According to Deloitte Private’s recently released report, Private Company Outlook: Digital Investment, 52% of private company leaders now rank increasing AI use across the organization among their top three business priorities, more than doubling from 22% a year earlier. Revenue growth (71%) and productivity (62%) remain the leading priorities, underscoring how companies increasingly view AI as a tool to drive both outcomes. Nearly two-thirds (63%) of respondents said their organizations are actively investing in digital transformation initiatives, including AI, while companies with more than $500 million in annual revenue are seeing particularly strong returns. Nearly two-thirds (64%) of those larger companies reported moderate to significant return on investment from AI investments.
For boards, however, the findings suggest a widening gap between overseeing technology and governing organizational transformation.
“Private companies are moving beyond AI experimentation and investing in it to drive growth, improve productivity and make faster decisions,” says Wolfe Tone, vice chair and U.S. Deloitte Private leader, in the report. “Many are starting to see returns, and continuing the momentum will depend on how they integrate AI across leadership, governance and the workforce.”
From Experimentation to Imperative
The rapid increase in AI prioritization reflects both the pace of technological change and growing concern among companies about falling behind competitors.
“I think it certainly speaks to the pace of change and the pace and adoption of AI by organizations of all sizes,” says Tone, cautioning that boards failing to appreciate AI’s impact risk falling behind management teams that increasingly view the technology as central to future growth. “If there are members of the board that don’t appreciate the impact that AI will have on the organization that they are advising, they’re missing the boat.”
The governance challenge extends beyond opportunity to risk management, according to Scott Holcomb, Deloitte’s US Enterprise Trust AI Leader, who advises boards on AI implementation. “Everyone’s in love with the opportunity, right? Who doesn’t want to drive revenue uplift or drive costs out? But you also have to make sure that you have the right governance in place there to manage it responsibly going forward,” says Holcomb. “I think where boards need to be more attuned, and this is a new lesson I’ve learned in the last couple years, is that change is really hard. People don’t like the change, but the risk that AI implementation is introducing is tremendous. Do they have the right governance in place to handle this risk? That’s where I get concerned when I talk to boards and advise them, just kind of opening their eyes to this new world that they’re operating in. And I think one of the areas they really need to pay attention to is the risk element.”
Scaling AI Requires Governance
The report found that boards are most proactive in overseeing technology investment (70%), cybersecurity (67%) and data governance, privacy and regulatory compliance (64%). Yet only 25% of respondents said boards are proactive in overseeing ethical AI use, while just 22% cited oversight of leadership capability to execute AI and digital transformation.
The survey also identified data quality or availability challenges (72%), talent gaps (53%), legacy systems (48%) and difficulty scaling beyond pilot programs (48%) as the leading barriers to realizing AI’s full value.
Holcomb attributes some of that gap to familiarity. “I have three tenets essential to approaching AI: a business process. You’ve got to have your data estate in order. And you’ve got to have governance. There’s the allure of AI agents right now. Some clients are just enamored with automation and agents,” says Holcomb. “But, until you understand your business process and until you have it documented and until, potentially, you redesign it for the AI age, you can’t just sprinkle agents around and all your problems go away. That is not how this works. I think that’s a hard reality a lot of clients are running into, particularly when they’re trying to move from proof of concept or pilot to production. If they don’t have those three elements addressed well, if they don’t have an analytics and AI and data strategy in there, they don’t have the right governance.”
Without those building blocks, organizations often remain stuck in experimentation mode.
AI-related talent and workforce questions are proving more difficult to answer and boards cannot simply leave those questions to management, Holcomb warns.
Tone notes that the report’s findings suggest larger companies may have an advantage precisely because they have already developed those capabilities.
“If you make the presumption that those that are larger are more mature, more sophisticated, have documented processes, then it leads to the conclusion that those are also the ones that are more heavily investing into AI and a bigger return on investment,” says Tone.
The Structural Advantage of Private Companies
The report suggests private companies may enjoy unique advantages in AI adoption due to their ownership structures and decision-making processes. Funding for AI investments is also largely coming from within: 50% of respondents said internal budget reprioritization will be their primary source of funding, compared with 43% relying on existing operating capital. Meanwhile, 93% expect digital investments to improve workforce productivity and operational efficiency.
Tone believes private companies’ agility gives them an edge. “I have always been in the camp that believes the resilience of private companies is a strength, as well as the flexibility and the speed to action.”
Unlike public companies facing quarterly earnings pressure, private companies often evaluate investments over longer time horizons while maintaining the ability to act quickly.
“They can put things in action very quickly,” says Tone. “And so long as everyone is in the boat rowing in the same direction relative to what the AI efforts and activities are, they have a significant advantage.” That advantage, however, depends on governance structures keeping pace with technological change. As private companies move from AI pilots to enterprise-wide implementation, boards may find that their most important role is not overseeing technology itself, but ensuring their organizations are prepared to transform around it.