The truth about agentic AI success
Why most AI initiatives stall. And what it takes to scale real outcomes.
Define success upfront with formal metrics tied to business outcomes—not activity
Prioritize end‑to‑end execution by automating complex, multi‑system processes—not isolated tasks
Orchestrate work across systems to avoid fragmented processes and inconsistent execution
Rethink how work operates to unlock AI value and enable predictable outcomes at scale
Align teams, processes, and ownership to support how work is designed and measured
Agentic AI success depends less on technology and more on how work is designed to run. Most organizations stall at the pilot stage. Not because AI isn’t effective, but because it’s applied to isolated tasks instead of orchestrated, end‑to‑end execution.
The study, conducted with research firm Savanta shows that organizations driving real impact are architecting systems for predictable outcomes, aligning processes, decisions, and teams to scale AI consistently across the business, not just in moments.
If AI is going to run the business, it needs to be designed for predictable, measurable outcomes—not just deployed for experimentation.
This paper helps enterprise leaders move forward:
New research from Pega highlights this shift in action, showing that organizations achieving success are reimagining existing processes to unlock real value from agentic AI. Read the full press release
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