Gartner: 45% of High-Maturity Firms Run AI Projects Over 3 Years
Jul 19 2025
2025-07
Semiconductors
Gems Sensors Inc
A new Gartner survey shows that organizations with high AI maturity are staying ahead by keeping their AI projects alive for the long run. According to the data, 45% of companies with advanced AI maturity have been running their AI initiatives for more than three years, ensuring that these projects keep delivering value and impact over time. By contrast, only 20% of companies with lower AI maturity have managed to maintain their AI projects that long.
One big reason high-maturity companies can keep AI going is that they pick projects carefully—choosing based on clear business value and technical feasibility—and back them up with solid governance and engineering practices. The survey, which ran in Q4 2024, gathered insights from 432 respondents across the US, UK, France, Germany, India, and Japan. It used Gartner’s structured AI Maturity Model, where companies rate themselves from 1 (“Planning/Initial”) to 5 (“Leading”). On average, high-maturity companies scored between 4.2 and 4.5, while low-maturity organizations came in at just 1.6 to 2.2.
Trust turns out to be a make-or-break factor for AI success. Birgi Tamersoy, Senior Director Analyst at Gartner, notes that trust is critical for any AI or GenAI project to succeed. The survey found that 57% of business units in high-maturity companies trust and are ready to use new AI solutions, while only 14% of low-maturity companies report the same. Building trust in AI and GenAI is what drives real adoption — and adoption is the first step to creating measurable value.
Still, there are common hurdles no matter how mature a company’s AI is. Data availability and quality remain the biggest challenges for everyone: 34% of leaders at low-maturity companies and 29% at high-maturity companies flagged it as a top obstacle to implementation. Security threats are another sticking point—48% of high-maturity leaders listed security risks among their top three AI barriers. And for less mature organizations, 37% said they struggle most with finding the right use cases in the first place.
High-maturity companies stand out in how they track performance. The survey found that 63% of companies with advanced AI maturity have clear metrics in place. These companies routinely measure ROI, financial risks, and customer impact to fine-tune their projects and keep improving results.
Strong leadership also makes a difference. 91% of leaders in high-maturity organizations say they now have a dedicated AI leader in place—someone focused on driving AI innovation, building the necessary infrastructure, putting together AI teams, and designing the architecture to scale. Nearly 60% say they’ve integrated their AI strategy, governance, data, and infrastructure to increase consistency and efficiency across the company. As Tamersoy puts it, this kind of coordinated effort needs a dedicated team that knows how to manage AI as a strategic resource.
For businesses still working to level up their AI maturity, the message is clear: pick the right projects, invest in trusted data, measure what matters, and put strong AI leaders in place. Those moves make all the difference between short-term experiments and AI programs that keep delivering real, long-lasting impact.
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