The future of customer experience: Embracing agentic AI

A McKinsey Talks Operations podcast discusses the shift from generative AI to agentic AI, where AI agents make decisions and take actions on behalf of humans, transforming customer experience and internal operations. Experts emphasize the need for companies to move beyond experimentation and focus on ROI, redesigning workflows to integrate AI at the core, and fostering collaboration between CIOs and COOs. While many companies are still in the pilot phase with AI implementations like chatbots, those achieving scale are seeing improvements in metrics such as reduced average handle time and improved first contact resolution, highlighting the importance of addressing security, data fragmentation, and undocumented agent knowledge to fully realize the potential of agentic AI.

Analysis

The discussion highlights a significant evolution in artificial intelligence application within enterprises, moving from generative AI's content creation capabilities to agentic AI systems capable of autonomous decision-making and action on behalf of humans. Companies are reportedly shifting focus from experimentation to demanding demonstrable Return on Investment (ROI) and substantial business impact from AI initiatives, necessitating a fundamental redesign of operational workflows rather than simple task automation. While a recent survey cited indicates 95% of firms remain in pilot stages for common AI applications like chatbots, notable progress is observed in AI-driven copilot solutions and agent coaching, where 30% to 45% of these use cases are reportedly operating at scale. Successful scaled implementations are yielding tangible benefits, including reduced average customer interaction handle times and improved first contact resolution rates. The article emphasizes that critical prerequisites for broader adoption of agentic AI include robust collaboration between Chief Information Officers (CIOs) and Chief Operating Officers (COOs), characterized by shared accountability and integrated strategies, to overcome implementation complexities. A future vision is presented where personalized AI agents manage customer interactions comprehensively across multiple touchpoints, suggesting a paradigm shift in customer experience; however, achieving this requires surmounting significant hurdles including security and regulatory compliance, pervasive data fragmentation across numerous enterprise systems (often 7 to 10 per agent), and the challenge of codifying undocumented operational knowledge, which reportedly constitutes at least 25% of daily tasks for 70% of contact center agents.

Key Decisions for Investors

• Investors should assess companies within their portfolio, particularly those in service-heavy industries, for their strategic approach towards adopting agentic AI, looking beyond pilot programs to evidence of scaled deployment and quantifiable ROI generation.
• Given the critical role of integrated operations and technology outlined, prioritize scrutiny of management teams based on their demonstrated ability to foster strong CIO-COO collaboration and articulate a clear vision for embedding AI into core business processes, rather than treating it as a siloed IT project.
• Monitor companies' investments and progress in addressing key AI adoption hurdles identified—such as data infrastructure modernization, establishing robust security and compliance protocols for AI agents, and developing strategies to capture and leverage undocumented institutional knowledge—as these will be crucial differentiators for realizing agentic AI's productivity gains.
• Consider the long-term transformative potential of agentic AI on customer experience and operational efficiency, recognizing that early adopters who successfully navigate the complex implementation challenges and effectively manage the associated organizational change will likely gain significant competitive advantages.