Gartner: AI agents set to automate half of decisions by 2027

Gartner has released its latest predictions for data and analytics trends, outlining the key developments expected to shape business practices through 2025 and beyond.

According to Gartner, by 2027, half of all business decisions will be either augmented or automated by artificial intelligence (AI) agents. This projection comes alongside warnings about risks related to synthetic data and recommendations for improving executive AI literacy to drive better financial outcomes.

AI agents and decision intelligence

Gartner analysts predict that decision intelligence—which integrates data, analytics, and AI to assist or automate complex judgement—will see increasing adoption. By 2027, 50% of business decisions are expected to be supported by AI agents handling complex analysis and data retrieval. These developments are driven by the need for organisations to make faster and more informed decisions in a data-rich environment.

"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 organisation."

This statement from Carlie Idoine, Vice President Analyst at Gartner, places emphasis on the need for effective governance and the architecture surrounding the use of AI. Idoine added, "AI agents for decision intelligence aren't a panacea, nor are they infallible. They must be used collectively with effective governance and risk management. Human decisions still require proper knowledge, as well as data and AI literacy."

Executive AI literacy and financial performance

The report highlights a direct link between executive understanding of AI and an organisation's financial results. Gartner forecasts that, by 2027, organisations prioritising AI literacy among executives will see financial performance improve by 20% compared to those that do not. This is attributed to more strategic investments in AI and better management of opportunities and risks.

Gartner recommends that leaders introduce upskilling programmes for executives, suggesting activities such as developing domain-specific prototypes to make AI applications more tangible and actionable.

Synthetic data: Risks and management

As organisations use synthetic data to train AI models—often to enhance data privacy or expand datasets—Gartner flags potential risks related to governance, accuracy, and compliance. The firm predicts that 60% of data and analytics leaders will experience critical failures in synthetic data management by 2027.

Idoine said, "To manage these risks, organisations need effective metadata management. 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."

Build versus buy in GenAI

The report also looks ahead to the development of generative AI (GenAI) applications, predicting that by 2028, 30% of GenAI pilots transitioning to large-scale production will involve bespoke builds rather than off-the-shelf software solutions. This trend is attributed to the flexibility and control afforded by in-house development, though Gartner notes it is critical for organisations to assess costs, available skills, integration requirements, and regulatory factors before making a decision to build or buy.

Semantics and data readiness

Another area highlighted is the importance of semantics and metadata within AI-ready data. Poor semantics can lead to AI hallucinations, increase computational costs, and reduce model accuracy. Gartner expects that by 2027, companies focusing on semantics in their AI data will increase their GenAI model accuracy by up to 80% and potentially lower costs by up to 60%. This is seen as key to improving the efficiency and reliability of AI agents in business decision making.

AI in the boardroom

Looking further ahead, Gartner predicts that by 2029, 10% of global boards will employ AI advice to challenge executive decisions that are material to their businesses. The growing use of AI at board level will reinforce the need for robust data governance, clear regulatory policies, and reputation management. Boards are encouraged to set firm boundaries around AI involvement and define clear oversight and compliance frameworks to maintain strategic control.

Gartner clients have access to detailed predictions and recommendations on these trends, including guidance on the roles and responsibilities of Chief Data and Analytics Officers in ensuring AI delivers business value while managing emerging risks.