Though still increasing investments in data and AI initiatives, many companies say the programs have not yet delivered the benefits they expected, according to new research from global AI-centered technology research and advisory firm Information Services Group (ISG).
The ISG Market Lens Data and AI Programs survey found that three-quarters of companies expect to increase their annual budgets in the next two years for projects such as improving data quality, integration, and security, even as most overall IT budgets remain flat.
A majority of enterprises expect the value created by data initiatives to grow by more than 10 percent during that time. However, high spending in some areas has delivered low performance so far.
“Data is the growth area for IT, especially to support adoption of AI,” said Alex Bakker, ISG distinguished analyst and co-author of the study. “Companies believe investments in data will ultimately enable better insights and efficiency through AI. But multiple technology and operational barriers are preventing many companies from reaching AI goals.”
The data activity most funded by enterprises in 2025 is gaining more business value from insights.
Other high-spend areas include increasing productivity, data security, and integration.
Large investments in productivity, data quality, validation, and de-duplication have not yielded strong results for enterprises, the survey showed.
Companies believe centralized data governance is crucial to AI success, but only 43 percent say they have created a consistent data structure. Thirty-eight percent believe the cost of harmonizing data management outweighs its likely benefits.
The slow progress on data management has significant implications for AI adoption, according to ISG.
AI application data usability is the most-cited data challenge companies expect in 2025-2026, and nearly one-third of enterprises expect data quality, accuracy, and consistency to be one of their biggest AI challenges.
The complexity of integrating and updating data infrastructure for thousands of applications in a typical large enterprise is a major barrier to success.
More than two-thirds of companies say the ability to manage complexity, rather than a lack of innovation, is what hinders their progress on data and AI solutions.
While many companies have integrated some financial, employee, IT, or other data into centralized management platforms, there is no category of data that has been mostly or completely integrated at a majority of firms.
A lack of expertise is another setback for data and AI projects, according to the survey.
Enterprises struggle to find employees with both technical skills and industry knowledge who can apply technology for practical purposes.
More than one-quarter of enterprises cite talent issues as the main barrier or delay to bringing data initiatives to full production.
To help address the complexity of managing data, enterprises are planning to increase their spending on outsourced data services by an average of seven percent over the next two years, with 60 percent of enterprises engaging new providers.
Organizations are seeking providers’ help with data organization, data design, AI, and data productivity and access to multidisciplinary talent that combines technical expertise with business understanding.
“Data is seen as a key driver for both revenue growth and profitability, but inflexible design and ineffective tools to expose or share data are holding enterprises back,” said Michael Dornan, principal analyst and co-author of the study. “In the era of AI, enterprises need a business- and data-first approach to solve many of these complexity challenges, and this need is reframing how they engage managed service providers.”
The ISG study, conducted globally in May 2025, surveyed 281 executives in mostly multinational enterprises in the Americas, Europe and Asia Pacific with decision-making responsibility for IT spending in their organization.
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