What We’re Reading in January: AI Predictions for 2026
January is peak “AI predictions” season, but the strongest signal across what we’re reading is surprisingly consistent.
2026 is shaping up to be less about bigger models and flashier demos, and more about control and proof. Control shows up as AI sovereignty: where data lives and who governs the infrastructure behind them. Proof shows up as ROI and evaluation: measurable impact in real workflows, not promise-filled pilots.
Here are three reads that keep reinforcing those themes from three different angles: academia, enterprise tech, and healthcare.
1. “The era of AI evangelism is giving way to an era of AI evaluation.”
Read: Stanford AI Experts Predict What Will Happen in 2026
Stanford HAI (the Institute for Human-Centered Artificial Intelligence) points to a clear turning point. Faculty across medicine, law, and computer science argue that AI enthusiasm is giving way to scrutiny. Two priorities emerge for 2026: clearer models for AI sovereignty and stronger frameworks for evaluation.
2. “From AI experimentation and excitement to private and secure deployments with real ROI expectations.”
Read: The trends that will shape AI and tech in 2026
IBM’s predictions frame 2026 as the year AI moves from experimentation into secure deployments with real ROI expectations. Three themes stand out: rising focus on AI sovereignty, the expansion of agentic AI, and growing pressure to prove ROI. As AI systems become more capable and autonomous, enterprises must strengthen governance, security, and control over data and infrastructure, while tying AI investments to clear, measurable operational outcomes.
3. “Healthcare doesn’t need a new hero; it needs better tools for the heroes it already has.”
Read: Healthcare AI 2026 Enters Its Next Act — Prove It Or Lose It
As the title suggests, healthcare AI is entering a “prove-it phase,” where excitement alone no longer carries AI projects forward. What matters now is operational impact. AI use cases are separating into those that truly replace tasks and those that enhance human work, with adoption hinging on how well tools complement clinicians’ work. The article also provided an interesting mindset shift for 2026: healthcare doesn’t need a new “technology” hero, but better tools for the heroes it already has.
Continuing the Conversation
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