Last week in AI: Davos Power Struggle, Policing by Algorithm, Worker Trust Erodes.
Last week’s AI story was less about breakthroughs and more about consequences. Power struggles at Davos, creeping use of AI in policing and politics, uneven workplace impact, and rising anxiety all point to the same truth: AI is scaling faster than trust, governance, and institutions are ready to handle.
Davos Turns into an AI Power Struggle
Davos has become less a forum for global cooperation and more a stage for AI one-upmanship. TechCrunch reports that this year’s World Economic Forum was dominated by tech CEOs boasting, bickering, and warning about AI, as leaders sparred over regulation, speed, and responsibility. A companion TechCrunch podcast notes that AI executives effectively transformed Davos into a tech conference, sidelining traditional political voices. The tension was on full display when Google DeepMind CEO Demis Hassabis publicly questioned OpenAI’s priorities, telling TechCrunch he was surprised the company was rushing to add ads to ChatGPT.
AI Power Meets Policing, Politics, and Democracy
As AI scales, its influence is extending into the most sensitive parts of society. Axios reports that police departments are increasingly using AI-generated evidence to reopen cold cases, raising questions about reliability, bias, and due process. At the same time, Inc. warns that experts fear AI swarms could disrupt democratic systems through coordinated misinformation and automated influence campaigns. Underpinning it all is infrastructure. Futurism reports on how data center expansion has become entangled with politics and power, turning AI compute into a geopolitical asset. Together, the stories show AI’s evolution from tool to force—reshaping law enforcement, elections, and state power faster than governance structures can adapt.
AI at Work: Efficiency Claims Collide with Employee Reality
Executives may be celebrating AI-driven efficiency, but workers tell a more complicated story. The Wall Street Journal reports that while many CEOs say AI is streamlining operations, employees often see little day-to-day benefit and describe added friction instead. Data backs up the disconnect: a Gallup poll cited by the Canadian Press finds most Americans use AI sparingly at work, often for small productivity boosts rather than transformation. Meanwhile, TechCrunch reports that new benchmarks suggest AI agents still struggle in real workplace tasks. Even Futurism notes that workers often rely on AI less to replace labor than to work around bad management. The result: modest gains, inflated promises.
AI’s Growing Mental and Labor Toll
Beyond productivity debates, AI is reshaping how workers feel about their jobs. CNBC reports that concerns over automation and relevance are driving more people to seek therapy, as uncertainty becomes a constant feature of work life. Futurism similarly documents rising business and labor anxiety around AI adoption, particularly where expectations outpace training. The economic stakes are just as unsettled. TIME outlines how AI’s impact on jobs remains uneven and unresolved, with productivity gains failing to translate cleanly into security. At Davos, Reuters reports that EY’s Sue Daley Teigland urged firms to invest in people, not just AI tools. The message is clear: without trust and support, efficiency won’t stick.
The Agent Era Arrives — but the Math, Media, and Reality Lag Behind
AI agents are being pitched as the next leap beyond chatbots, but cracks are already showing. WIRED reports that the economics of AI agents don’t yet add up, with high compute costs and limited autonomy undermining claims that agents will cheaply replace human labor at scale. Still, startups are racing ahead. Fortune profiles how Cursor built a web browser powered by swarms of AI agents, showcasing the ambition to offload complex workflows to coordinated systems rather than single models. Meanwhile, Fast Company warns that newsrooms aren’t ready for the agent era, as editorial workflows and accountability structures lag behind the technology. Together, the stories capture a familiar pattern: rapid experimentation racing ahead of sustainable economics, institutional readiness, and clear proof that agents can reliably deliver on their promise.
OpenAI Scales Up: From Enterprise Agents to Hardware and Health
OpenAI is accelerating its push to become foundational infrastructure across industries. Reuters reports that the company has rolled out age-prediction tools inside ChatGPT to better tailor safety and content controls. In enterprise software, The Wall Street Journal notes that OpenAI has struck a deal with ServiceNow to embed AI agents directly into workplace workflows. Hardware ambitions are also coming into focus. 9to5Mac reports that OpenAI has teased a hardware unveiling as Jony Ive–linked recruits from Apple continue to join the company. Meanwhile, Reuters says OpenAI and the Gates Foundation are partnering on AI-driven healthcare tools in Africa, underscoring its global ambitions beyond chat.
Trust, Money, and Oversight: The Risks Catching Up to OpenAI
As OpenAI scales, scrutiny is rising just as fast. The Information reports that the company is lining up advertisers ahead of its long-anticipated ads launch, sharpening questions about incentives, data use, and trust inside ChatGPT. At the same time, Futurism highlights criticism from an asset manager who warns that OpenAI’s financial structure could be a liability, calling its hybrid nonprofit-for-profit model unstable at scale. Even safety features are drawing attention. Reuters’ reporting on age prediction has sparked debate about surveillance, misclassification, and regulatory exposure, particularly as OpenAI expands globally. Together, the stories point to a company entering a more difficult phase—where growth, monetization, and governance collide, and where reputational risk may matter as much as technical capability.
Google Positions Gemini as Personal Intelligence and Questions OpenAI’s Ad Push
Google is sharpening its vision for AI as a deeply personalized assistant, even as it throws subtle shade at competitors’ business models. TechCrunch reports that Google DeepMind CEO Demis Hassabis expressed surprise that OpenAI is rushing to introduce ads in ChatGPT, signaling concern that monetization could undermine user trust and product quality. At the same time, Google is leaning hard into personalization. The Verge details how Gemini is evolving into a “personal intelligence” layer designed to understand users’ goals, habits, and context across Google services. The contrast highlights Google’s strategy: frame AI not as an ad surface, but as ambient infrastructure—while quietly defending its long-standing dominance in both data and advertising.
Anthropic Reframes the AI Race Around Collaboration, Not Chat
Anthropic is repositioning Claude away from solo prompting and toward shared work. New York Magazine argues that Claude Code and CoWork reset the AI assistant race by treating AI less as a conversational partner and more as collaborative infrastructure embedded in real workflows. Instead of flashy demos, the focus is persistence, context, and team use. That shift is gaining traction with developers. The Wall Street Journal reports that Claude Code is emerging as a serious rival to tools like GitHub Copilot, particularly for engineers working across large, complex codebases. VentureBeat adds that CoWork turns Claude into shared AI infrastructure, enabling multiple users to collaborate inside the same AI context.
Apple Rethinks the Interface for AI as Siri Faces an Existential Test
Apple is quietly reworking how users may interact with AI across devices. The Information reports that the company is developing an AI-powered wearable pin, an experimental form factor that could offload contextual AI tasks from phones and hint at a post-screen future shaped by ambient computing. At the same time, Apple is racing to shore up Siri. Bloomberg reports that iOS 27 will revamp Siri into a built-in chatbot across iPhone and Mac, as Apple seeks to counter pressure from OpenAI and other generative AI rivals. Together, the moves suggest Apple sees interface—not raw model performance—as its best leverage point in the AI race.
Meta Slows Consumer AI — While Positioning Itself as Infrastructure
Meta is hitting the brakes on one of its most visible AI experiments even as it leans harder into long-term platform strategy. TechCrunch reports that the company has paused teen access to AI characters ahead of a revamped release, citing safety concerns around youth interaction, emotional attachment, and content boundaries. At the same time, Meta is reframing how it wants to be seen in the AI race. Yahoo Finance explains why the company is positioning itself as an AI infrastructure player, investing heavily in open models, data centers, and compute rather than consumer-facing polish. Together, the moves suggest Meta is prioritizing scale and backbone control over short-term engagement—accepting slower consumer rollouts in exchange for long-term leverage across the AI ecosystem.
Creativity vs. Slop: AI’s Battle for Cultural Value
As generative AI floods the market, creators and brands are drawing sharper lines around value. Billboard reports that artists including Cyndi Lauper and Questlove are backing a campaign for licensing frameworks that ensure creators get paid when their work is used to train AI. The push comes amid growing backlash against low-quality automation. That backlash is detailed in The Verge’s report on AI-generated advertising “slop”, which argues that mass-produced creative is cheapening brand storytelling. Meanwhile, Quartz points to industry data showing AI video tools are rapidly improving—but adoption remains uneven as quality concerns persist.
AI Slips into the Workflow—and the Background
Some of AI’s biggest changes are arriving quietly, embedded inside everyday tools. TechCrunch reports that Adobe Acrobat now lets users edit documents and generate podcast summaries using prompts, signaling how generative AI is becoming standard office infrastructure rather than a novelty feature. A similar shift is underway in enterprise voice technology. VentureBeat explains that recent breakthroughs in voice AI are enabling more natural, scalable systems for customer service, analytics, and internal workflows. Instead of flashy assistants, the focus is reliability and integration.