their U.S. counterparts, Krikorian pointed out that the landscape is shifting towards models that are predominantly Chinese-built. While discussions around tightening restrictions on Chinese AI models occur in the U.S., several American tech giants, including Microsoft, Meta, and Nvidia, have endorsed a commitment to open AI initiatives.

Moreover, specific U.S. policies have inadvertently given Chinese firms an advantage. For instance, shortly after the U.S. government imposed export controls on Anthropic’s models, Z.ai launched its GLM-5.2, quickly filling the gap left by the U.S. restrictions.

"Whenever an American model faces restrictions, a Chinese alternative can quickly emerge," Angelopoulos explained.

China is also focused on promoting AI technologies internationally. At a recent tech summit in Shanghai, President Xi Jinping advocated for open-source AI and emphasized the objective of increasing global equity, while articulating China’s aim to enhance AI capabilities, particularly in developing nations.

The competitive landscape is shifting, with Chinese firms eager to extend their reach globally. Leading AI startups in China are in the process of securing more investment to subsidize their expansion efforts, including through public offerings.

Both nations are driven to encourage a wide uptake of their AI technologies while carefully safeguarding developments that could enhance their strategic competitors, explained Chelsey Tam from Morningstar.

"The competition has evolved beyond the U.S. versus China, with Chinese labs increasingly competing against each other as well," Angelopoulos noted.

Nevertheless, the surge in AI investment, while promising, raises sustainability questions for these rapidly growing Chinese companies. For instance, Z.ai reported a remarkable 132% revenue increase to 724 million yuan ($107 million) last year, but their net losses rose to 4.7 billion yuan ($694 million).

Looking ahead, the momentum of Chinese AI models is likely to persist, particularly in the U.S. “I encourage anyone serious about their AI needs to evaluate these options,” Krikorian recommended.

Affordable, accessible, and smart: Chinese AI models are making progress in the US market.

A sunlit modern server lab with floor-to-ceiling windows revealing a U.S. city skyline at dawn. In the foreground, sleek racks of servers bear a single Chinese flag sticker and “Open AI Model” labels. A nearby workstation displays open-source AI code running, warm natural light flooding the room to symbolize the surge of cheaper, intelligent Chinese AI models making inroads in America.

Cheaper, open and intelligent: Chinese AI models gain ground, as they make inroads in the US - AP News

- Chinese AI models are gaining popularity in the U.S. for their affordability and efficiency.  
- The newly launched Kimi K3 exceeded demand, prompting temporary subscription suspensions by Moonshot.  
- U.S. restrictions on advanced technologies may inadvertently benefit Chinese AI model adoption.  

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HONG KONG (AP) — China has a hot new product in the United States: artificial intelligence.

San Francisco-based Raffi Krikorian, the chief technology officer at Mozilla, which runs the Firefox browser, switched to Chinese AI startup Moonshot’s Kimi K3 for many of his day-to-day activities within days of the new, powerful model’s launch more than a week ago.

“It just seems snappier,” he said of K3, comparing it to the acclaimed and more expensive Claude Fable chatbot from San Francisco company Anthropic. Earlier, he had been using another high-performing Chinese model, Z.ai’s GLM-5.2, for routine tasks such as managing his calendar, documents and email.

Krikorian is one of a growing number of Americans adopting Chinese AI systems, which are gaining ground around the world because they are more affordable and increasingly efficient. U.S. companies like cryptocurrency exchange Coinbase said they’re switching to Chinese AI models to help trim costs.

Their popularity has frustrated some U.S. tech giants, but short of an outright ban, they’re likely to continue to appeal to independent software developers in the U.S. and elsewhere.

American-led restrictions block China from accessing some of the world’s most advanced technologies including cutting-edge AI chips and U.S. Treasury Secretary Scott Bessent has warned more sanctions could be coming to protect American intellectual property.

U.S. President Donald Trump’s administration on Wednesday accused Moonshot of using “covert” but not necessarily illegal methods to build K3 off the back of Anthropic’s Fable. Some U.S. politicians and AI companies including Anthropic have accused Chinese startups of illicit “distillation” of their models to extract their technologies, a claim that Beijing rejects as “groundless.”

China’s AI models are cheaper and ‘good enough’

The rapid rise of cutting-edge Chinese AI models this year shows the China-U.S. race in AI has moved on from early last year, when Chinese startup DeepSeek shook up the U.S. technology industry and put China on the map with an AI model that performed on par with those in the U.S. but much more cheaply.

Read More

The latest AI models launched by startups Z.ai, or Zhipu, in June, and Moonshot in July are nearly as intelligent as the frontier models from OpenAI and Anthropic, experts say. Also in July, China’s Alibaba previewed its Qwen3.8 Max AI model. In April, DeepSeek rolled out previews of its latest V4 model, challenging OpenAI’s GPT and Google’s Gemini.

Those constant advances are bearing fruit. Curt Meinhold, a Greensboro, North Carolina-based technology executive, said he increasingly prefers to use DeepSeek for tasks such as finding business leads or ways to generate sales.

“At the end of the day, most of us, the vast majority of us, 90 plus percent, don’t need (Anthropic’s) Mythos or Fable,” said Meinhold, who founded digital legacy platform LilyList. “Like, we just don’t need it, we need something good enough.”

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Chinese AI models are reaching a “critical stage” for wide adoption, U.S. investment bank Goldman Sachs wrote in a July research report, especially when a surge of global “agentic” AI usage, which requires the AI models to autonomously conduct multistep, complex tasks, is driving higher demand for cost effective AI models.

AI prices are calculated per million tokens for both input and output, so the use of AI “agents” is dramatically compounding cost differences, according to analysts including Alex Colville of the Australian Strategic Policy Institute.

“The Chinese models, you know, I find them to be pretty close on code and research,” said Meinhold. “If I can pay a handful of cents per million output tokens versus 30 bucks or 40 bucks or 50 bucks, then it’s good enough.”

Moonshot’s Kimi K3 leads, but Chinese AI models have limits

Based on data over the past month, the top five most popular models on OpenRouter, a platform that tracks data across AI models, were Chinese.

Estimates from Sensor Tower, a market intelligence firm, showed Kimi had more than 930,000 downloads during the week after K3’s July release, an increase of 200% from the week before. In the U.S. it was downloaded around 86,000 times, a 387% jump.

K3 proved so popular that Moonshot had to temporarily suspend new subscriptions after overwhelming demand pushed its capacity close to its limits.

Still, while Chinese models are becoming serious competitors to the U.S., they lag American AI leaders across their overall, full-range capabilities, said Anastasios Angelopoulos, co-founder and CEO of Arena, a platform for evaluating AI systems.

And U.S. AI firms are also looking for more options to reduce pricing, such as with cheaper alternatives of competitive models, added Yasir Atalan, with the Center for Strategic and International Studies.

US policy could boost Chinese AI models

Most Chinese AI models are open-source — meaning anyone can examine and build on them — at a time when frontier models from U.S. companies like Anthropic and OpenAI are closed-source.

Chinese model vendors are expected to leverage open-source software to promote their global usage and adoption, said Lian Jye Su, of the technology research and advisory group Omdia.

As Chinese open-source models are increasingly almost as good as closed systems made by leading U.S. companies, said Mozilla’s Krikorian, “the open frontier is becoming increasingly Chinese-built.” While the U.S. weighs restricting Chinese AI models, a group of American tech firms including Microsoft, Meta and Nvidia signed an open letter published Friday backing “open” AI models.

Other U.S. tech policies also at times give China an upper hand, some experts say. China’s Z.ai released its GLM-5.2 model in mid-June, not long after the Trump administration put export controls on Anthropic’s Fable and Mythos models, keeping them offline for more than two weeks.

“Restricting an American model can immediately create an opening for a Chinese competitor,” said Arena’s Angelopoulos.

Chinese AI models look to expand globally

In China, people and businesses have rapidly embraced AI technologies that have prospered with state support. Chinese tech companies like Huawei and Tencent are also embedding AI in devices such as smartphones, AI glasses and humanoid robots.

Now China is increasingly looking to dominate AI abroad, too. At a flagship technology summit in Shanghai, Chinese President Xi Jinping championed open-source AI models and the importance of promoting greater global equity, while pledging Chinese involvement in raising AI capabilities especially in developing nations.

As is true for many other industries in China, intense competition at home is driving companies to expand globally. Leading Chinese AI startups are now raising more funding to support that effort, including through public share offerings.

Both China and the U.S. will want to “encourage widespread adoption of their AI ecosystems, while safeguarding technologies that could materially strengthen strategic rivals,” said Chelsey Tam, with investment research firm Morningstar.

“The competition is no longer simply the United States against China; the Chinese labs are also putting a lot of pressure on one another,” Angelopoulos said.

But as is the case in the U.S., huge investments in AI have also raised concerns over sustainability of these Chinese startups. Z.ai, for example, reported its revenue surged 132% to 724 million yuan ($107 million) last year, but net loss jumped 60% to 4.7 billion yuan ($694 million).

For now, Chinese AI models will likely continue to march ahead including in the U.S. “I would highly recommend anyone doing any serious AI load to at least evaluate it,” said Krikorian.

___

O’Brien reported from Providence, Rhode Island. AP Business Writer Kelvin Chan in Toronto contributed to this report.

Cheaper, open and intelligent: Chinese AI models gain ground, as they make inroads in the US

In light of growing environmental issues and the potential effects of AI data centers on the workforce, Jobs for Justice East Tennessee is taking the initiative to facilitate discussions among residents, as there currently isn't an established platform for public dialogue. Officials are addressing community concerns by responding to inquiries about these developments.

Chuck Corra, co-founder of AppPodlatcha, emphasizes the necessity of keeping the public well-informed about the implications of AI data centers, especially regarding their influence on local employment. "Understanding the scope of these projects and their repercussions on jobs is crucial," Corra remarked.

Event organizers note that while the recent one-year moratorium on AI data centers marks a positive step, its protection only extends to the unincorporated areas of the county. 

Regarding ongoing projects, Nathan Shew from the Tri-State Musicians Union expressed optimism about converting the old Hamilton County Jail into a music studio. However, he cautioned that if the AI component is not carefully managed, it could ultimately be detrimental. "If we end up with a large generative data center simply churning out art, it won’t contribute anything meaningful," Shew explained.

The impact of AI data centers extends to everyone, as highlighted by Sandy McRae, the president of the League of Women Voters. She pointed out that the implications of AI reach all job sectors in the region, noting that it's imperative for voters to stay informed about the decision-making processes behind these projects.

"The representatives are accountable to us; they manage our funds, and we deserve transparency regarding what we're getting in return for our investment," McRae stated.

AI data center workshop seeks to address inquiries from Hamilton county residents

Prompt: A bright community center bathed in warm natural light, adult residents seated around sleek server racks with soft white rack lights, an expert at the front pointing to a large screen titled “Hamilton County AI Data Center Workshop,” attendees with notepads raise their hands, a banner overhead reads “Hamilton County Workshop,” potted plants by the windows, wooden floors conveying a welcoming, informative atmosphere.

AI data center workshop aims to answer Hamilton county residents questions - WTVC

- Jobs for Justice East Tennessee addresses local concerns about AI data centers and workforce impacts.  
- A one-year moratorium on AI centers only protects unincorporated county areas, raising concerns.  
- Community leaders emphasize the need for public awareness and informed decision-making on AI projects.  

From environmental concerns to how AI data centers could impact the local workforce, officials from Jobs for Justice East Tennessee say with no current way for the public to have a formal discussion about the topic, they’re doing it themselves by answering an questions residents may have.

"It's really important that people are fully informed about what they are, the implications, and most importantly, with this discussion today, what the impact on the local jobs are going to be, " Cofounder of AppPodlatcha Chuck Corra says.

According to event officials, the recently passed one year moratorium on AI data centers is a step in the right direction, but it only protects the unincorporated parts of the county.

Photo: WTVC.

As for projects currently underway, Nathan Shew with the Tri-State Musicians Union says the plan to turn the old Hamilton County Jail into a music studio could be beneficial, but if the AI portion of it isn’t checked, it could do more harm than good.

...But if we just have a big old generative data center that's creating that artwork, that doesn't do anything. Shew says.

But how do AI data centers like the purposed one for the old Hamilton County Jail affect you?

AI impacts everyone. I mean, it impacts all jobs in this area. Sandy McRae League of Women Voters President says.

Sandy McRae with the League of women voter of Chattanooga says AI Data center is a complex issue, but its up to the voters be informed on how decisions are being made.

The representatives do work for us, and they are spending our money, and we need to know what we're getting for for the investment. McRae says.

AI data center workshop aims to answer Hamilton county residents questions

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Quote of the day by Vladimir Putin on AI: 'Whoever becomes the leader in this sphere will become the ruler... - Yahoo

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A Seattle resident named Lisa Booth, who has been battling stage 4 metastatic breast cancer for over 11 years, has partnered with fellow cancer survivor Steve Brown to create an innovative AI tool known as CureWise. This platform is specifically designed to support cancer patients in managing their medical records, understanding their diagnoses, exploring treatment options, and potentially discovering clinical trials that could be life-saving.

The inception of CureWise took place in February 2025, and since then, it has proven effective in assisting Booth, Brown, and other users in navigating the complexities of cancer treatment. The tool emerged from their own experiences with cancer, addressing the challenges they faced in tracking treatments and care.

Booth, having lived with cancer for more than a decade, often used spreadsheets and various technological tools to monitor new therapies and clinical studies. This experience sparked her desire for a more streamlined method to process vital information regarding her health journey.

CureWise employs AI to analyze a patient’s diagnosis, medical history, and overall health, aiming to connect them with appropriate treatments and clinical trials more efficiently. It’s important to note that while CureWise is not a cure for cancer, it significantly aids in uncovering treatment possibilities.

As the vice president of operations for CureWise, Booth utilized the tool during its prototype phase last summer, particularly when her cancer returned, providing her with crucial information about available trials.

“I’m not joking; this has been the most enjoyable experience in both my professional and personal life,” Booth shared, reflecting on the product’s development.

Co-founder Steve Brown, who was diagnosed with blood cancer after being displaced by the Palisades fire in January 2025, leveraged the AI tool to educate himself about his condition. “I directed this incredible AI tool at my own medical records, which fundamentally changed everything regarding the uncertainty of my illness,” he remarked, having learned about a rare mutation through the platform.

Regina Brown, another cancer survivor, recounted her experience with CureWise in an interview with KIRO 7. After an incident in Olympia last October led to the discovery of a growth around her thyroid, she faced a rapid cancer diagnosis months later. With her husband battling stage 4 lung cancer, she felt the weight of having to inform their daughters about her diagnosis. 

In stark contrast to her husband's lengthy research efforts over a decade, Brown utilized CureWise to hasten her treatment process, stating, “From my diagnosis on June 1st, I already had surgery by July 13th.” Her husband is also now using the tool to locate targeted therapies in far less time than it took previously.

The developers of CureWise have incorporated strict privacy protocols to safeguard patient information. Booth assured users that all personal data is de-identified, securely stored, and not employed to train large language models. “Users have complete control over their data and can remove it at any time,” she emphasized, underscoring the platform's commitment to user privacy.

Expressing profound appreciation for the tool, Regina Brown described it as transformative for her and her family, feeling it played a crucial role in their journey. “It was an answer, an answer to prayer,” she said, highlighting the peace of mind CureWise provided her in managing her cancer. This newfound empowerment enabled her to speak with confidence about her diagnosis to her daughters, attributing her upcoming post-surgery appointment to the support she received from the AI platform.

Cancer survivors from WA with tech expertise create AI platform to assist fellow cancer patients.

Two adult cancer survivors—one woman, one man—in a bright, sunlit modern office. Warm morning light streams through large windows as they stand side by side, one pointing at a large touchscreen showing an AI-powered cancer support dashboard with a gold awareness ribbon icon and friendly patient charts. Behind them a whiteboard features a hand-drawn outline of Western Australia, hinting at their roots, while potted plants and laptops on the desk underscore a hopeful, collaborative spirit.

Cancer survivors with WA roots and tech skills develop AI platform to help other cancer patients - KIRO 7 News Seattle

- Lisa Booth and Steve Brown developed CureWise, an AI tool for managing cancer treatment.  
- CureWise helps patients navigate medical records and find clinical trials for faster treatment.  
- The tool ensures patient privacy with de-identified data and user control over information.  

A Seattle woman living with stage 4 metastatic breast cancer for 11 years, Lisa Booth, has co-developed an artificial intelligence tool called CureWise.

The tool, created with fellow cancer survivor Steve Brown, who is originally from Wenatchee, aims to help countless cancer patients manage their medical records, cancer diagnoses, treatment and maybe even help find clinical trials that could save lives.

Development of CureWise, according to Brown and Booth, began in February 2025, and it has already demonstrated success in aiding its creators and other patients in navigating their cancer journeys.

CureWise was born from Booth’s personal struggle as well as Brown’s.

For Booth, living with cancer for more than a decade, she had experience tracking new treatments and clinical trials using spreadsheets and other tech tools. She was doing all this while living with cancer and still believed there had to be a simpler way to process all the information.

The AI platform she helped design actually can help learn about a patient’s diagnosis, their overall medical conditions and history, and maybe find specific treatments or clinical trials faster and more effectively that could help them.

While developers emphasize CureWise is absolutely not a cure for cancer, it can help patients find treatment options.

Both Booth and Brown used the tool they built to navigate their own illnesses; they admit the builders became patients also.

Lisa Booth, who serves as vice president of operations for CureWise, says she applied her medical records to the tool during its prototyping stage last summer.

She used it to understand available trials when her breast cancer recurred.

“I’m quite serious, I’ve never had this much fun in my entire professional and personal life,” Booth said about the development process.

Steve Brown, co-founder of CureWise, was diagnosed with blood cancer after being displaced from his Southern California home by the Palisades fire in January 2025.

He used the AI tool to educate himself about his condition.

“I kind of took this amazing tool of AI and pointed it at my own medical record,” Brown said, explaining that gaining visibility into his condition “changes everything” by addressing the “scariest thing, the unknown.”

Through the tool, Brown learned he had a rare mutation.

Another cancer survivor, Regina Brown, also spoke to KIRO 7 about her journey with cancer and the AI platform. She credits CureWise with significantly accelerating her treatment path.

After being assaulted in Olympia last October, a visit to the emergency room revealed a growth in the area around her thyroid. Months later, she found out the growth had doubled, and in June, testing revealed an unexpected cancer diagnosis.

“My husband has stage 4 lung cancer so the fact of sitting our daughters down once again and telling them now their other parent has cancer was very daunting,” Brown said.

She contrasted her rapid treatment with her husband’s decade-long experience of “old-fashioned” research.

With CureWise, Brown said, “I went from diagnosis date of June 1st, I already had surgery by July 13th.” Her husband also began using the tool to find targeted therapy in months, rather than years.

The developers say they have implemented safeguards to protect patient privacy when using CureWise.

Lisa Booth confirmed that patient data is de-identified, stored securely, and not used to train any large language models.

“You have absolute control. You can remove your data at any point in time,” Booth stated, highlighting user autonomy.

Regina Brown expressed deep gratitude for the AI tool, describing it as life-changing for her and her family. She believes CureWise helped her, definitely helped her husband, and absolutely did save her family.

She teared up, saying, “It was an answer, it was an answer to prayer, it was just an answer.”

She admitted that finding peace of mind in her ability to manage her cancer with the tool’s assistance was transformative.

It also gave her confidence to talk to her daughters about her diagnosis, and she felt empowered with all the information she received through using the AI platform.

She says she is scheduled for a post-operation appointment next week, an outcome she attributes to the assistance of the AI tool.

©2026 Cox Media Group

Cancer survivors with WA roots and tech skills develop AI platform to help other cancer patients

Oklahoma has introduced an innovative artificial intelligence platform designed to enhance the efficiency of state agencies and elevate customer service standards.

The Office of Management and Enterprise Services (OMES) has rolled out BEACON, a comprehensive state platform that establishes a consistent and secure approach to utilizing AI. State officials emphasized that this platform comes equipped with robust security measures, governance structures, and data standards aimed at minimizing redundancy among agencies while providing a unified framework for creating AI-driven applications.

“Oklahoma aspires to rank among the top ten states for business, which means leveraging the most advanced tools at our disposal,” stated Governor Kevin Stitt. “We are empowering our agencies to optimize their operations, deliver quicker outcomes, and serve the residents of Oklahoma more efficiently.”

The launch of BEACON follows the recent appointment of Tai Phan as Oklahoma’s inaugural Chief AI and Technology Officer, whose role is to guide the responsible and secure implementation of AI throughout government operations.

The initial offerings developed through BEACON are referred to as “lighthouse applications,” designed to demonstrate how AI can tackle governmental challenges and establish reusable models for future initiatives. Currently, two lighthouse applications are in beta testing: the Administrative Rules Modernization tool and the Procurement Guidance Assistant.

The Administrative Rules Modernization tool is crafted to assist lawmakers and state employees in assessing administrative rules, pinpointing opportunities for regulatory simplification, and alleviating unnecessary burdens on both citizens and businesses.

“We have invested significant hours in reviewing administrative regulations to ensure alignment with the state Legislature's intent and the needs of Oklahomans,” commented Senator Micheal Bergstrom, R-Adair. “This tool will enhance our effectiveness in this crucial work and uphold government accountability.”

On the other hand, the Procurement Guidance Assistant is designed to offer state workers real-time advice on purchasing policies and procedures, aiming to streamline decision-making processes while ensuring consistency and compliance.

“Our agencies provide essential services daily, and procurement is vital to that mission,” explained Amanda Otis, the state purchasing director. “This technology will enable teams to operate more efficiently while adhering to regulations, allowing them to concentrate on serving the people of Oklahoma.”

OMES highlighted that these tools are designed to support employees in their day-to-day tasks, reducing the time spent searching for information and enhancing precision, thereby assisting agencies in better serving the citizens of Oklahoma.

Oklahoma introduces a new AI platform to enhance state agencies.

A sunlit modern government office in the Oklahoma State Capitol, with a single Oklahoma flag billowing outside the window. At a polished wooden desk floats a translucent AI dashboard showing vibrant service icons and data charts—“Licensing,” “Permits,” “Health Services”—as a suited official interacts with it, symbolizing the new AI platform streamlining state agencies.

Oklahoma launches new AI platform to improve state agencies - KOKH

- Oklahoma launched BEACON, a new AI platform for state agencies to enhance efficiency.  
- The platform includes security, governance, and data standards to reduce agency duplication.  
- Two "lighthouse applications" are in beta testing to address government challenges effectively.  

Oklahoma has launched a new enterprise artificial intelligence platform aimed at helping state agencies work more efficiently and improve customer service.

The Office of Management and Enterprise Services announced the rollout of BEACON, a statewide platform designed to provide a shared foundation for using AI “safely, consistently and effectively.” State officials said the platform includes built-in security, governance and data standards intended to reduce duplication across agencies and give them a common framework for developing AI-powered tools.

“Oklahoma is committed to being a top ten state for business, and that means using the best tools available,” Gov. Kevin Stitt said. “We are equipping our agencies to work smarter, deliver results faster and serve Oklahomans more effectively.”

The launch follows the appointment of Oklahoma’s first Chief AI and Technology Officer, Tai Phan, who is leading efforts to implement AI “in a secure, responsible and practical way across government.”

The first tools built through BEACON are described as “lighthouse applications,” projects intended to show how AI can address government challenges while creating models that can be reused for future work. Two lighthouse applications are currently in beta testing: an Administrative Rules Modernization tool and a Procurement Guidance Assistant.

The Administrative Rules Modernization tool is designed to help policymakers and state employees review administrative rules, identify opportunities to simplify regulations and support efforts to reduce unnecessary burdens on citizens and businesses.

“We’ve spent countless hours reviewing administrative rules to ensure they reflect the intent of the state Legislature and serve the people of Oklahoma,” said Sen. Micheal Bergstrom, R-Adair. “This tool will help us do that work more effectively and ensure government stays accountable.”

The Procurement Guidance Assistant is intended to provide state employees with real-time guidance on purchasing policies and procedures, with the goal of helping agencies make decisions more efficiently while improving consistency and compliance.

“Our agencies deliver critical services every day, and procurement plays a key role in that work,” said Amanda Otis, state purchasing director. “This technology will help teams move more quickly while still following the rules, so they can stay focused on serving Oklahomans.”

OMES said the tools are intended to support employees in daily work by reducing time spent searching for information and improving accuracy, with the broader goal of helping agencies better serve Oklahomans.

Oklahoma launches new AI platform to improve state agencies

When Joe Spector's corgi, Eddie, ingested four M&Ms, the co-founder of Hims faced a frantic challenge finding an emergency veterinarian to help. A clinic directed him to a pet poison hotline, while another option was over an hour away with a wait time of four hours. Ultimately, the vet bill totaled a staggering $2,000.

This distressing experience in 2021 led Spector to realize, "it doesn’t have to be this way," as he recounted in an interview with Fortune.

This revelation prompted the creation of Dutch, a veterinary telehealth platform launched by Spector on July 1, 2021, following his success with Hims & Hers, a direct-to-consumer telehealth company recognized for addressing issues like hair loss and sexual health. Both businesses have since expanded significantly to encompass a wider range of health matters.

Dutch recently celebrated its fifth anniversary, providing members with telehealth services that allow video consultations with veterinarians for a subscription fee of $100 annually, which covers up to five pets. This fee is comparable to the price of a single visit to a conventional veterinary practice. With operations now stretching across 35 states—up from just eight at its inception—Dutch is benefiting from a more favorable regulatory environment for veterinary telemedicine. The platform has facilitated millions of consultations and boasts over 100,000 active members, as reported by the company. In early 2022, Dutch secured $20 million in funding to further enhance its platform, with the investment led by Forerunner Ventures.

While the company did not disclose its current revenue or valuation, Spector noted significant revenue growth, with an increase of 5.5 times from 2022 to 2023, followed by a 2.2 times rise from 2023 to 2024, and a further 1.8 times boost anticipated between 2024 and 2025.

In a strategic shift to invigorate the business, Spector made a bold decision last year to terminate the services of an outside marketing agency that had been costing the company around $50,000 monthly for just five creative pieces, which averaged $10,000 each.

"This approach was both costly and restrictive, especially since marketing new products is all about testing what resonates," Spector explained.

He then assembled an in-house marketing team that utilizes AI tools to generate diverse content types, including static ads and fully animated commercials. This shift has allowed Dutch to produce about 50 pieces of content monthly—a tenfold increase. The internal operation now costs approximately half a million dollars less than the previous agency arrangement, facilitating more effective testing to engage pet owners, many of whom may be unaware of telehealth options for veterinary care.

"We need to enhance trust and educate consumers on how this service functions and its benefits," Spector emphasized.

Dutch's advertising strategy has evolved, with its investment on Meta increasing from 5% of ad spending to around 25%. The efficiency of the new team has already yielded a 20% reduction in customer acquisition costs from January 2026 to April and an impressive 20% audience growth per month between February and March, according to company data. AI is also being harnessed for measurement tasks such as A/B testing, brand-lift studies, and refining the search strategy.

Spector is quick to credit his marketing team for these advancements, stating, "It’s not just the software—it's the people behind it that drive success."

The aim for Spector is to elevate Dutch’s market presence. Initially, Dutch capitalized on immediate needs through bottom-funnel Google searches targeting pet owners in crisis. The next step is to enhance brand awareness so pet owners consider Dutch before emergencies arise.

To further this initiative, Dutch enlisted former Olympic figure skater Tara Lipinski as a brand ambassador. Lipinski, who became a customer after losing her home in the Los Angeles fires and needing veterinary care for her dog, connects emotionally with the brand's mission.

"I want our customers to feel a sense of relief,” Spector concluded.

A cofounder of Hims dismissed his entire marketing team for AI, and now his tele-vet is experiencing 20% monthly growth.

A bright home office flooded with warm morning light: in the shadowed corner, two empty desks and chairs pushed back hint at the departed marketing team. Center stage, the Hims logo is emblazoned on a sleek laptop showing a tele-vet video call—an enthusiastic veterinarian examining a happy dog while a bold “+20%” growth arrow climbs on a side monitor.

A Hims cofounder fired his entire marketing team for AI. Now his 24/7 online vet service is growing 20% a month - Fortune

- Joe Spector founded Dutch after struggling to find urgent vet care for his corgi.  
- Dutch offers video vet visits for $100 annually, expanding to 35 states since launch.  
- The company shifted to in-house marketing, increasing content production and reducing costs significantly.  

When Joe Spector’s corgi, Eddie, ate four M&Ms, the Hims cofounder spent hours trying to find an emergency vet who could see him. One office pointed him to a pet poison hotline, and another was an hour away and had a four-hour wait. The bill came out to $2,000.

Spector thought at the time “this does not have to be that way,” he told Fortune.

That stressful scramble in 2021 sparked the idea for Dutch, the veterinary telehealth company Spector launched on July 1 of that year after helping build and take public Hims & Hers, the direct-to-consumer telehealth brand best known for treating hair loss and sexual wellness. Those companies have since grown exponentially to cover an array of health concerns.

Dutch, which just marked its fifth anniversary, offers members video visits with veterinarians for a flat $100 a year covering up to five pets. That amounts to roughly the cost of a single in-person visit at a regular veterinary office. The company now operates in 35 states, up from eight at launch, as more states loosen restrictions on veterinary telemedicine. The company has logged millions of interactions and now counts more than 100,000 active members, according to the company. Dutch raised $20 million in early 2022 to scale the platform, in a round led by Forerunner Ventures.

The company declined to share its current revenue and valuation, but its revenue grew 5.5x between 2022 and 2023, 2.2x between 2023 and 2024, and 1.8x between 2024 and 2025.

Firing his agency to grow the business

Although Dutch is clearly charting its growth path now, it was a bit stagnant for a while. Now Spector is making a bigger bet on how the company markets itself.

Late last year, Spector said, Dutch was paying an outside agency roughly $50,000 a month to produce five pieces of creative material, or about $10,000 apiece.

“It’s both expensive and it’s just limited because so much of marketing, especially with a new product, is just testing to see what’s resonating,” Spector said.

So he fired that agency. That drastic move is somewhat reminiscent of Bolt’s CEO telling Fortune at its Workplace Innovation Summit in May he had ditched his entire human resources team, although the executives had very different motivations for their moves.

In its place is a new in-house marketing team leaning heavily on AI tools to generate content, from static ads to full animated and live-action commercials. Now Dutch produces about 50 pieces of content a month internally, or a 10x jump, Spector said. That’s enough work to cost roughly half a million dollars a month through an agency, he said. Just as important as the savings, he said, is the ability to test what actually lands with pet owners who often don’t know virtual vet care exists.

“We have to get over the trust factor,” he said. “We have to educate consumers on how this even works, or like what’s the use case.”

Dutch’s presence on Meta has grown from about 5% of its ad spend to roughly one-quarter. Since the new team’s first full month, the company has cut its customer acquisition cost by 20%—comparing January 2026, before the team started, with April—and grew its audience 20% month over month from February to March, according to the company. Spector said Dutch is also using AI on the measurement side, for A/B testing, brand-lift studies, and its search strategy.

To be sure, Spector is quick to credit the people, not just the software.

“I shouldn’t take the credit—it’s the marketing folks,” he said. The team, he added, is what makes leaning into the tools possible.

For Spector, the goal is to move Dutch upstream. The company built its early growth on bottom-of-funnel Google search, reaching pet owners in the middle of an emergency, he said. Now he wants to grow brand awareness, so that owners think of Dutch before the crisis hits.

That’s partly why Dutch brought on former Olympic figure skater Tara Lipinski as a brand ambassador. Lipinski, Spector said, came to Dutch as a customer after losing her home in the Los Angeles fires and needing care for her dog.

“One of the feelings I want people to have is this sense of relief,” Spector said.

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