Joerg Storm argues that 2026 will be the year AI shifts from experimentation to structural impact. The next 12–18 months will compress a decade of change into one planning cycle, and companies that still treat AI as a collection of tools—rather than a redesign of workflows, operating models, and economics—will fall behind fast.

Three forces will define AI leadership in 2026:

1. Context and Memory over Models
   Competitive advantage is moving away from “who has the best model” to who can provide the richest, best-governed institutional context. AI systems that remember user preferences, past decisions, and domain knowledge will outperform prompt-based usage. Memory and context become the real performance multiplier.

2. Autonomy and Agents
   AI is evolving from reactive tools to autonomous agents that can plan, act, verify, and execute multi-step work across applications—often without prompts. Early browser and code agents already demonstrate production-ready autonomy, signaling a shift toward AI-driven workflows, not AI-assisted ones.

3. Economic Value and ROI
   Evaluation is moving beyond academic benchmarks to GDP-linked, real-world work—measuring impact on roles, processes, and multi-hour tasks. Boardrooms are no longer asking whether models are state-of-the-art, but where ROI is showing up and which jobs are structurally changing.

Bottom line:
AI strategy in 2026 is not about choosing better tools. It’s about orchestrating context, deploying agents, and capturing measurable economic value. The winners will redesign how work gets done—not just how prompts are written.

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From Prompts to Profit: How Context, Agents, and ROI Will Decide the AI Winners of 2026 #144b

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