Most companies expect greater productivity and efficiency from AI, but that hasn't prevented nearly 80% from reverting to human-centric processes after their AI initiatives yielded disappointing results.
Despite positive expectations of corporate AI, nearly 80% of companies say they’ve backtracked artificial intelligence initiatives due to performance issues, integration challenges, and skills gaps.
New research from IT training and certification provider CompTIA reveals that the promise of AI is outpacing the reality of the experiences organizations are having with their AI implementations. While corporate leadership continues to expect AI-driven productivity gains (82% anticipate measurable returns), as many as 79% of companies report backtracking to human-centered solutions after AI initiatives failed to meet business objectives. More than 1,100 U.S. business respondents were surveyed in September for the report, AI’s Impact on Productivity and the Workforce.
This gap between expectation and actual experiences highlights the challenges enterprises face when deploying AI at scale, CompTIA says. “Experimentation and the accompanying two steps forward, one step back is a healthy dynamic of AI’s progression in the enterprise,” said Tim Herbert, chief research officer at CompTIA, in a statement. “This undoubtedly affects the labor market, but not nearly at the rate suggested by most alarmist prognosticators.”
Why AI projects fail
More than half of companies (52%) cite underperforming AI as the primary culprit, while 50% struggle with scaling AI to handle complex tasks.
Nearly half (47%) of organizations attempting to integrate AI into existing workflows point to integration problems as the cause of AI failures. Another 48% said that they found the cost of the technology outweighs the anticipated return on investment. CompTIA’s survey of more than 1,100 U.S. businesses reveals that successful AI deployments require a balance of orchestrating work across people, processes, and technology.
“The findings reaffirm the importance of holistic approaches to AI implementations, from across the tech stack to workflow processes to people skills,” Herbert said.
CompTIA estimates a 37% weighted average adoption rate of AI across respondents, but despite the widespread AI adoption, AI skills training strategies remain reactive rather than proactive. Only one in three companies currently mandates AI training for staff, though that figure will change as 85% of respondents are either already providing or planning to provide AI compliance and security training.
The research shows employer demand for AI talent has tripled compared to overall tech hiring, based on CompTIA’s analysis of Lightcast job posting data. Among those not requiring AI training, 46% say they are still in early AI adoption phases, while 37% remain uncertain about the value of AI training.
Workforce impact unclear
Some 38% of companies reported taking staffing actions that they attribute to AI, and among those companies, 48% said that they moved staff to other roles and 36% stated that they hired new employees. Another two-thirds (64%) of companies acknowledged using AI to cover for unpopular business decisions, such as cost-cutting or layoffs.
Junior and mid-level workers are the most vulnerable, according to this study, with 53% and 52% of affected companies reporting impacts at these levels, respectively. This reality raises concerns about talent pipeline development, with 91% of companies worried about AI disrupting early-career opportunities that traditionally feed the workforce pyramid, according to CompTIA.
CompTIA’s research segments companies into three tiers:
- 18% showing low adoption (under 10% of workers using AI)
- 51% in the mid-range (20%-49% usage)
- 29% reporting high adoption rates
Larger firms tend toward top-down AI mandates from the C-suite, while adoption at smaller companies is often bottom-up, driven by power users, according to CompTIA. Companies with higher AI usage rates view the technology more favorably as a productivity tool, suggesting positive experiences breed broader adoption—or conversely, that companies struggling with AI implementations remain skeptical of its value proposition.
Business and technology leaders must understand that AI success will require equal attention to technology capabilities, workflow integration, and workforce development, according to CompTIA. “It remains to be seen just how much AI will boost productivity over the long-term and the degree to which it will be statistically measurable,” the report reads.
