From AI Experiments to Enterprise Value Driving Real Business ROI - with Dan Diasio of EY

2026-03-24 · Source: The AI in Business Podcast · Field: Business & Management — Corporate Strategy & Leadership, Operations & Process Management, Human Resources & Workforce Development · Depth: Advanced, extended

Summary

EY's AI Pulse Survey, discussed by Dan Diasio, Global AI Consulting Leader and Americas Consulting CTO at EY, reveals a significant shift in enterprise AI adoption. Organizations investing over $10 million are moving beyond mere efficiency gains and headcount reduction, with only 17% of companies using AI gains for layoffs. Instead, these leaders are reinvesting in their workforce, focusing on competitive differentiation and product innovation. The survey highlights that 97% of companies report positive ROI from AI initiatives, but true transformation requires redesigning core business processes rather than just automating existing ones. This pivot involves CEOs driving AI integration into business and operating models, moving from "bolting AI on" to "building it in" to unlock enterprise-level value and address previously impossible problems.

Key takeaway

For CTOs and AI Product Managers driving enterprise AI initiatives, recognize that true transformation extends beyond automating existing tasks. Your strategy should prioritize reinvesting AI-driven efficiency gains into workforce development and redesigning core business processes for competitive differentiation and product innovation. Avoid the "visibility trap" of merely optimizing current processes; instead, challenge your teams to envision entirely new operating models to unlock greater growth and customer connectivity.

Key insights

AI transformation prioritizes workforce reinvention and new operating models over simple automation and headcount reduction.

Principles

• AI adoption shifts from automation to enterprise redesign.
• Reinvest AI gains into people, not just cost cutting.
• Differentiation comes from human ingenuity, not just technology.

Method

Shift from project-based AI to wholesale business transformation by reinventing the entire flow of work, mapping "jobs to be done" to AI agents, and rebuilding an AI-native operating model end-to-end.

In practice

• Focus on competitive differentiation and product innovation.
• Invest in mindset, skill set, and tool set simultaneously.
• Engage junior talent to challenge status quo processes.

Topics

• AI Adoption Strategy
• Enterprise AI Transformation
• Workforce Reinvention
• Competitive Differentiation
• AI Investment

Best for: CTO, VP of Engineering/Data, AI Product Manager, Executive, Director of AI/ML, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by The AI in Business Podcast.