Private companies are gradually moving past the early stages of experimenting with artificial intelligence, with many larger firms now beginning to report measurable returns from their investments.
Summary
- 64% of private firms with $500M+ revenue report moderate to strong AI ROI, compared with 11% of smaller firms.
- 52% of leaders rank expanding AI use as a top priority, while 63% are actively investing beyond pilot stages.
- Data quality (72%), talent gaps (53%), and scaling challenges (48%) remain key barriers despite rising adoption.
According to a new survey by Deloitte, nearly two-thirds (64%) of private companies with an annual revenue of $500 million or more have achieved moderate to significant return on investment (ROI) from AI initiatives. This marks a sharp contrast from smaller firms, where only 11% reported such levels of returns.
The findings also bring to light a broader shift in how private companies are now approaching AI. More than half (52%) of the business leaders surveyed said that expanding AI use across their organizations is now a top-three priority for the next 12 months, a figure that has gone up significantly from 22% a year earlier.
At the same time, 63% of respondents said their organizations are actively investing in digital transformation initiatives, including AI, compared with 33% that remain in limited or pilot stages.
Scaling efforts and key challenges
Larger firms have been leading the charge in deployment. About 74% of higher revenue companies reportedly said they are expanding AI across select functions, compared with 38% of smaller firms.
The main business priorities driving this push are revenue growth at 71% and improved productivity at 62% as companies look to automate complex workflows.
Funding for these initiatives is largely coming from internal sources. Half of those surveyed said budget reprioritization will be their primary funding method, followed by existing operating capital at 43%.
Despite the progress, significant roadblocks still hinder full-scale implementation. Data quality and availability were cited as the biggest challenges by 72% of respondents. Other issues include gaps in AI skills and leadership (53%), integration with legacy systems (48%), and difficulty scaling projects beyond the pilot stage (48%).
The survey also found uneven oversight at the board level. While boards are generally active in areas such as technology investment and cybersecurity, fewer respondents said they are proactive in monitoring the ethical use of AI or leadership readiness for digital transformation.
The findings are based on a March 2026 survey of 100 U.S. private company leaders, including senior executives and board members.
