Bold claim: companies spend a staggering 93% of their AI budgets on technology and just 7% on the people who will use it, and that imbalance is stalling real impact. This is the core tension Deloitte’s CTO, Bill Briggs, highlights as organizations shift from AI experimentation to delivering value at scale. He argues the obsession with models, chips, and software has overshadowed the essential human elements—culture, processes, and training—that turn tech into tangible outcomes.
Deloitte’s 17th Tech Trends report, which Briggs has helped shape for nearly two decades, underscores a familiar pattern. In his early days at the firm, tech was a glimmer rather than a core function; now it’s a strategic driver. The 93-7 split didn’t just surprise him—it revealed a systemic trap: organizations apply new tech to old workflows instead of reimagining how work gets done. He compares this to trying to cook paella but ending up with only cilantro—the foundational ingredients exist, but the recipe is missing.
Briggs notes that this inertia isn’t about underinvesting in AI alone. It’s about resisting “institutional inertia”—the tendency to bolt AI onto existing processes rather than redesign them from the ground up. He recalls Grace Hopper’s warning about the damage of the mindset, “We’ve always done it this way.” To truly succeed in this era, leaders must push beyond comfort zones and embrace a holistic transformation that redefines workflows, roles, and accountability in a silicon-first world.
These calls align with a broader, parallel finding from Protiviti. HR functions, in particular, must redesign roles for the AI era; yesterday’s talent won’t solve today’s problems. The takeaway is clear: you can’t fix today’s talent gaps with yesterday’s solutions. This convergence of tech and people issues sets the stage for what Deloitte calls a potential “Shadow AI” crisis—unauthorized AI usage that erodes trust and governance—and frames the broader question of how to govern, train, and integrate AI agents responsibly.
A key consequence of neglecting the human side is a decline in trust. Deloitte’s TrustID findings show that even as GenAI access rises, overall usage in the workplace has fallen by about 15%. And with many workers bypassing official channels to use unapproved tools, a Shadow AI ecosystem is developing. Workers often find unapproved tools easier, faster, and more accurate, which undermines official solutions and erodes confidence in AI initiatives. Training matters: employees who received hands-on AI education report substantially higher trust in their employer’s AI capabilities.
A central fear among CEOs and boards is buyer’s remorse: the worry that today’s choice will be obsolete tomorrow when a newer model arrives. Briggs compares this hesitancy to fearing the stock market’s next big swing, which leads to delays that impede progress. He argues that the quickest path forward is to act now with a workable solution, even in a crowded market, rather than waiting for perfection.
The urgency intensifies with Physical AI—robotics and drones that operate in the real world. Early successes are already appearing: for example, Hewlett Packard Enterprise (HPE) reported a 50% faster cycle from data to decision after adopting Zora AI. Briggs’ bottom-line message for the C-suite is clear: technology is ready, but unless leaders prioritize human and cultural transformation, expensive AI investments risk remaining underused and distrusted. In his words, “No matter how much traffic there is, the sooner you leave, the sooner you can get there.”
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