26 leaders say organizations are moving AI from investment to operational use

An Impact Council survey of 26 leaders, published May 8, 2026, found a rapid shift from generic AI experiments to tailored, process — level deployments; boards and customers now expect measurable impact; governance is reframed as “speed — with‑control”;

Twenty — six senior leaders, including Neil Barrie and Celia Jones, told an Impact Council query published May 8, 2026, that attitudes toward artificial intelligence have shifted decisively: organizations are moving beyond headline investments and experiments toward embedding AI into operations, and that change matters because boards, customers and employees now demand clear, measurable impact.

Several contributors described a move away from one-size-fits-all AI outputs toward tailored applications. Neil Barrie said the field is split between passive, generic content creation and a smaller cohort treating large language models as extensions of individuals — building custom GPTs, “vibe coding” web apps and training models to write in a founder or employee voice. Celia Jones noted the same pattern: capital is less often the story; instead teams are embedding AI into specific processes and workflows.

Market and institutional pressures are changing expectations. Steve Holdridge said AI has become expected rather than experimental, with boards and customers increasingly asking, “where’s the impact?” Darren Person warned that in education the workforce disruption is accelerating experimentation while raising the bar for measurable learning outcomes. Those pressures are forcing organizations to demonstrate tangible benefits instead of settling for exploratory pilots.

Governance, contributors said, is being reframed as speed — but with control. Blake Brannon reported leaders shifting from attempts to slow AI to figuring out how to move faster without losing oversight; he warned that failing to align governance with AI’s pace carries both operational and existential risks. Builders now face a concrete trade — off: deploy quickly enough to avoid falling behind competitors, while implementing guardrails that prevent compliance and trust breaches.

Adoption inside organizations remains uneven. Jones observed a dichotomy among younger staff — some fully embrace AI while others resist on ethical and environmental grounds — which is shaping who adopts and how quickly. Usage today is concentrated on individual and team productivity, but that expansion is also exposing major faults and blind spots that contribute to hesitation among some stakeholders.

The council’s responses point to practical implications for product teams and technical leads: prioritize role-based, functional integrations over generic capabilities; invest in customization that preserves organizational voice; and pair faster rollouts with governance that can scale. The variety of examples — from curated LLM personas to purpose — built web apps-illustrates both immediate opportunities and the operational risks builders must navigate.