THEGartner, Incannounced the main forecasts ofData & 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 literacy in AI will drive greater financial performance; and critical failures in synthetic data management will jeopardize AI governance, model accuracy, and compliance.
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 on its own – Artificial Intelligence needs to be strongly aligned with data.analyticsand governance to enable smart and adaptive decisions and actions throughout the company," saysCarlie IdoineVice 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 combinesdata,analyticsand 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 critical decisions for the company's success and those that can benefit from more effective application ofanalyticsand 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 literacy.
By 2027, companies that emphasize AI literacy for executives will achieve 20% higher financial performance compared to those that do not.
To unlock the full business potential of Artificial Intelligence, it is necessary to develop executives' AI literacy. They should be informed about the opportunities, risks, and costs of Artificial Intelligence so that they can make effective and future-ready decisions regarding AI investments that accelerate organizational results. Gartner recommends that D&A leaders introduce experimental 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 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 aessential strategyto increase privacy and generate diverse datasets. However, the complexities arise from the need to ensure that synthetic data accurately represent real-world scenarios, are scaled effectively to meet the growing demand for data, and integrate seamlessly withpipelinesand existing data systems.
"To manage these risks, companies need effective metadata management," says Idoine. Metadata provides the context, lineage, and governance necessary to track, verify, and responsibly manage synthetic data, which is essential for maintaining AI accuracy and meeting compliance standards.
By 2028, 30% of GenAI pilots that advance to large-scale production will be developed internally rather than implemented using off-the-shelf applications, to reduce costs and increase control.
The creation of models ofGenerative Artificial Intelligence(GenAI) internally offers flexibility, control, and long-term value that many ready-made tools cannot match. As internal resources increase, Gartner recommends that companies adopt a clear framework for creation decisions.versuspurchase. She should consider the 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 leads to more hallucinations, moretokensnecessary and higher costs. Companies that rethink data management to focus on active metadata increase model accuracy and efficiency, have moreready data for AIand reduce computing costs. According to Gartner, this enables AI agents to operate more effectively and facilitates smarter and faster decision-making across the company.
By 2029, 10% of global boards of directors will use AI guidance to challenge executive decisions that are important to their businesses.
As AI is incorporated into the board's strategy, the need for a strongdata governanceregulatory clarity and reputation management will intensify. Gartner recommends that boards define the boundaries of Artificial Intelligence 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 at "Predictions for 2025: AI-Powered Analytics Will Revolutionize Decision MakingandPrevisões para 2025: CDAOs Devem Abraçar Seu Papel na IA ou Risco de Perda de Credibilidade”.Additional information is available in the free Gartner webinar.The Gartner Top Data & Analytics Predictions for 2025”.
