"In the Loop But Not in the Weeds": Organizational Change and the Path to AI ROI
Description
Artificial intelligence will reshape enterprise operations, much like automation did in healthcare records, financial markets, aviation systems, and industrial manufacturing. These historical transitions show that automation rarely delivers immediate productivity gains; instead, organizations pass through phases of experimentation, disruption, stabilization, and eventual transformation. Therefore, AI should be treated not as a productivity tool add-on but as a shift in how decisions are made. Leaders must redesign workflows, governance, and human roles while maintaining human oversight of automated systems. Organizations that integrate AI into decision processes — and build the infrastructure and operating norms to supervise it — will capture far greater long-term value than those that simply layer AI tools onto existing workflows."Organizations looking for immediate ROI from AI are treating it like software. It isn't. AI is closer to autopilot in aviation or algorithmic trading in financial markets: a system that participates in decisions. Those transitions did not pay off simply because the technology was installed. They paid off because institutions rebuilt workflows, governance, and human roles around automation." — Research Director Grace Trinidad, AI Security & Trust, IDC
Table of Contents
9 Pages
Executive snapshot
Key takeaways
Recommended actions
Situation overview
EHR transition in healthcare
Financial institutions and algorithmic trading
Keep pilots "in the loop and out of the weeds"
Industrial robotics and manufacturing
Four phases of organizational technology transition
Phase 1: Experimentation
Phase 2: Disruption
Phase 3: Stabilization
Phase 4: Transformation
Guidance for business leaders
Guidance for technology leaders
Conclusion
Advice for the technology buyer
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