A recent survey by Gartner, Inc. indicates that organisations with high AI maturity are significantly more successful at sustaining their AI initiatives, with 45 percent reporting that their AI projects remain operational for three years or more.
The survey, conducted in Q4 2024 with 432 respondents across the U.S., U.K., France, Germany, India, and Japan, assessed AI maturity using Gartner's AI Maturity Model. High-maturity organisations, scoring an average of 4.2-4.5 on a 5-level scale, demonstrated that selecting AI projects based on business value and technical feasibility, coupled with robust governance and engineering practices, is key to long-term success.
This stands in stark contrast to low-maturity organisations, where only 20 percent achieve similar longevity. "Trust is one of the differentiators between success and failure for an AI or GenAI initiative," stated Birgi Tamersoy, Sr Director Analyst at Gartner.
The survey found that in 57 percent of high-maturity organisations, business units trust and are ready to utilise new AI solutions, compared to a mere 14 percent in low-maturity organisations. "Building trust in AI and GenAI solutions fundamentally drives adoption, and since adoption is the first step in generating value, it significantly influences success," Tamersoy added.
Additionally, the report also reveals that, despite varying maturity levels, data availability and quality remain prominent hurdles in AI implementation. The survey revealed that 34 percent of leaders from low-maturity organisations and 29 percent from high-maturity organisations identified these as top challenges.
For high-maturity organisations, security threats were also a significant barrier (48 per cent), while low-maturity organisations frequently struggled with identifying the right use cases (37 percent).
A notable finding is the strong trend towards dedicated AI leadership in high-maturity organisations, with 91 percent already having appointed such roles. These AI leaders are primarily focused on fostering AI innovation (65 per cent), delivering AI infrastructure (56 percent), building AI organisations and teams (50 percent), and designing AI architecture (48 percent).
Furthermore, nearly 60 percent of leaders in high-maturity organisations reported centralising their AI strategy, governance, data, and infrastructure capabilities to enhance consistency and efficiency.
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