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77% of AI Decision-Makers Now Use Agentic AI as Chat-Only Approaches Fade

By InnovaAI Research2 min read

Forrester reports that 77% of AI decision-makers are already running agentic AI in production, signaling a clear shift away from simple chat tools. At the same time, guidance from researchers like Ethan Mollick shows that model selection and AI entity visibility are now equally critical decisions for organizations deploying AI at scale.

Key Facts

01Forrester data shows 77% of AI decision-makers are already using agentic AI in production as of mid-2026.
02Ethan Mollick's July 2026 guide reflects a major shift from chat-centric AI use toward task-specific model selection, with o3, Claude 4 Opus, and Gemini 2.5 Pro among the named models.
03An AI entity footprint audit reveals how AI systems describe a client's business, uncovering gaps before they affect visibility.
04Agencies defaulting to a single AI model for all tasks are accepting a measurable performance disadvantage.
05Agentic AI adoption is no longer an emerging trend but a documented majority practice among AI decision-makers.

Why does this matter for agencies?

▶The 77% agentic AI adoption figure from Forrester means clients are increasingly expecting agencies to operate at that level, not just use chat tools.
▶Task-specific model selection, now reflected in practitioner guides updated as recently as July 2026, directly affects output quality and efficiency for agency deliverables.
▶AI entity footprints are shaping how prospective customers find and evaluate brands, making this a client services gap agencies can fill with a structured audit process.
▶Agencies that document a model selection framework now will be better positioned as AI capabilities continue to shift across quarters.

What should agencies do?

Create a written model selection framework that maps specific AI tools to specific task categories such as research, writing, visual ideation, and data analysis, using updated practitioner guides like Mollick's July 2026 edition as a reference.

medium effort

Conduct an AI entity footprint audit for at least one current client by querying ChatGPT, Claude, and Gemini with branded and category prompts, then documenting gaps between AI-generated descriptions and actual positioning.

low effort

Select one repeatable internal process, such as monthly report drafting, and pilot an agentic AI workflow before the end of the current quarter.

high effort