Gartner, Inc. announced the top Data & Analytics (D&A) predictions for 2025 and beyond. Highlights include half of business decisions enhanced or automated by AI agents; executive AI literacy driving greater financial performance; and critical failures in synthetic data management posing risks to AI governance, model accuracy, and compliance.
“Almost everything today – from how we work to how we make decisions – is directly or indirectly influenced by AI. But it does not deliver value on its own – AI needs to be closely aligned with data, analytics, and governance to enable intelligent and adaptive decisions and actions throughout the enterprise”, says Carlie Idoine, Gartner Vice President Analyst.
Gartner recommends companies use the following strategic premises 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
The decision intelligence combines data, analytics and Artificial Intelligence to create decision flows that support and automate complex judgments. AI agents enhance this process by dealing with the complexity, analysis, and retrieval of multiple data sources. Gartner recommends that Data & Analytics leaders work with business stakeholders to identify and prioritize critical decisions for the company’s success and those that can benefit from a more effective application of 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 Artificial Intelligence literacy.”
By 2027, companies that emphasize AI literacy for executives will achieve a 20% higher financial performance compared to those who do not
To unlock the full business potential of Artificial Intelligence, executives need to develop AI literacy. They must be educated about the opportunities, risks, and costs of Artificial Intelligence so they can make effective and future-ready decisions about AI investments that accelerate organizational outcomes. Gartner recommends that D&A leaders introduce experimental enhancement programs for executives, such as developing domain-specific prototypes to make AI tangible. This will lead to increased and more suitable investment in AI resources.
By 2027, 60% of Data & Analytics leaders will face critical failures in synthetic data management, jeopardizing AI governance, model accuracy, and compliance
Using synthetic data to train AI models is now an essential strategy to enhance privacy and generate diverse data sets. However, complexities arise from the need to ensure that synthetic data accurately represents real-world scenarios, scales effectively to meet the growing data demand, and seamlessly integrates with existing pipelines and data systems.
“To manage these risks, companies need effective metadata management,” says Idoine. “Metadata provides the necessary context, lineage, and governance to track, verify, and responsibly manage synthetic data, which is essential to maintaining AI accuracy and meeting compliance standards.”
By 2028, 30% of GenAI pilots moving into large-scale production will be created internally rather than implemented using off-the-shelf applications to reduce cost and increase control
Internally creating models of Generative Artificial Intelligence (GenAI) offers flexibility, control, and long-term value that many off-the-shelf tools cannot match. As internal resources grow, Gartner recommends companies adopt a clear framework for build versus buy decisions. It should take into account cost, time to market, available skill sets, integration capabilities, compliance, and risks.
By 2027, companies prioritizing 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 higher hallucination rates, more necessary tokens, 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 computation costs. According to Gartner, this enables AI agents to operate more effectively and facilitates smarter and faster decision-making throughout the company.
By 2029, 10% of global boards of directors will use AI guidance to challenge executive decisions that are crucial to their business
As AI becomes ingrained in board strategy, the need for strong data governance, regulatory clarity, and reputation management will intensify. Gartner recommends that boards set boundaries for AI involvement in decision-making and establish clear policies on supervision, 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 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 information is available in Gartner’s free webinar “The Gartner Top Data & Analytics Predictions for 2025”.
