Rapid AI advancements have left IT and business leaders feeling burned out. CIOs can take steps -- such as finding quick wins and upskilling employees -- to reduce this fatigue.
After years of excitement around GenAI, the fatigue is starting to kick in.
Many IT professionals -- such as CIOs and CTOs -- have overseen efforts to rapidly deploy generative AI (GenAI) capabilities across their organizations. The technology can offer various benefits, but the combination of media hype and unrealistic expectations has led to a feeling of burnout known as AI fatigue.
"We saw the overnight transformation people got from ChatGPT and things like that. And they kind of expected a similar level of transformational change, and it just didn't really come straight away," said David Sewell, CTO at Synechron, a digital transformation consulting firm.
Data readiness issues, legal constraints and a lack of talent have frustrated business leaders. Returns have also been hard to find. For example, 95% of organizations reported no ROI from their GenAI investments, according to a 2025 study by MIT Media Lab's Project NANDA.
To reduce the feeling of AI fatigue, CIOs can invest in employee learning, calm the fears of skeptical colleagues, look for quick wins and conduct risk-reward analyses to prioritize AI initiatives effectively.
What causes AI fatigue?
AI fatigue stems from unrealistic expectations, legal obstacles and excessive vendor options, which overwhelm organizations as they attempt to adapt to AI's rapid advancement.
1. Inflated expectations
Unlike many technological developments, GenAI -- in the form of tools, such as ChatGPT and Gemini -- reached the public before it reached most IT departments. This unconventional rollout generated significant attention and hype, causing many business leaders to expect instant productivity gains and cost savings. However, most breakthroughs in technology take many years to drive clear, measurable ROI -- and GenAI is no exception.
"When the internet came out, it was pretty useless, because you couldn't find anything until people started to make good browsers," said Graeme Thompson, CIO at Informatica, a data management platform company.
Similarly, the early days of cloud computing saw organizations grapple with infrastructure challenges before they realized its full potential. GenAI has followed a similar path, with enterprise adoption slowed by the need for organizations to prepare their data for AI-driven insights.
2. Legal and compliance barriers
As organizations explore GenAI deployment, they often encounter resistance from legal teams and oversight functions. This hesitation stems from a combination of uncertainty about how the technology works and fears about potential risks -- such as data privacy violations, intellectual property issues and compliance breaches. These challenges can stall AI initiatives and create fatigue.
"We've had a couple of instances where we've tried to deploy something and someone -- either in legal or in another oversight function -- has said 'no,' just because partly they're afraid [and] partly they don't know enough about how it works," Thompson said.
3. Vendor overload
The rapid growth of the AI market has led to an overwhelming number of vendors touting GenAI capabilities. As decision-makers in large organizations receive countless pitches from these vendors, they can struggle to differentiate between genuine innovation and exaggerated claims. This constant barrage of options creates confusion and fatigue.
"Any decision maker in a large organization probably hears about another AI vendor every five minutes, right?" said Shay Levi, CEO at Unframe AI, an enterprise AI company.
How can CIOs minimize AI fatigue?
IT leaders can reduce AI fatigue if they communicate GenAI's limitations, address ethical concerns and empower employees. These steps can turn frustration into opportunity and build a foundation for success as AI evolves.
1. Explain the limitations
To effectively address AI fatigue, CIOs must set realistic expectations about what GenAI can achieve in the short term. Many employees and business leaders have been swept up in the excitement surrounding GenAI and expect immediate, transformative results.
However, GenAI can require significant groundwork -- including data preparation, infrastructure upgrades and iterative development. CIOs can offer context about the challenges and gradual nature of AI adoption to help their teams understand that meaningful transformation is a long-term process rather than an overnight success.
"From a CIO, CTO perspective, [the goal] is making sure that you know everyone involved -- business leaders, technology leaders -- are all aware of the limitations, and they know that the real transformation is possible, but it's more of a journey," Sewell said.
2. Calm the fears of AI skeptics
CIOs must proactively address concerns about the risks and ethical implications of GenAI deployment as many employees and stakeholders worry about data leakage, security breaches and AI hallucinations.
Although these fears address real concerns, they sometimes stem from a lack of understanding about how the technology works or from high-profile incidents where organizations have misused AI systems. To build trust and ease apprehension, CIOs can foster transparency, educate teams about the safeguards in place and emphasize responsible AI practices.
"Calm people down and reassure them. [Say] look, we're not going to do anything dangerous and dumb. The first use case we're going to go after is not loading everybody's health benefits and compensation into the model and see if we can take a few bucks out of our annual benefits costs," Thompson said.
3. Find quick wins
AI fatigue often occurs when business leaders view GenAI adoption as a grandiose, all-encompassing transformation project, Levi said. Instead, CIOs can start with quick wins that have low risk and high reward. This approach lets IT leaders build trust as they demonstrate GenAI's benefit on a practical level.
"I don't believe you can preach to them that the future is going to be better. I think you have to show them … by making some small progress today with what's available now," Thompson said.
I don't believe you can preach to them that the future is going to be better. I think you have to show them.
Graeme ThompsonCIO, Informatica
4. Prioritize initiatives
IT departments in large organizations can face hundreds of AI deployment requests, including those related to marketing tools and legal automation. However, CIOs must prioritize which to start with due to limited time, resources and labor capacity.
CIOs can create a central group to filter, assess and execute these deployments, Thompson said. This group acts as a hub to evaluate incoming ideas, prevent duplication of efforts and ensure alignment with organizational goals.
People in these groups can develop or identify a framework to assess each initiative's risk-to-reward ratio. This ensures organizations allocate resources to projects that offer the highest value with the least effort and risk.
"We ended up doing a two by two … which [considers] how much effort is it, and what's the value if it works -- or how much risk is it?" Thompson said.
5. Invest in employee learning
GenAI requires a workforce that understands its capabilities, limitations and applications. CIOs should invest in AI training programs and create opportunities for employees to engage with AI tools. This reduces skepticism and empowers employees to contribute to AI initiatives effectively.
"Give the employees the opportunity to learn this really exciting, once-in-a-career, tech transformation … You have to drive that literacy," Thompson said.
Tim Murphy is site editor for Informa TechTarget's IT strategy group.
