What: New McKinsey playbook reveals how AI agents can transform business processes and unlock scalable value through autonomous, goal-driven execution.

Why it is important: The research highlights a critical shift in AI implementation, where success depends not on adding AI to existing processes but on fundamentally reimagining operations with AI agents at their core.

McKinsey's latest report addresses the "gen AI paradox" where despite 78% of companies using generative AI, over 80% report no material earnings impact. The study identifies how AI agents can break this pattern by enabling autonomous, goal-driven execution of complex business processes. Unlike traditional AI tools, agents can understand objectives, break them into subtasks, and adapt in real time with minimal human intervention. The report emphasises that success requires more than simply inserting agents into existing workflows – it demands complete process reinvention. Organisations must shift from scattered tactical initiatives to strategic programs, focusing on end-to-end business process transformation rather than isolated use cases. The research also outlines the need for a new "agentic AI mesh" architecture to manage risks, blend custom and off-the-shelf solutions, and maintain agility amid rapid technological evolution.

IADS Notes: Recent retail industry developments validate McKinsey's findings. In February 2025, research showed that 38% of global consumers were already using AI tools for shopping, with 80% reporting positive experiences. The impact on operations has been significant, with retailers achieving 15-30% improvements in customer service efficiency. However, only 10% of retailers have successfully scaled their AI applications, supporting McKinsey's emphasis on the need for comprehensive transformation rather than piecemeal implementation. The most successful cases, such as Intime Department Store's 15% boost in counter sales through AI integration, demonstrate how reimagining processes around AI can deliver substantial business value.

Seizing the agentic AI advantage