10 AI Predictions for 2026: Agents, Jobs, Token Efficiency

10 Predictions That Could Reshape How Organizations Use AI

Phillip, an AI executive, joins tech journalist David on the one-year anniversary of Mindset Podcast to lay out ten bold predictions for 2026. From OpenAI losing its crown to AI agents becoming packaged services you can buy by results, these forecasts paint a picture of seismic shifts in the enterprise AI landscape.

On OpenAI being dethroned: "There are two tendencies which can cause this to happen... Gemini 3.5 Pro release has been super strong and the response from OpenAI, GPT 5.2, was not that strong. I checked the traffic development and there's a very clear dip after the Gemini release." Phillip sees either Google overtaking in user count or Anthropic surpassing OpenAI in API revenue.

On AI-driven unemployment: "I literally have seen companies who have new versions of their org charts where some of the positions are not humans anymore. A manager who has several humans reporting to him and several automatic agents reporting to him as well." The hybrid org chart is already here—and the 1:4 ratio in startup hiring (20 people down to 4-5 for the same stage) signals what's coming for larger enterprises.

On the test-first development revolution: "Given the progress of self-coding models, it's clear that computers can already write code at par with human programmers. The biggest value of humans will be to write tests strong enough to validate if the software designed by autonomous coding engines is good enough." Software teams are shifting from "development-first" to "testing-first"—engineers will spend more time writing test cases than blueprints or code.

On Agent-as-a-Service: "2026 will be the year where you can buy a service of AI agents priced on the result—not 'you have five attempts' but 'here's an agent that solves customer support issues and I'm going to charge you for every successfully resolved case.'" The prediction that matters most for enterprise: AI agents packaged as services with outcome-based pricing, rivaling both SaaS and traditional hiring models.

On token efficiency becoming critical: "The models coming out of Asia seem to be so much more token efficient. DeepSeek was doing at par with contemporary models with a significantly lower token footprint... if you are model-agnostic, then price will be something you're going to look after." With best-in-class models changing every few weeks, token cost becomes the deciding factor.

10 Predictions for AI in 2026

• OpenAI dethroned - Either Google overtakes in users or Anthropic surpasses in API revenue; GPT 5.2's weak response to Gemini 3.5 Pro signals vulnerability
• Major AI IPOs - At least three big AI companies go public in Western markets, giving retail investors their first chance at the AI boom
• Autonomous taxis hit Europe - Five European cities will have robo-taxis you can try; regulatory approach varies but technology is ready
• AI-driven unemployment spike - One major economy sees job displacement attributed to AI; org charts already show agent positions
• Full AI-generated cinema film - Either a Chinese AI lab or a frontier lab produces a complete movie for public release
• Meta scales down open source - With Yann LeCun departing, Llama's future uncertain; a Chinese model may briefly top benchmarks
• Test-first development dominates - Engineers shift from writing code to writing tests; QA becomes the highest-value human skill
• Two new AI device form factors - Beyond glasses and pendants, entirely new device categories emerge
• Token efficiency year - API users become cost-conscious; model-agnostic design makes price the deciding factor
• Agent-as-a-Service arrives - AI agents sold by outcomes, not attempts; hybrid human-agent teams become standard

What This Means for Enterprise AI Strategy

These predictions converge on a fundamental shift: AI moves from tool to teammate. The hybrid org chart—where managers oversee both humans and agents—isn't science fiction; it's already appearing in forward-thinking companies. The startup hiring ratio (4-5 people doing what 20 did before) will force incumbents to follow or fall behind. And the Agent-as-a-Service model changes the buy-vs-build calculus entirely: why hire when you can subscribe to an agent priced on resolved tickets? For organizations planning their 2026 AI strategy, the question isn't whether to adopt agents—it's whether to build them, buy them, or both.