Gartner: Half of business decisions to be automated by AI by 2027

Gartner has predicted that half of business decisions will be augmented or automated by AI agents decision intelligenceby 2027.

Decision intelligence combines data, analytics and AI to create decision flows that support and automate complex judgements.

Gartner said that AI agents will enhance this process by handling the complexity, analysis and retrieval of various data sources, with the research and advisory firm recommending data and analytics (D&A) leaders work with business stakeholders to identify and prioritise decisions critical to the success of the organisation, and those that can benefit from more effective application of analytics and AI.

During the Gartner Data & Analytics Summit in Sydney, Carlie Idoine, VP analyst at Gartner, said 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," she said.

“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.”

By 2027, Gartner also predicted that organisations that emphasise AI literacy for executives will achieve 20% higher financial performance compared with those that do not.

Gartner recommended D&A leaders to introduce experiential upskilling programs for executives, such as developing domain-specific prototypes to make AI tangible, which the firm said will lead to greater and more appropriate investment in AI capabilities.

Also by 2027, Gartner predicted that 60% of data and analytics leaders will face critical failures in managing synthetic data, risking AI governance, model accuracy, and compliance.

“To manage these risks, organisations need effective metadata management,” said 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.”

Close to a third (30%) of GenAI pilots that move forward into large scale production will be built versus deployed using packaged applications by 2028, Gartner predicted.

As internal capabilities grow, Gartner recommends organisations adopt a clear framework for build versus buy decisions, factoring in cost, time to market, available skillsets, integration capabilities, compliance and risk.

By 2027, Gartner said that organisations that prioritise semantics in AI-ready data will increase their GenAI model accuracy by up to 80% and reduce costs by up to 60%.

The company said that poor semantics in GenAI lead to greater hallucinations, more tokens required and higher costs, but organisations that rethink data management to focus on active metadata drive greater model accuracy and efficiency, have higher AI data readiness and reduce compute costs.

According to Gartner, this enables AI agents to operate more effectively and facilitates smarter, faster decision making across the organisation.