AI drives agentic process outsourcing shift, says tech exec
NEW JERSEY, UNITED STATES — Global enterprises are on the verge of a major operational shift as artificial intelligence (AI) moves from advisory roles to executing work directly, signaling the rise of agentic process outsourcing (APO).
According to a thought leadership article published in Forbes, AI is no longer just a tool to enhance human tasks or generate insights. The next frontier is software that can manage operational cases end-to-end, with humans stepping in only for complex exceptions.
Sanjay Srivastava, who wrote the article, is a chairman at Executive Technology Board, chief digital strategist at Genpact, Venture Partner at Masa Group Ventures and also serves on AI-enabled services company boards and senior advisor to CEOs.
“The biggest near-term shift inside large enterprises will not be ‘better content.’ It will be the conversion of operational work from human-executed to AI-executed, with people supervising the edge cases,” Srivastava noted.
How agentic process outsourcing executes enterprise tasks
Agentic processing allows software to take an exception, request, or document, decide the next steps, and execute across systems. The software can gather missing information, apply policies, route approvals, complete transactions, and escalate cases when risk or uncertainty is high.
Agentic systems provide closed-loop execution capabilities that include planning, cross-system actions, outcome verification, and auditability that differ from conventional automation methods and chatbots.
Orchestration and monitoring tools have matured, enterprises offer broader application programming interface (API) access, and systems can handle more exceptions than previous brittle automations.
“Agentic processing changes the constraint by making exception handling and cross-system work a software problem first, with humans as designed escalation rather than the default throughput engine,” Srivastava said.
APO adoption accelerates AI-driven outsourcing transformation
APO achieved its first win through the successful management of three different types of workflows that include high-volume operations, policy-based processes ,and exception handling procedures.
Some enterprises may develop agentic systems in-house, particularly for processes central to competitive advantage or where regulatory and data sensitivities demand control. Others may buy managed outcomes, focusing internal resources elsewhere.
“The hard part is often not the model — it is running the full production system: instrumentation, exception operations, human takeover, reliability, and continuous improvement,” Srivastava explained.
The evolution of APO also highlights a new supplier landscape: traditional BPOs modernizing their delivery, software-first vendors extending into operations, and clean-sheet APO providers delivering AI-first service with humans in supervisory roles.
The transition to APO will transform how companies handle outsourcing and their relationships with vendors. Operational work requires AI as its main engine, as this choice enables companies to achieve cost reductions, shorter operational cycles, and develop solutions that can handle increased demand.
Success will depend not only on technology but on governance, performance monitoring, and disciplined scaling. APO represents more than automation—it is a fundamental redesign of how work is executed and outsourced in the enterprise sector.
