Corporate AI adoption is moving from simple information-retrieval assistants to agent-driven orchestration capable of taking actions rather than just giving answers.
In a discussion led by MIT CISR researcher Stephanie Woerner at IFS Industrial X Unleashed, panelists emphasized the shift from “assistive AI” to autonomous agents executing workflows within variable, unstructured environments.
Early enterprise deployments show that agents will soon represent users, trigger business processes and coordinate with other agents, which is dramatically altering how ERP work gets done.
Woerner’s upcoming research indicates 90% of business leaders expect at least a 25% revenue uplift from agent-based automation within three years. But that value requires rethinking role definitions, trust models, compliance frameworks, and observability. Leaders must determine how to charge, govern and audit agents, especially when they make decisions traditionally handled by humans.
For ERP and operations executives, this transition represents a structural change in day-to-day work. Business analysts, supply chain planners and service coordinators will spend less time executing processes and more time supervising agent clusters, validating exceptions, and optimizing workflows. The market for agent-orchestration platforms is expanding quickly, fueled by rising multi-model, multi-platform environments requiring consistent governance.
Building AI-Native Operating Models
Accenture’s Amaresh Tripathy noted that most organizations still suffer from broken data flows and fragmented processes. This is a problem that must be resolved before agentic automation can scale. Companies succeeding with digital colleagues follow a consistent pattern:
- Building AI-native operating models that assume agents, not humans, execute baseline processes
- Standing up greenfield AI teams to avoid culture-based resistance from traditional operations groups
- Deploying multi-model governance frameworks, where one model generates actions and another validates compliance
- Establishing central observability layers to monitor agent behavior across ERP, CRM, and supply chain systems.
Case studies show meaningful outcomes. One aerospace manufacturer achieved a 30% reduction in service planning effort after deploying digital colleagues to assemble work packages automatically. A global distributor cut sales-order cycle time by 40% after agents began orchestrating credit checks, inventory confirmations, and pricing approvals across its ERP.
ERP leaders evaluating digital-colleague platforms should prioritize tools that support cross-system orchestration, human-in-the-loop escalation patterns, and transparent audit trails for all agent decisions.
What This Means for ERP Today Insiders
There’s a redefinition of core roles happening. Process owners will transition from task execution to supervising agent workflows and validating edge cases. Automation these processes helps free teams to focus on optimization rather than routine administration.
There’s tremendous pressure to modernize data pipelines. Agentic automation requires clean, broadly accessible data and consistent domain models across ERP modules. This pushes architecture teams to accelerate master-data remediation and integration cleanup.
There’s a great potential for companies to benefit from rapid gains in process throughput. Digital colleagues will shorten cycle times, automate handoffs, and reduce manual coordination. Daily operations will increasingly depend on agent-based orchestration layers embedded directly into ERP environments.
