– To unlock the full potential of Artificial Intelligence for business, it is necessary to develop executive AI literacy
– Using synthetic data to train Artificial Intelligence models is an essential strategy to increase privacy and generate data sets
O Gartner, Inc.. announces the main forecasts of Data&Analytics (D&A) for 2025 and beyond. Among the highlights: half of business decisions will be enhanced or automated by Artificial Intelligence (AI) agents; executive AI literacy will drive higher financial performance; and critical flaws in synthetic data management will put AI governance, model accuracy, and compliance at risk.
“Almost everything today – from the way we work to the way we make decisions – is directly or indirectly influenced by AI. But it doesn’t deliver value on its own – AI needs to be tightly aligned with data, analytics and governance to enable intelligent, adaptive decisions and actions across the enterprise,” he says Carlie Idoine, Vice President Analyst at Gartner.
Gartner recommends that companies use the following strategic assumptions to guide their planning over the next 2 to 3 years.
By 2027, 50% of business decisions will be enhanced or automated by AI agents for decision intelligence
Decision intelligence combines data, analytics and Artificial Intelligence to create decision flows that support and automate complex judgments. AI agents enhance this process by handling the complexity, analysis and retrieval of multiple data sources. Gartner recommends that Data & Analytics leaders work with business stakeholders to identify and prioritize decisions that are critical to the company’s success and those that can benefit from a more effective application of AI. analytics and AI.
“AI agents for decision intelligence are not a panacea, nor are they infallible,” says Idoine. “They must be used collectively with effective governance and risk management. Human decisions still require adequate knowledge, as well as data and AI literacy.”
By 2027, companies that emphasize AI literacy to executives will achieve 20% higher financial performance compared to those that do not
To unlock the full business potential of AI, executives need to develop AI literacy. They need to be educated on the opportunities, risks, and costs of AI so they can make effective, future-proof decisions about AI investments that accelerate organizational outcomes. Gartner recommends that D&A leaders introduce experiential enrichment programs for executives, such as developing domain-specific prototypes to make AI tangible. This will lead to greater and more appropriate investment in AI capabilities.
By 2027, 60% of Data & Analytics leaders will face critical flaws in synthetic data management, putting AI governance, model accuracy, and compliance at risk
Using synthetic data to train AI models is now a essential strategy to enhance privacy and generate diverse datasets. However, complexities arise from the need to ensure that synthetic data accurately represents real-world scenarios, scales effectively to meet growing data demands, and integrates seamlessly with pipelines and existing data systems.
“To manage these risks, organizations need effective metadata management,” says Idoine. “Metadata provides the context, lineage, and governance needed to track, verify, and responsibly manage synthetic data, which is essential to maintaining AI accuracy and meeting compliance standards.”
By 2028, 30% of the GenAI pilots that advance to full-scale production will be built in-house, rather than deployed using off-the-shelf applications, to reduce cost and increase control
The creation of models of Generative Artificial Intelligence (GenAI) in-house offers flexibility, control and long-term value that many off-the-shelf tools can’t match. As in-house capabilities grow, Gartner recommends that companies adopt a clear framework for design decisions versus purchase. It should take into account cost, time to market, available skill sets, integration capabilities, compliance, and risk.
By 2027, companies that prioritize semantics in AI-ready data will increase the accuracy of their GenAI models by up to 80% and reduce costs by up to 60%
Low-quality semantics in GenAI leads to greater hallucinations, more tokens required and higher costs. Companies that rethink data management to focus on active metadata increase model accuracy and efficiency, have more AI-ready data and reduce computing costs. According to Gartner, this enables AI agents to operate more effectively and facilitates smarter, faster decision-making across the enterprise.
By 2029, 10% of global boards will use AI guidance to challenge executive decisions that are important to their business
As AI is incorporated into board strategy, the need for a strong data governance, regulatory clarity and reputation management will intensify. Gartner recommends that boards define the boundaries of AI involvement in decision-making and establish clear policies on oversight, accountability and regulatory compliance. This will enable them to use AI as a strategic advisor while maintaining trust and control.
Gartner clients can read more at “Predicts 2025: AI-Powered Analytics Will Revolutionize Decision Making" and "Predicts 2025: CDAOs Must Embrace Their Role in AI or Risk Credibility Loss”. Additional information is available in the free Gartner webinar “The Gartner Top Data & Analytics Predictions for 2025”.
About Gartner for Data & Analytics Leaders
O Gartner for Data & Analytics Leaders provides objective and actionable insights for CDAOs and Data & Analytics leaders, helping them accelerate their D&A strategy and operating model to increase business value. Additional information is available at https://www.gartner.com/en/data-analytics. Follow news and updates from Gartner for Data & Analytics Leaders on X and LinkedIn using #GartnerDA.
About Gartner
O Gartner, Inc. delivers objective, actionable insights that drive smarter decisions and better performance for enterprises’ mission-critical priorities. To learn more, visit www.gartner.com.
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