I've made public predictions about B2B go-to-market for four years, grading myself each time. This year was the hardest, since AI is moving so fast and everything feels uncertain. As Nicolas de Kouchkovsky says, "2026 won't be predicted as much as navigated."
But committing to specific predictions helps me navigate the year, even if I don't get them exactly right.
One thing I am confident about: enterprise adoption will remain incremental, and the gap between what's possible and reality will be large.
Here are my predictions; I hope they help you navigate your year.
PS: The full 6,676 word article is hosted on the Chiefmartec blog: Jon Miller’s Predictions for B2B Go-To-Market in 2026.
1️⃣ Marketing to agents, not just humans — AI agents will increasingly act as research partners in buying committees. Teams will start tracking agent activity and designing content and data structures for machine consumption.
2️⃣ AI transforms martech, but not in 2026 — Autonomous agents and new tools are real, but enterprises move cautiously. In 2026, most martech still looks like familiar SaaS with AI layered in.
3️⃣ Composable stacks grow slowly — Composable architectures are the long-term direction, but they shift complexity rather than remove it. Fewer than 20% of teams will be ready in 2026.
4️⃣ Context engineering becomes a thing — The real value of AI comes from operational context that lives in people’s heads and Slack threads. Formalizing that knowledge for AI becomes a new discipline.
5️⃣ Reasoning AI replaces brittle rules — Rules-based automation can’t handle ambiguity. Reasoning models start taking over the messy middle between simple automation and human judgment.
6️⃣ Journey orchestration moves to AI playlists — Personalization isn’t infinite content; it’s the right action at the right time. AI assembles unique journeys from a finite set of assets.
7️⃣ AI inbox gatekeepers make email earned — With hundreds of billions of emails sent daily, buyers rely on AI filters. Email attention shifts from volume to relevance and trust.
8️⃣ Taste, trust, and accountability matter more — As AI floods the market with mediocre content, buyers gravitate toward trusted voices, clear points of view, and people who stand behind their ideas.
9️⃣ Public intent data commoditizes — When everyone has access to the same signals, they stop being differentiators. Advantage comes from proprietary data, combinations, and timing.
🔟 Signal-based orchestration defines the next stack — Martech evolves toward three layers: signals, AI decisioning, and execution APIs. The transition will be messy but directional.
1️⃣1️⃣: Uncertainty intensifies — Economic and AI-driven uncertainty remains elevated. Entry-level roles are already being disrupted, and this pressure won’t stay contained. Preparation beats prediction.
