Strategy Over Speed: How Deloitte is Helping Boards Navigate the AI Maturity Arc

At the LA Times Studios and Monks lounge during CES 2026, Faith Pinnow sat down with China Widener, Vice Chair of Technology, Media, and Telecommunications at Deloitte, to discuss the evolving landscape of Artificial Intelligence. While 2025 was defined by the “silver bullet” hype, Widener argues that 2026 is the year of operationalization – where the “fairy dust” settles and the hard strategic work begins.

Beyond the Silver Bullet

Reflecting on the past year, Widener noted a significant gap between experimentation and execution. According to a Deloitte study, while 38% of organizations experimented with AI in 2025, only 11% successfully translated those experiments into true operational efficiency.

“The reality is that the perception that it would be the panacea... it isn’t necessarily different from the release of any technology,” Widener explained. “There’s an arc and a maturity... It’s the move from ‘it solves all problems easily and magically’ to the true operationalization of AI.”

Strategy: The “Least Sexy” Necessity

For businesses intimidated by the rapid pace of change, Widener suggests taking a step back. She estimates that nearly 80% of organizations are still in the early stages of developing an AI strategy. The real value, she argues, isn’t in fixing a singular problem, but in scalability.

Widener used a vivid construction analogy to explain this: If you give a house framer a power nail driver, they work faster. However, that technology doesn’t answer the underlying strategic questions: Do we even need nails? Should the house be framed with wood?

“AI allows you to say, ‘Do we need nails? Should the house be framed of wood at all?’” Widener noted. “The plan for the technology is actually incredibly important. It’s the thing that CEOs and boards are concerned about: what is that broad plan?”

AI as a “Team Member,” Not a “Star”

Deloitte’s vision for 2026 is moving AI away from being a standalone “star” technology and toward being an integrated collaborative team member. In this model, the AI handles the massive ingestion and synthesis of data, while the human provides the essential element of judgment.

Using a supply chain example, Widener explained that while AI can determine the best components to buy based on millions of data points, a human CFO is still needed to decide when to buy based on quarterly cash flow and risk comfort.

Trust and Transparency

As AI becomes more embedded in everyday work, Widener emphasizes the need for trustworthy AI. This requires transparency in how models are built and, crucially, a diverse set of humans “at the table” to mitigate bias.

“You don’t undo the cake; you take the cake in its whole form,” Widener said, regarding the finality of AI outputs. “Trustworthiness is a function of a couple of things: a level of transparency... and who was at that table.”

The Future is “Quieter”

Looking toward the rest of 2026 and beyond, Widener predicts that AI will lose some of its “flash” but gain immense value. Instead of being tagged onto existing products, it will be invisibly embedded within them, driving long-term growth and meeting organizational visions.

Key Takeaways from Widener

“While 38% of organizations experimented with AI, only 11% were really able to bring something to true operational efficiency.”

“AI allows you to say, ‘Do we need nails? Should the house be framed of wood at all?’ That fundamental change requires a strategic view.”

“AI is going to be quieter in some ways, but much more valuable... We’re losing a little flash, which is actually okay, because we’re getting real operationalization.”