SYDNEY, Australia, June 17, 2025: Gartner, Inc. has announced the top data and analytics (D&A) predictions for 2025 and beyond. Among the top predictions, half of business decisions will be augmented or automated by AI agents; executive AI literacy will drive higher financial performance; and critical failures in managing synthetic data will risk AI governance, model accuracy and compliance.
Carlie Idoine, VP Analyst at Gartner, said, “Nearly everything today – from the way we work to how 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 organization.”
Gartner recommends organizations use the following strategic assumptions to inform their planning over the next 2-3 years.
By 2027, 50% of business decisions will be augmented or automated by AI agents for decision intelligence.
Decision intelligence combines data, analytics and AI to create decision flows that support and automate complex judgements. AI agents enhance this process by handling the complexity, analysis and retrieval of various data sources. Gartner recommends D&A leaders work with business stakeholders to identify and prioritize decisions critical to the success of the organization, and those that can benefit from more effective application of analytics and AI.
“AI agents for decision intelligence aren’t a panacea, nor are they infallible,” said Idoine. “They must be used collectively with effective governance and risk management. Human decisions still require proper knowledge, as well as data and AI literacy.”
By 2027, organizations that emphasize AI literacy for executives will achieve 20% higher financial performance compared with those that do not.
Unlocking AI’s full business potential requires building executive AI literacy. They must be educated on AI opportunities, risks and costs to make effective, future-ready decisions on AI investments that accelerate organizational outcomes. Gartner recommends D&A leaders introduce experiential upskilling 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 and analytics leaders will face critical failures in managing synthetic data, risking AI governance, model accuracy, and compliance.
Using synthetic data to train AI models is now a critical strategy for enhancing privacy and generating diverse datasets. However, complexities arise from the need to ensure synthetic data accurately represents real-world scenarios, scales effectively to meet growing data demand and integrates seamlessly with existing data pipelines and systems.
“To manage these risks, organizations need effective metadata management,” said Idoine. “Metadata provides the context, lineage and governance needed to track, verify and manage synthetic data responsibly, which is essential to maintaining AI accuracy and meeting compliance standards.”
By 2028, 30% of GenAI pilots that move forward into large scale production will be built versus deployed using packaged applications to lower cost and increase control.
Building GenAI models in-house offers flexibility, control and long-term value that many packaged tools cannot match. As internal capabilities grow, Gartner recommends organizations adopt a clear framework for build versus buy decisions. It must factor in cost, time to market, available skillsets, integration capabilities, compliance and risk.
By 2027, organizations that prioritize semantics in AI-ready data will increase their GenAI model accuracy by up to 80% and reduce costs by up to 60%.
Poor semantics in GenAI lead to greater hallucinations, more tokens required and higher costs. Organizations that rethink data management to focus on active metadata drive greater model accuracy and efficiency, have higher AI data readiness and reduce compute costs. According to Gartner, this enables AI agents to operate more effectively and facilitates smarter, faster decision making across the organization.
By 2029, 10% of global boards will use AI guidance to challenge executive decisions that are material to their business.
As AI becomes embedded in board-level strategy, the need for strong data governance, regulatory clarity and reputation management will intensify. Gartner recommends boards define the boundaries of AI involvement in decision making and establish clear policies around oversight, responsibility and regulatory compliance. This will enable them to use AI as a strategic advisor while maintaining trust and control.
Gartner clients can read more in Predicts 2025: AI-Powered Analytics Will Revolutionize Decision Making and Predicts 2025: CDAOs Must Embrace Their Role in AI or Risk Credibility Loss.
Additional insight is available in the complimentary Gartner webinar The Gartner Top Data & Analytics Predictions for 2025.
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