O Gartner, Inc announced the key predictions for 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 greater financial performance; and critical failures in synthetic data management will jeopardize 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 doesn’t deliver value on its own – AI needs to be strongly aligned with data, analytics, and governance to enable intelligent and adaptive decisions and actions across the enterprise,” 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 AI to create decision flows that support and automate complex judgments. AI agents enhance this process by handling complexity, analysis, and retrieval from 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 could 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 AI literacy.”
By 2027, companies that emphasize AI literacy for executives will achieve 20% greater financial performance compared to those that do not
To unlock the full business potential of AI, developing executives’ AI literacy is necessary. They must be educated on AI opportunities, risks, and costs to make effective, future-ready decisions about AI investments that accelerate organizational outcomes. Gartner recommends that D&A leaders introduce experiential enhancement programs for executives, such as domain-specific prototype development to make AI tangible. This will lead to greater 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
The use of synthetic data to train AI models is now an essential strategy to enhance privacy and generate diverse datasets. However, complexities arise from the need to ensure synthetic data accurately represents real-world scenarios, scales effectively to meet growing data demands, and seamlessly integrates with existing pipelines and data systems.
“To manage these risks, companies need effective metadata management,” says Idoine. “Metadata provides the context, lineage, and governance needed to responsibly track, verify, and manage synthetic data, which is essential for maintaining AI accuracy and meeting compliance standards.”
By 2028, 30% of GenAI pilots that progress to large-scale production will be built in-house, rather than implemented using off-the-shelf applications, to reduce cost and increase control
Building Generative AI (GenAI) models in-house offers flexibility, control, and long-term value that many off-the-shelf tools cannot match. As in-house capabilities grow, Gartner recommends companies adopt a clear framework for build versus buy decisions. It should account for cost, time to market, available skill sets, integration resources, compliance, and risks.
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 lead to more hallucinations, higher tokens needed, and increased costs. Companies that rethink data management to focus on active metadata enhance 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 company.
By 2029, 10% of global boards will use AI guidance to challenge executive decisions that are critical to their business
As AI is incorporated into board 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 on oversight, accountability, and regulatory compliance. This will allow 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“.
