A certain anxiety is taking hold in boardrooms around the world. It's not just the fear of losing your job to robots. It's the paralyzing fear of “buyer's remorse” in a fast-moving market. Bill Briggs, chief technology officer at Deloitte, said that as companies move from AI experimentation to impact and value at scale, they are pursuing a lopsided investment strategy, with 93% of their AI budgets going to technology and only 7% going to the people who are expected to use it.
Briggs emphasized that the 93-7 split was a real surprise and a grave mistake. Organizations are fixated on the “ingredients” such as models, chips, and software, and ignore the “recipe” such as the culture, workflow, and training needed to make the technology work. Briggs likened this technology-heavy approach to “trying to eat paella” and “ending up with just cilantro.”
luck I was speaking with Briggs at Deloitte's New York City offices ahead of the holiday shopping crowd at 30 Rockefeller Center to discuss the company's 17th annual Technology Trends Report. Briggs has been involved in this effort for nearly 20 years. At the time, Briggs recalled, he was a senior manager hired directly from Notre Dame as part of a broader effort to bring technology talent to what was then primarily a tax and audit firm. “Technology was the light for what more we would do in the future,” he recalls. The Tech Trends report came about when he was consulting with companies looking to create CTO organizations, but Deloitte didn't have a CTO organization. “So I went back to the CEO and said, 'Whether I play the role or not, we need this.'”
Briggs, who is based near Kansas City but travels frequently to New York and the United States, said he was truly surprised by the 93-7 result. Regarding this ratio, he said, “I felt it while traveling, but I couldn't quantify it.'' He likened this to any technology wave. The easiest way is to apply new technology to the way your company has always done things. “This gradualism is a difficult trap to escape from.”
Briggs did not comment on whether companies are spending too much or too little on AI, but said he sees too much “institutional inertia” winning out today, as companies seek to fit AI into existing workflows as if it were just a bolt-on, rather than rethinking their processes holistically. He recalled the famous words of computer science legend Grace Hopper. “The most harmful phrase is 'We've always done it this way.' He argued that to succeed in this technology revolution, leaders need to push what is easy to do, and that this 93-7 ratio shows that they are relying too much on the same old ways of doing things at a time when something new is needed.
Briggs' comments coincide with a major global study by consulting firm Protiviti, released the same week as his new technology trends report. Fran Maxwell, head of global human resources consulting at Protiviti, put it succinctly in a press conference with journalists: “HR departments and organizations are going to have to redesign their jobs, which is not necessarily a capability that most departments have.” And, unintentionally echoing both Briggs and Hopper, he added, “Yesterday's talent will not solve today's talent problem.”
The result: loss of trust and the rise of “shadow AI”'
To correct the 93-7 imbalance, Briggs proposed a fundamental shift in how companies view AI agents. As organizations move from “carbon-based” to “silicon-based” workforces (meaning the transition from humans to semiconductor chips or robots), they will need to establish HR processes comparable to those for agents, robots, and advanced AI, as well as complex issues around responsibility and performance management. This will be difficult as it involves complex issues around liability and performance management. He proposed the hypothesis that humans create an agent, and that agent creates five more generations of agents. If injustice occurs from the fifth generation, whose fault is it? “What's the disciplinary action? Putting the line robots in time-out and forcing them to do 10 hours of mandatory compliance training?”
The consequences of ignoring the human side of the equation are already being felt in the workforce. According to Deloitte's TrustID report released in Q3, despite increasing access to GenAI in the workplace, overall usage actually fell by 15%. Additionally, the issue of “shadow AI” is emerging. 43% of workers with access to GenAI admit to non-compliance, circumventing employer policies and using unapproved tools. This matches the previous one luck Studies have shown that up to 90% of company employees use AI tools while hiding their usage from IT departments, reporting on the scourge of shadow AI.
Employees say these unauthorized tools are “easier to access” and “better and more accurate” than company-approved solutions. This disconnect has led to a collapse in trust, with corporate employee trust in GenAI decreasing by 38% from May to July 2025. The data supports the need for a human-centered approach. Workers who received hands-on AI training or workshops reported 144% more trust in their employer's AI than those who did not.
fear of 'buyer's remorse'
The reluctance of CEOs and boards to engage in cultural change stems from a deep fear that today's investments will be obsolete by next week. Briggs noted that leaders fear that if they contract with a vendor, they will face “buyer's remorse” when a better model is released days later. “CEOs and boards are scared because they don't want to commit at the wrong time,” he said. It's easy to delay committing to an AI tool because there might be another release next week or the week after.
Briggs likened this mentality to trying to time the stock market perfectly, but argued that this hesitation is “almost like a pre-snap penalty” in sports. He argued that no matter how crowded the market is, the fastest path to progress is to start working on solutions.
The urgency to fix this ratio is further heightened by the rise of “physical AI,” which extends beyond text generation to robotics and drones. Real-world applications have already proven the value of proper integration. For example, at HPE, data-to-decision reporting is 50% faster after deploying Zora AI.
For Briggs, the message to executives is clear. The technology is ready, but unless leaders shift their focus to human and cultural transformation, they risk being left with expensive technology that no one trusts enough to use. As Briggs warned, “No matter how heavy the traffic is, the earlier you leave, the sooner you'll get there.”
