Building an agentic AI strategy that pays off - without risking business failure (www.zdnet.com)

Recent insights from KPMG and Accenture highlight the monumental potential of agentic AI, projecting it to unlock $3 trillion in annual productivity gains. Companies must define their AI strategies quickly, as Gartner warns that 40% of agentic AI projects could be canceled by 2027 due to high costs and unclear business value. Despite the allure of significant organizational transformation, risks abound, including the phenomenon known as "agent washing," where many vendors mislabel existing products as agentic. The reliance on external large language models for cognitive processing also leads to escalating operational costs, particularly as companies scale their AI usage. For successful implementation, organizations should adopt a cautious approach. Starting with the identification of low-hanging fruit—internal processes that are repetitive or costly—and gradually integrating agentic solutions can mitigate risks. Establishing strong governance frameworks and monitoring both behavior and costs are crucial steps to prevent potential failures, ensuring that AI systems align with business objectives without overwhelming existing processes. By managing these implementations strategically, businesses can harness the vast potential of agentic AI while minimizing the risk of significant setbacks.