Gucker also emphasizes the need for responsible AI practices and the importance of having the right operating paradigm. He suggests developing an internal center of AI excellence, prioritizing use cases based on their impact and ROI, and evaluating the risks and rewards of building versus buying AI. He concludes by stating that a comprehensive AI strategy aligned with business goals can lead to AI maturity and sustained success.
Key takeaways:
- AI-mature organizations outperform their industry peers and have greater expectations for growth across critical business outcomes. They are expected to use AI across all business functions in the next two years.
- Five key areas for AI investment include internal operations, business functions and employee enablement, discerning approaches to AI investments, delivering more AI inference at the edge, and a tailored approach to AI at the edge.
- Responsible AI practices will receive greater scrutiny in 2025, with regulatory scrutiny worldwide pushing enterprises to implement full-scale governance and responsible AI.
- Successful AI transformations often involve developing an internal center of AI excellence, prioritizing use cases based on their impact and ROI, and evaluating the risks and rewards of building versus buying your AI.