Your AI Strategy Deadline: 6 Lessons from 2026's Year of AI Learning

Your AI Strategy Deadline: 6 Lessons from 2026's Year of AI Learning

The industry's informal grace period on AI strategy is almost up. According to Charlie Bruton, director of innovation at Iris London, companies that don't lock in their AI plans by year-end risk falling behind when 2027 budget decisions begin. After hundreds of hours of experimentation across generative, agentic, and analytical AI, Bruton shares what actually moved the needle.

Key Takeaways

• Never operate alone. A shared vision across agency and client teams is essential — isolated AI experimentation leads nowhere. Agencies and clients need collaborative discovery of solutions that benefit both businesses.
• Don't overpromise. Agencies that claim they "can do everything" with AI undermine trust. Better to collaborate, uncover specific challenges, and design solutions accordingly.
• Make tools accessible to everyone. The broader the distribution of AI tools across an organization, the more value they generate. Bruton draws the comparison to Slack — a project management tool whose emotional stickiness came from universal adoption.
• Fee structures are changing fast. Last summer's AI efficiency credits have already shrunk. AI now requires more budget, not less, as the balance between human and automated work continues to shift.
• GEO strategy is coming next. Beyond current AI adoption, companies need to plan for Generative Engine Optimization — taking back control over how and when content is surfaced by LLMs.

The message is clear: the next six months are more critical than the last. If your AI strategy isn't locked in by Christmas, expect to enter 2027 already behind.

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