Eighty percent of enterprise leaders report positive AI ROI, but only 28% describe their returns as strongly positive, according to the 2026 AI adoption report from Wharton Human-AI Research and GBK Collective released October 13. Strong returns cluster at companies that redesign workflows and measure growth, and those companies are no more likely to cut staff.
Key Takeaways
- Only 7% of organizations succeed on all three of the study’s markers of AI success: proving value, transforming workflows, and aligning the organization around AI.
- Companies measuring AI against growth outcomes report strong ROI at nearly three times the rate of those measuring efficiency alone, 35% versus 13%.
- 37% of enterprise leaders report AI-related staff reductions and 33% report slowed or frozen hiring.
- Organizations with strong ROI are no more likely than others to report staff reductions or hiring freezes.
- 78% of leaders say employees receive adequate AI training, but only 56% of entry- and mid-level employees agree.
- 24% of leaders expect fewer entry-level hires over the next two to five years, compared with 14% expecting fewer executive roles.
AI ROI Is Widespread, But Strong Returns Are Not
Four years into the enterprise AI cycle, adoption is no longer the question. The Wharton–GBK study, now in its fourth annual edition, finds that 80% of enterprise leaders, defined as managers, directors, vice presidents and C-suite executives, see positive returns on AI investments. The gap is in the size of those returns. Just 28% call them strongly positive, and only 7% of organizations clear all three of the study’s success markers.
The findings come from a 15-minute online survey of 1,416 full-time employees at U.S. private-sector companies with more than 1,000 employees and over $50 million in revenue, conducted July 9 through 29, 2026. The sample includes 1,007 enterprise leaders and 409 entry- and mid-level employees. The results describe large companies, not small businesses.
AI ROI Measurement Shapes The Results
How a company defines success appears to matter as much as the technology. Among organizations measuring AI against growth outcomes such as new revenue, new products or customer experience, 35% report strong ROI. Among those measuring efficiency alone, 13% do.
Most companies are still in the efficiency camp. 52% of leaders say AI’s primary job over the next 12 to 24 months is improving productivity or reducing costs, while 22% point to growing the business. Wharton professor Prasanna “Sonny” Tambe said many companies are “still asking it to prove itself by saving time,” while stronger performers redesign workflows and measure outcomes tied to growth.
Workflow Redesign, Not AI Job Cuts, Separates Top Performers
The study’s workforce data complicates the assumption that AI returns come from reducing headcount. 37% of enterprise leaders report AI-related staff reductions and 33% report slowed or frozen hiring. Yet organizations reporting strong ROI are no more likely than others to report either. Instead, they are more likely to have changed management structures, redesigned workflows, monitored AI use, included AI in performance reviews and trained employees adequately.
Workflow transformation shows the clearest link to returns. Only one in five organizations meets all three of the study’s workflow measures: significantly changed workflows, AI embedded in core processes and use of AI agents. Among departments that do, 67% report strongly positive ROI, compared with 28% of leaders overall.
The Supervised Middle Limits AI Agent Returns
AI agents are common but tightly controlled. 67% of departments use agents in some form, yet only 28% say AI is fully embedded in core processes, and 17% let agents act without a person approving each step. GBK Collective’s Brian Smith described most companies as sitting in a “supervised middle,” paying for autonomy while reviewing every action, where returns are weakest.
Leaders And Employees See Different AI Transformations
For the first time, the study surveyed junior staff alongside leaders, and the two groups describe different workplaces. 73% of leaders say AI has significantly changed workflows, compared with 58% of entry- and mid-level employees. The training gap is wider: 78% of leaders believe employees receive adequate AI training, while 56% of employees agree. Leaders are also more likely to say a clear long-term AI vision exists, 79% versus 64%.
The gap does not reflect employee resistance. 73% of entry- and mid-level employees say AI has improved their own role, and 84% of users say it saves them time. A similar integration gap appears among smaller companies, where only 14% of small businesses have fully integrated AI into core operations.
AI Workforce Impact Hits The Entry Level First
Pressure concentrates at the start of the career ladder. 24% of leaders expect fewer entry-level hires over the next two to five years, compared with 14% expecting fewer executive roles, even as 82% say AI helps newer employees contribute faster. Skill erosion is a shared concern: 48% of VP-level leaders and 46% of entry- and mid-level employees worry their own skills or thinking are declining with AI use, compared with 32% of managers and directors.
Usage Rises As Enthusiasm Cools
Daily AI use among managers and above rose about 16 points to 62%, and 91% use it more than weekly. Sentiment moved the other way. The share of leaders describing themselves as “excited” fell eight points, while “cautious” rose seven and “skeptical” rose eight, the first year in the study’s history that usage and sentiment diverged.
How Organizations Structure AI Oversight Matters
Ownership of AI tracks with results. 58% of managers and above at organizations with a newly designated Chief AI Officer report strongly positive ROI, compared with 24% where AI was added to an existing executive’s duties and 8% with no such role. Organizations standardized on one approved AI platform report strong ROI at 50%, versus 9% for those still experimenting. The study reports these as associations, not proof that the structures cause better returns.
FAQs
What Is The ROI Of AI?
In the 2026 Wharton–GBK study, 80% of enterprise leaders reported positive returns on AI investments, but only 28% described those returns as strongly positive.
Does AI Have A Good ROI?
For most large companies, AI returns are positive but modest. Strong returns are concentrated among organizations that redesign workflows, measure growth outcomes and train employees adequately.
Why Aren’t More Companies Seeing Strong ROI From AI?
The study points to measurement and workflow. Most companies measure efficiency rather than growth, few embed AI in core processes, and most require human approval for every AI agent action.
How Do You Measure AI ROI?
Companies that measure AI against growth outcomes such as new revenue or products report strong ROI at 35%, compared with 13% for those tracking efficiency alone.
Are Companies Cutting Jobs Because Of AI?
Some are. 37% of enterprise leaders report AI-related staff reductions, but companies with strong AI returns are no more likely than others to report cuts or hiring freezes.
