The Gartner, Inc.. announced the main forecasts of Data&Analytics (D&A) for 2025 and beyond. Among the highlights, half of business decisions will be improved or automated by Artificial Intelligence (AI) agents; AI executive literacy will drive greater financial performance; and critical failures in synthetic data management will put AI governance, model accuracy, and compliance at risk.
“Almost everything today - from the way we work to how we make decisions - IS directly or indirectly influenced by AI. But it does not deliver value by itself & AI needs to be strongly aligned with data, AI says analytics and governance to enable smart and adaptive decisions and actions across the company”, he says Carlie Idoine's, 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 e Artificial Intelligence to create decision flows that support and automate complex judgments. AI agents enhance this process by addressing the complexity, analysis, and recovery of various data sources.Gartner recommends that Data & Analytics leaders work with business stakeholders to identify and prioritize decisions critical to company 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 should be used collectively with effective governance and risk management.Human decisions still require adequate knowledge as well as data literacy and Artificial Intelligence.”
By 2027, companies that emphasize AI literacy for executives will achieve a higher 20% financial performance compared to those that do not
To unlock the full business potential of Artificial Intelligence, it is necessary to develop the AI literacy of executives. They should be educated on the opportunities, risks and costs of Artificial Intelligence so that they can make effective and future-ready decisions about AI investments that accelerate organizational outcomes. Gartner recommends that D&A leaders introduce experiential enhancement programs for executives, such as developing domain-specific prototypes to make AI tangible.
By 2027, 60% of Data & Analytics leaders will face critical failures in synthetic data management, putting AI governance, model accuracy and compliance at risk
The use of synthetic data to train AI models is now a essential strategy to increase privacy and generate diverse datasets, however, the complexities arise from the need to ensure that synthetic data accurately represents real-world scenarios, scales effectively to meet growing data demand, and integrates seamlessly with data pipelines and existing data systems.
“To manage these risks, companies need effective” metadata management, says 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 moving into large-scale production will be built in-house, rather than deployed using off-the-shelf applications, to reduce cost and increase control
Creating models of Generative Artificial Intelligence (GenAI) internally provides flexibility, control and long-term value that many ready-made tools cannot match. As internal resources grow, Gartner recommends that companies adopt a clear framework for creative decisions versus purchase - This should take into account cost, time to market, available skill sets, integration capabilities, compliance, and risks.
By 2027, companies that prioritize semantics over 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 greater hallucinations, more tokens companies that rethink data management to focus on active metadata increase model accuracy and efficiency, have more data ready for AI and they reduce computing costs, according to Gartner, this allows AI agents to operate more effectively and facilitates smarter, faster decision-making across the enterprise.
By 2029, 10% of global boards of directors 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 governanceregulatory clarity and reputation management will intensify. Gartner recommends boards set the boundaries of Artificial Intelligence 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 customers 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 “ webinarThe Gartner Top Data & Analytics Predictions for 2025”.
