The agentic-AI market forecast is growing faster than process redesign
Spending expectations are accelerating, but many organizations are still trying to automate planning without redesigning decision rights, data ownership or workflows.
The market narrative around agentic AI is expanding faster than the redesign of the planning processes those agents are expected to operate.
Observation
Recent industry commentary contrasts aggressive growth expectations for agentic Supply Chain software with slower progress on end-to-end process redesign.
Operational implication
Organizations risk automating the current operating model, including fragmented data, duplicate planning logic and unclear escalation paths.
Decision architecture
Before deploying agents, leaders should define the exact decision, authoritative data, owner, constraints, approval thresholds, audit history and failure mode.
Data requirements
Agents need governed master data, active planning versions, current parameters and traceable outcomes.
Governance implication
Agent deployment should be tied to process redesign milestones, not treated as a standalone technology program.
What should remain lightweight
Controlled experiments and narrow decision assistants can remain outside the core architecture while evidence is gathered.
What should be integrated
Mature workflows should be integrated into APS, ERP or BI only when decision rights and controls are explicit.
Buying agents without redesigning the decision process automates ambiguity.
Source discussion: Vast Insight Partners on LinkedIn.