Conference Presentation, Keynote
Scale or Stall: The ICONIQ 2026 State of AI | Seth Pierrepont & Vivian Guo | RAISE Summit 2026
- AI product revenue is projected to exceed 50% of total revenue by 2027, accompanied by a gross margin increase from 45% to nearly 60%.
- Pricing models are shifting away from subscriptions and seats toward consumption and outcome-based structures, with nearly half of companies adopting consumption pricing over the last six months.
- Forward Deployed Engineer motions are slated for scaling by 50% of companies within the next two to three years, cementing their role in building durable competitive advantages.
- Investment and market focus are migrating to complex, regulated domains like financial services and healthcare, where embedded AI workflows offer higher stickiness.
- 66% of companies plan to release agentic AI capabilities within the next 12 months, though reliability, orchestration infrastructure, and domain depth remain critical production requirements.
- Agent-driven productivity gains are expected to yield a uniform 20% to 27% impact across company sizes, with revenue per FTE anticipated to nearly double over the next year.
- Agentic workflows are predicted to remain heavily human-involved through 2026 due to workflow breakdowns and insufficient context for long, complex tasks.
- Cost predictability for agentic workflows remains challenging for 68% of respondents, driven by token spend, inference costs, hidden integration expenses, and upskilling needs.
- Total AI spend is expected to rise from 11% to 19% of revenue, with high-growth companies ramping new tools in two and a half months compared to three and a half months for others.
- Organizational structures are forecasted to become faster and flatter, with wider spans of control and fewer hierarchical layers between CEOs and individual contributors.
- Non-engineers are expected to begin shipping production-ready features, driving PR throughput increases of 25% to 40% and compressing concept-to-prototype timelines to under two days.
- Functional transformations include AI-enabled sales coaching loops, customer success expansion via AI deflection, and RevOps teams being rebuilt from the ground up.
- Finance functions are projected to reduce close cycles from weeks to under a day, while companies plan to redesign work entirely rather than merely accelerating existing tasks.
- Human labor will be retained only where AI lacks capability, and the strategic divergence between scaling and stalling is expected to resolve in the coming quarters.