TL;DR — Key Takeaways
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AI ROI Remains Uneven: While 80% of organizations report positive returns on AI investments, only 28% experience strongly positive ROI.
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Growth Metrics Drive Stronger Returns: Departments measuring AI success through revenue, output and customer satisfaction are nearly three times as likely to report strong ROI compared to those focused on efficiency alone.
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Leadership and Standardization Matter: Organizations with dedicated chief AI officers and standardized AI platforms report substantially higher rates of strong ROI.
A vast majority of enterprise leaders report positive financial returns on their artificial intelligence (AI) investments, but only a fraction sees strong returns because of structural and leadership bottlenecks.
A study from Wharton School of the University of Pennsylvania and market research firm GBK Collective found that while 80% of organizations experience positive ROI from AI, just 28% report strongly positive results.
A primary driver of the ROI divide lies in how companies measure success. Although 83% of enterprise leaders expect AI to dramatically transform their industries within five years, 52% still focus AI efforts primarily on cost-cutting or productivity gains. The most common success metric remains “hours saved” (40%), while “net-new revenue” trails at 27%.
However, departments evaluating AI against growth metrics — such as net-new revenue, output volume, or customer satisfaction — are nearly three times as likely to see strong ROI compared to those measuring efficiency alone (35% versus 13%), based on the survey of 1,416 U.S. enterprise leaders and junior-to-mid-level employees.
“Companies believe AI is going to transform their industries, but many are still asking it to prove itself by saving time,” said Prasanna Tambe, professor at the Wharton School and Faculty Co-Director of Wharton Human-AI Research. “The companies seeing stronger returns are going further. They are redesigning workflows, putting clear ownership and governance in place, and measuring AI against outcomes that matter to growth.”
Organizational structure plays a critical role in unlocking AI value. Companies with a designated Chief AI Officer reported a 58% rate of strong ROI, compared to 24% for those assigning AI oversight to existing executives.
Similarly, organizations standardized on a single approved AI platform reported strong ROI at 50%, compared to just 9% for those still experimenting.
Additionally, while 67% of departments deploy AI agents, deep integration remains sparse. Only 28% have fully embedded AI into core processes, and a mere 17% allow agents to act autonomously. Most companies operate in a supervised middle — paying for automated capabilities while manually reviewing every output — which dilutes potential returns.
The report highlights a growing divide between executive perception and workplace reality. Some 73% of leaders believe departmental workflows have significantly changed, compared to 58% of entry- and mid-level employees.
Meanwhile, 78% of executives believe employees receive adequate AI training; only 56% of non-executive workers agree.
The study also outlines shifting workforce dynamics.
While 82% of leaders report that AI enables newer staff to contribute faster, 24% expect to reduce entry-level hiring over the next two to five years. Furthermore, nearly half of senior executives (48%) and junior staff (46%) expressed concern over potential skill or cognitive atrophy due to heavy AI reliance.
While daily executive AI usage rose to 62%, enthusiasm has softened.
For the first time in the study’s four-year history, overall excitement fell by 8% as caution and skepticism increased, signaling that corporate leaders are shifting focus from early hype to demanding concrete results.
