McKinsey’s year-long review of over 50 AI agents highlights significant insights for businesses. Although marketed as digital co-workers, these agents require extensive onboarding and may not suit every task. The report, authored by Lareina Yee, Michael Chui, and Roger Roberts, reveals six key lessons for optimizing agentic AI. Firstly, agents perform best when integrated into reimagined workflows rather than implemented arbitrarily. Secondly, not all problems warrant AI; simpler solutions may suffice for repetitive tasks. Thirdly, AI outputs often disappoint, leading to trust issues—hence, agents need structured onboarding and consistent feedback. Additionally, tracking many agents becomes complex, emphasizing the importance of monitoring and evaluation tools. Sharing agents across functions can reduce redundancy, while fostering collaboration between human workers and AI is crucial for maximizing effectiveness. Ultimately, ensuring human oversight is essential to prevent errors, suggesting next year’s performance reviews might reflect ongoing challenges.
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