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# The Compute Economy Has Arrived, and It Rewards Organizations That Adapt Quickly and Strategically
- URL: https://datacatalyst.org/the-compute-economy-has-arrived-and-it-rewards-organizations-that-adapt-quickly-and-strategically/
- Published: 2026-10-22T11:03:18.000Z
- Updated: 2026-10-22T11:03:18.000Z
- Description: Cheap computing power has made AI an everyday business tool. Companies moving fast with a clear plan are pulling ahead, and light, national rules help America lead.
- Author: DCI
- Tags: Compute, AI, AI Adoption, Training, and Trust, US-China competition, ai policy, #hero-immersive

Cheap, abundant computing power, or “compute,” has made AI an everyday tool for organizations of all kinds in just a few short years. Stanford’s AI Index [found](https://hai.stanford.edu/assets/files/hai%5Fai-index-report-2025%5Fchapter1%5Ffinal.pdf?ref=datacatalyst.org) that the cost of running an AI model as capable as the original ChatGPT fell about 280-fold within two years of its November 2022 launch. Entrepreneurs quickly turned cheap compute into a flood of new AI software, apps, platforms, and tools, and by 2025, 88 percent of organizations [surveyed by McKinsey](https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-2025?ref=datacatalyst.org) were already using AI in at least one part of their business. The more people use AI, the more computing power it takes to run: chips to train models and answer requests, networks to move data, and processors in machines making decisions in the real world. As the tools get cheaper, the uses multiply, and so does demand for the infrastructure behind them. Combined with proprietary data, robots, drones, and sensors, these AI tools have already changed how organizations write software, sell products, make movies, deliver goods, fight wars, and more.

Now is the moment for leaders of organizations to put AI to work quickly and strategically, and for U.S. policymakers to keep the rules light, simple, and national. Leaders are caught between the fear of falling behind and the fear of betting badly, and for those who want to win, the evidence so far favors moving fast with a clear plan. The organizations doing that are pulling ahead, while those that wait are almost certainly losing customers and market value, whether quietly or publicly. Washington’s market-led, light-touch approach to the internet in the 1990s helped American companies build and lead it, and the same approach gives America its best chance to lead the global compute economy.

While America leads the world in funding AI by a wide margin, [Chinese](https://hai.stanford.edu/assets/files/ai%5Findex%5Freport%5F2026%5Fchapter%5F4%5Feconomy.pdf?ref=datacatalyst.org) [companies](https://thenextweb.com/news/stanford-ai-index-2026-china-us-performance-gap?ref=datacatalyst.org) have nearly matched American AI model performance, so victory will ultimately belong to whoever puts AI to work fastest and smartest. American companies drew about $286 billion in private AI investment in 2025, more than 20 times as much as China, though that count doesn’t include investment from China’s more opaque state-backed funds. The best American AI models led Chinese rivals by wide margins in 2023, but by March 2026 [that lead had shrunk](https://thenextweb.com/news/stanford-ai-index-2026-china-us-performance-gap?ref=datacatalyst.org) to less than 3 percent. Chinese models are now also [downloaded more often](https://equalocean.com/news/2026073122070-chinese-models-account-41-hugging-face-downloads-overtaking-us?ref=datacatalyst.org) than American ones on Hugging Face, the most popular platform for sharing open-source AI models.

AI has already taken over much of the routine work in software development and customer service. In February 2026, Spotify co-CEO Gustav Söderström [told investors](https://techcrunch.com/2026/02/12/spotify-says-its-best-developers-havent-written-a-line-of-code-since-december-thanks-to-ai/?ref=datacatalyst.org) that the company’s best developers “have not written a single line of code since December,” because AI now writes it for them. [At Google](https://www.techspot.com/news/112152-google-ai-now-generates-75-new-code-up.html?ref=datacatalyst.org), AI writes about 75 percent of new code, which engineers then review, up from about 25 percent in late 2024\. [Salesforce](https://dc.fortune.com/2025/09/02/salesforce-ceo-billionaire-marc-benioff-ai-agents-jobs-layoffs-customer-service-sales?ref=datacatalyst.org), for its part, cut its human support staff by more than 40 percent after AI agents took over roughly half of its customer conversations.

Elsewhere, AI shopping assistants have quickly become one of retail’s most powerful sales tools. During Amazon Prime Day in June 2026, shoppers who reached U.S. retail sites through AI assistants were [40 percent more likely to buy](https://business.adobe.com/blog/2026-prime-day-insights?ref=datacatalyst.org) than other shoppers, after being 23 percent less likely to buy just a year earlier. In addition, [Amazon says](https://www.modernretail.co/technology/amazon-says-its-ai-shopping-assistant-is-gaining-traction-with-rufus-users-up-115/?ref=datacatalyst.org) its own Rufus assistant, used by 300 million customers in 2025, helped bring in nearly $12 billion in additional annual sales. Meanwhile, at Walmart, shoppers who use the company’s [Sparky AI assistant](https://talkbusiness.net/2026/07/the-supply-side-walmarts-sparky-shopping-agent-drives-more-sales/?ref=datacatalyst.org) spend about 35 percent more than those who don’t. Each of these interactions is another request for computing power, multiplied across hundreds of millions of customers.

And on the West Coast, despite widespread industry trepidation and pushback, Hollywood has started using AI to make films faster and cheaper. In March 2026, [Netflix bought InterPositive](https://news.bloomberglaw.com/artificial-intelligence/netflix-acquires-ben-affleck-founded-ai-moviemaking-business?ref=datacatalyst.org), an AI postproduction company founded by actor and filmmaker Ben Affleck. More recently, [Netflix said](https://engadget.com/2217157/netflix-says-it-s-already-used-ai-in-roughly-300-titles-this-year?ref=datacatalyst.org) it had used generative AI on roughly 300 of its films and shows in 2026, mostly in post-production.

Paired with robots and drones, AI now moves goods and people, with results that range from faster toilet paper to faster medicine to novel warfare tactics. Walmart says its [drone delivery partnership](https://www.mediapost.com/publications/article/411138/walmart-partners-with-alphabet-subsidiary-for-dron.html?ref=datacatalyst.org) [with Wing](https://www.axios.com/2026/01/11/walmart-drone-delivery-wing-los-angeles-miami?ref=datacatalyst.org), a subsidiary of Google parent Alphabet, will reach about 40 million American customers by the end of 2026\. Zipline, a South San Francisco company that began by delivering blood in Rwanda in 2016, has [completed more than 2 million deliveries](https://mugglehead.com/drone-leader-zipline-surpasses-2m-delivery-milestone-raises-additional-us600m/?ref=datacatalyst.org) of medical supplies, food, and retail goods. [Waymo](https://coloradobiz.com/waymo-launches-public-robotaxi-service-denver/?ref=datacatalyst.org), another Alphabet company, now completes more than 500,000 paid driverless trips a week. Self-driving vehicles show how computing is moving beyond data centers and into machines that have to make decisions in real time. And [in Ukraine](https://www.yahoo.com/news/articles/over-80-every-battlefield-hit-073425388.html?ref=datacatalyst.org), drones now carry out about four of every five successful strikes against Russian forces, according to President Volodymyr Zelensky. As a character in the Paramount+ drama *Special Ops: Lioness* memorably put it, the fighting there is like “[World War One meets *Star Wars*.](https://theartsdesk.com/tv/lioness-season-3-paramount-review-which-war-worse-hell?ref=datacatalyst.org)” 

Companies making the most money from AI are changing how they operate around it. In McKinsey’s 2025 survey, only about 6 percent of organizations earned at least 5 percent of their operating profit from AI. Those high performers were [nearly three times as likely](https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-2025?ref=datacatalyst.org) to have redesigned their workflows and put senior leaders in charge of the change. For executives, boards, and investors, the test is whether AI helps a company serve customers better and build a business model that will endure.

Moving too slowly can be brutal, but moving fast in the wrong direction can be just as costly. [Chegg](https://the-captable.com/2026/05/pandemic-maketh-chegg-pandemic-taketh-away-ai-finished-the-job/?ref=datacatalyst.org), the online homework-help company, [was once worth](https://startup.pk/how-chegg-lost-14-billion-to-a-chatbot/?ref=datacatalyst.org) about $14.7 billion. Then students discovered ChatGPT. Its stock plunged 48 percent after its CEO acknowledged the threat in May 2023, and by October 2026 Chegg was worth roughly [$80 million](https://companiesmarketcap.com/chegg/marketcap/?ref=datacatalyst.org).

AI is also [changing the economics of software](https://www.saastr.com/beyond-the-saaspocalypse-the-winners-and-losers-of-2026-so-far/?ref=datacatalyst.org). As AI agents take on more work, usage-based businesses such as Snowflake and Datadog can benefit, while companies charging by user, such as HubSpot and monday.com, face pressure on their pricing models. The advantage will go to companies that change what they offer and how they make money from it.

And AI is changing careers along with companies. Stanford researchers [found](https://siepr.stanford.edu/publications/working-paper/canaries-coal-mine-six-facts-about-recent-employment-effects-artificial?ref=datacatalyst.org) weaker employment among young workers in occupations highly exposed to AI, while PwC [found](https://www.pwc.com/id/en/media-centre/press-release/2026/english/ai-jobs-barometer-en.html?ref=datacatalyst.org) faster growth and higher pay in jobs requiring AI skills. 

America’s light-touch approach to the early internet remains the best guide for AI, because it let American companies build and lead the global internet economy while Congress stepped in on specific harms as they arose. The United States built the early internet, from the Pentagon-funded [ARPANET](https://www.darpa.mil/about/innovation-timeline/arpanet?ref=datacatalyst.org) in 1969 to [Mosaic](https://timeline.web.cern.ch/node/793?ref=datacatalyst.org), the 1993 browser created at the University of Illinois that brought Tim Berners-Lee’s World Wide Web to a mass audience. In 1997, President Clinton’s [Framework for Global Electronic Commerce](https://clintonwhitehouse4.archives.gov/WH/New/Commerce/summary.html?ref=datacatalyst.org) declared that “the private sector should lead” and that “governments should avoid undue restrictions on electronic commerce.” Congress still acted on specific problems, such as [protecting children’s privacy](https://www.ftc.gov/node/40331?ref=datacatalyst.org) online in 1998\. Unlike the early internet, AI is already transforming industries people depend on, so policymakers need clear rules for real harms while leaving companies room to build and compete. That velvet-gloved approach let a generation of American founders build fast, from Marc Andreessen at Netscape and Steve Case at AOL to Larry Page and Sergey Brin, whose Stanford research on ranking web pages became Google. The early PayPal team, later nicknamed the “[PayPal Mafia](https://medium.com/business-insider/meet-the-paypal-mafia-3b776636ed77?ref=datacatalyst.org),” went on to build Palantir (Peter Thiel), SpaceX and Tesla (Elon Musk), LinkedIn (Reid Hoffman), YouTube (Chad Hurley and his cofounders), Yelp (Jeremy Stoppelman), Affirm (Max Levchin), and Yammer (David Sacks). Many of them also became [major early investors](https://venturebeat.com/business/a-look-at-the-paypal-mafias-continued-impact-on-silicon-valley?ref=datacatalyst.org) in Facebook, Airbnb, Stripe, and other giants of the next generation. By 2022, the [U.S. digital economy](https://apps.bea.gov/scb/infographics/2024/0224-scb-infographic-digital-economy.pdf?ref=datacatalyst.org) accounted for $2.6 trillion, or about 10 percent of GDP in the world’s largest economy. 

By contrast, Europe’s heavy-handed, punitive tech regulations are already costing Europeans, and, even worse, some American lawmakers at the state and federal levels want rules that look more like Europe’s. In 2025, the United States attracted [more than 13 times](https://hai.stanford.edu/assets/files/ai%5Findex%5Freport%5F2026%5Fchapter%5F4%5Feconomy.pdf?ref=datacatalyst.org) as much private AI investment as all of Europe. In June 2026, [Apple held back](https://dataconomy.com/2026/06/09/apple-scraps-siri-ai-launch-in-the-eu-over-intense-regulatory-clashes/?ref=datacatalyst.org) its new AI-powered Siri from iPhone users in the European Union, citing the EU’s digital competition rules. Now, even Brussels has blinked: in May 2026, [EU lawmakers agreed to delay](https://www.hlc.com/en/publications/eu-legislators-agree-to-delay-for-highrisk-ai-rules?ref=datacatalyst.org) the AI Act’s rules for high-risk systems by more than a year, amid pressure to lighten the regulatory burden on technology companies. Despite all of these warning signs, [Colorado](https://leg.colorado.gov/bills/SB26-189?ref=datacatalyst.org) is still creating new compliance requirements for AI systems used in hiring, lending, and other consequential decisions, even after rewriting its AI law this year. And in Congress, Sens. Josh Hawley (R-Mo.) and Richard Blumenthal (D-Conn.) have [proposed](https://www.nextgov.com/artificial-intelligence/2025/09/senators-propose-federal-approval-framework-advanced-ai-systems-going-market/408482?ref=datacatalyst.org) keeping the most advanced AI models off the market until they pass a federal safety review.

The Trump administration has asked Congress for one national AI framework, but the bills that followed have thus far stalled. In March 2026, the White House sent Congress [recommendations](https://www.morganlewis.com/pubs/2026/03/white-house-ai-framework-puts-federal-preemption-at-the-center-of-the-debate?ref=datacatalyst.org) for a framework that relies on existing agencies and would override burdensome state rules. It is the [closest thing](https://www.wlf.org/2026/06/22/wlf-legal-pulse/compromise-necessary-but-not-sufficient-for-ai-preemption/?ref=datacatalyst.org) to a modern version of President Clinton’s 1997 framework.

In the meantime, states are drafting plenty of their own AI rules, creating a complex patchwork that every company operating nationwide must monitor and navigate. [State lawmakers](https://www.multistate.ai/artificial-intelligence-ai-legislation?ref=datacatalyst.org) introduced more than 1,200 AI bills in 2025 alone (an average of 24 per state), on everything from deepfakes to hiring decisions. The Justice Department has [joined](https://www.justice.gov/opa/pr/justice-department-intervenes-xai-lawsuit-challenging-colorados-algorithmic-discrimination?ref=datacatalyst.org) a legal challenge to Colorado’s AI law, and the state has agreed to hold off on enforcement while the case proceeds. A single federal framework would be simpler for business and better for innovation, and R Street’s Adam Thierer has [urged](https://www.rstreet.org/outreach/adam-thierer-testimony-hearing-on-ai-at-a-crossroads-a-nationwide-strategy-or-californication/?ref=datacatalyst.org) Congress to “work the same magic for AI markets” that it worked for the internet in the 1990s.

The imminent November 3 midterms and the 2028 presidential race will decide whether America gets a national AI framework, and the politics cut across party lines. The Trump White House and congressional Republicans have [pushed for one national standard](https://techpolicy.press/trump-and-gop-lawmakers-push-for-new-national-ai-legislation?ref=datacatalyst.org), yet more than 50 Republican state lawmakers have written to the president objecting to federal interference. Democrats are divided too. Rep. Lori Trahan co-wrote a bipartisan House draft that would set a single national standard, while Rep. Valerie Foushee has [opposed](https://www.facebook.com/RepValerieFoushee/posts/in-light-of-recent-reports-surrounding-ai-policy-frameworks-that-preempt-states-/1048132061495619/) any preemption. Which party controls each chamber will help decide whether a national framework passes and whether congressional committees spend the next two years investigating AI companies or championing them. 

In the end, compute and the innovations it makes possible, especially AI, or “[Super Intelligence](https://www.whitehouse.gov/presidential-actions/2026/09/inaugurating-the-era-of-super-intelligence/?ref=datacatalyst.org)” as the U.S. federal government now calls it, will reshape daily life on the scale of electricity and the internet, changing how families shop, how students learn, and what a typical American day at the office, the warehouse, or the hospital looks like. These innovations will also change how banking and finance work, how nations compete and fight, and how people live and work beyond Earth in a growing space economy. The organizations that adapt quickly and strategically will grow, hire, and set the terms for their industries, while those that wait will shrink, disappear, or be absorbed. America has the companies, the capital, and the computing power to lead. What it needs now is business and government leaders who move quickly and strategically.