During the Fortune Brainstorm Tech dinner at CES in Las Vegas, senior technology executives discussed the complexities of managing change driven by agentic AI, emphasizing the critical role of human oversight in the corporate world. The panel addressed the need for organizations to fundamentally rethink their approaches when integrating AI, rather than simply applying it to existing processes.

Deloitte CTO Bill Briggs cautioned against the trap of using old paradigms to define AI implementation. He noted that while AI has demonstrated value in specific areas, organizations must challenge their desired outcomes and work backwards to achieve them effectively. Briggs emphasized that a complete change in mindset is required to harness the true potential of AI.

Hari Bala, CTO of Health Information Systems, stressed the importance of designing AI systems with the expectation of failure. He suggested that organizations must be realistic about the limitations of AI and build in safeguards to mitigate potential risks. This proactive approach is essential to ensure responsible and effective AI deployment.

The discussions highlighted a growing recognition that AI is not merely a tool but a capability that requires a comprehensive understanding and management. Analogous to a superhero learning to control new powers, organizations need to adapt their strategies and processes to effectively utilize AI. This adaptation involves rethinking traditional workflows and embracing new approaches that leverage AI's unique capabilities.

The integration of agentic AI has broad implications for society, raising questions about workforce transformation, ethical considerations, and the need for ongoing education and training. As AI continues to evolve, organizations must prioritize responsible development and deployment to maximize its benefits while minimizing potential risks. The current status of AI adoption reflects a period of experimentation and learning, with organizations actively exploring different use cases and refining their strategies. The next developments will likely involve increased focus on standardization, governance, and the development of best practices for AI implementation.