In a recent episode of O'Reilly's Generative AI in the Real World series, Timothy Persons, a leader at PricewaterhouseCoopers (PwC), shared insights on the challenges and best practices for adopting artificial intelligence in large organizations.
Persons emphasized that enterprises often stumble by focusing on technology for its own sake. "It’s important to focus on solving well-defined problems rather than just doing something cool with AI," he said. He stressed that AI adoption is not primarily a technical challenge but a cultural one. "The need to change corporate culture is a major hurdle," Persons noted, citing resistance to change and lack of trust in AI-driven decisions.
A robust data strategy is another critical component. "Good data strategies and data governance are essential," Persons explained. Without clean, accessible data, AI initiatives are likely to fail. He also highlighted the importance of training and education for everyone in the organization—not just technical teams—to build AI literacy and foster broader buy-in.
Persons advised enterprises to start with small, well-scoped pilots that deliver measurable value, then scale gradually. "Focus on solving real business problems, and let success drive further adoption," he concluded.