Agentic AI is moving beyond assistance toward autonomous execution, where systems interpret goals, make decisions, and act within defined guardrails. Mid-market enterprises are accelerating adoption, but scale remains uneven.
R Systems surveyed ~200 global mid-market enterprise leaders to understand how organizations are approaching autonomy, governance, and measurable value. The playbook is independently authored by Everest Group, translating these enterprise signals into a structured perspective on adoption and scale.
The findings reveal a clear maturity gap:
- 64% report strong confidence in agentic AI
- Only 15% have scaled to production
- Just 7% have formal governance in place
In fact, 43% are bypassing traditional AI maturity stages and moving directly toward agentic AI models. But confidence alone does not translate into scale. It requires governance, operating model clarity, and measurable accountability.
This playbook explores:
- What enterprise-scale agentic AI looks like in practice
- Why pilots stall, and what separates experimentation from sustained adoption
- How governance, accountability, and control models must evolve
- Where mid-market leaders are focusing to unlock measurable value
Grounded in enterprise data and independent research analysis, this playbook provides practical direction for organizations balancing autonomy with control and ambition with accountability.
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