If 2025 felt like living inside a rehearsal for a technological revolution, 2026 looks set to be opening night — complete with a spectacular set, a few missed cues and an audience that’s no longer sure whether to clap or riot.
Powering the boom: datacenters, energy and geopolitics
The physical backbone of the AI surge is becoming painfully visible. Big tech’s datacenter bets — Microsoft’s reported $17.5bn pledge in India, Amazon’s $35bn commitment and Google’s $15bn tie‑ups — are the sort of capital moves that change maps and local power dynamics. Across Southeast Asia and Latin America, new facilities are arriving faster than grids and regulators can cope. Brazil’s boom, for example, has already pushed fragile electricity systems to the limits; communities and activists are asking hard questions about water, coal and secrecy.
There are also outliers that should make planners nervous. China’s rapid build-out created a fleet of facilities that, by some accounts, now struggle to find demand — reports suggest a big share of capacity sits unused. That mismatch is a reminder: more servers don’t automatically produce more AI value. Meanwhile, novel ideas such as putting datacenters in orbit are being floated by companies like Google — a high‑ambition answer to the energy, latency and geography constraints that will only complicate an already thorny picture. See Google’s Project Suncatcher for one example of how infrastructure plans are getting creative.
Energy math matters. Global datacenter consumption was already in the hundreds of terawatt‑hours in 2024 and could more than double by 2030. The paradox is brutal: advanced AI needs immense power even as much of the planet races to decarbonize. That tension will shape investment choices, regulation and community pushback in 2026.
Agents, developer tools and the enterprise squeeze
On the software side, 2026 is likely to be dominated by agentic systems — LLMs that call tools, orchestrate workflows and, increasingly, transact. Developers are wrestling with the plumbing: Model Context Protocol (MCP) servers, parallel task execution, CLI versus desktop experiences and the thorny economics of agents that might call paid services on the fly.
Practical problems are under the gloss of demos. Teams need dashboards and governance for dozens of MCP endpoints; senior engineers will be the ones comfortable letting background agents touch code; and the fragmentation of developer tooling — forks of IDEs, differing extension ecosystems — is creating operational and security headaches. Those are not academic concerns: how enterprises standardize on agent patterns will decide who loses and who scales.
The vendor story is straightforward and consequential. After a long period of pilot projects, many VCs and enterprise buyers expect consolidation: companies will funnel bigger AI budgets to a narrower set of vendors that demonstrably deliver results, while experimentation budgets shrink. That implies fewer winners, tougher economics for thousands of startups and a buying pattern that favors integrated stacks and strong governance. An early sign of agents moving into consumer or enterprise life is the expansion of agentic booking and tasking — Google's recent moves around agentic booking are a concrete example — and integrations that drag models into core apps, like deeper search across Gmail and Drive. For context read about Google AI Mode's agentic booking and Gemini Deep Research bridging into Gmail and Drive.
People, politics and the premium on human judgment
Here’s where the rhetoric meets reality: AI is both creating roles and hollowing out pathways. Global analyses suggest millions of new roles could appear even as tens of millions of tasks are automated. But the distribution matters. Entry‑level jobs and on‑the‑job learning pathways are being reshaped by automation and agents that absorb coordination work — which risks creating a cohort of workers who can’t gain experience in traditional ways.
This is where the human paradox intensifies. Studies show many AI pilots fail to yield immediate ROI and organizations often face a productivity J‑curve: short‑term disruption before longer‑term gain. And there’s a cultural cost: as low‑quality, AI‑generated content proliferates — the so-called "AI slop" — authentic, well‑audited human work could command a premium. Some companies are already doubling down on human oversight and quality control as a differentiator.
Expect politics to creep in. Venture capitalists and some analysts predict white‑collar pushback over job security — a possible first wave of anti‑AI protests among professional cohorts who perceive their livelihoods threatened. That’s an ugly but plausible scenario in 2026 if layoffs and automation announcements accelerate without visible reskilling programs.
Robots, roads and rich people
The hardware story is changing too. Autonomous vehicles will push past the novelty phase: several firms are expanding robotaxi deployments into new global cities, and more visible self‑driving fleets will change urban life in subtle and not‑so‑subtle ways. Robotics more broadly is expected by some investors to have a GPT‑3 style inflection — a moment when capability jumps and new commercial pathways open.
Meanwhile, the money side of AI remains concentrated. High valuations and the prospect of large IPOs — including speculative figures attached to companies in the AI supply chain — mean the wealth effect will keep percolating upward even as social strains mount.
Why 2026 will feel different
In short: the pieces that were separate in 2025 are converging. Capital is building a global, energy‑hungry infrastructure; agentic software is pushing into both developer workflows and consumer apps; enterprises are getting picky about who earns their budgets; and social friction is likely to rise as real job pathways shift.
None of this is preordained. Regulation, smarter energy choices, rigorous product evaluation and deliberate upskilling can turn many of the tensions into opportunities. But if 2026 becomes a year of rushed rollouts and uneven governance, the backlash could be as consequential as the breakthroughs.
If you want to keep watching how the technical scaffolding meets policy and people, follow the datacenter and agent stories closely — they’ll be where the future is assembled, one contract and one angry town hall at a time.