The Automation Trap: Companies are racing to deploy agentic AI. Most are doing it wrong.
Article by Mansi Agarwal
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The new generation of AI systems is qualitatively distinct from the chatbots and copilots that preceded them. Rather than responding to prompts, agentic systems can reason through multi- step problems, invoke tools, query databases, execute transactions and run autonomously for hours at a stretch. They are not assistants. They are, in a meaningful sense, workers. And yet firms are deploying them as though they were merely faster typists — layering them onto approval chains, handoff sequences and status-update processes that were designed, implicitly, around the limitations of human cognition. The productivity gains are real but modest. The transformational gains remain largely unclaimed...
This thought-provoking article by Mansi Agarwal explores how processes, operating systems, and mindsets need to change to tap into agentic AI's full potential. Find out where the greatest opportunities are, how to identify if your process isn't agent-ready, and learn about principles to design processes from scratch that unlock agents' real value.
About the author:
Mansi Agarwal currently leads Global Analytics and AI Product Management at Carrier. With over 2 decades of experience in analytics, AI, and product management, she is passionate about delivering data-driven capabilities and experiences that create value and impact for the business. Prior to Carrier, she led data product teams supporting Nike’s business planning, supply chain, merchandizing and commercial organizations. She's held leadership roles in various retail and consulting organizations, including REI, Nordstrom, Target, and Infosys, partnering with executives at C-level.
