Gartner: AI Agents Will Drive Half of Decisions by 2027
Gartner has released its data and analytics predictions for 2025 and beyond, forecasting that AI agents will augment or automate 50% of business decisions by 2027. The research firm also warns that 60% of data and analytics leaders will encounter failures in managing synthetic data within the same timeframe.
The predictions emerge as organisations grapple with integrating AI across decision-making processes whilst managing governance and compliance requirements. Carlie Idoine, VP Analyst at Gartner, says the technology requires careful alignment with existing data and analytics frameworks.
“Nearly everything today – from the way we work to how we make decisions – is directly or indirectly influenced by AI,” says Carlie. “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.”
The research identifies six predictions that Gartner expects will shape organisational planning over the next two to three years. These span executive education, synthetic data management and the balance between building versus buying generative AI solutions.
Gartner forecasts executive AI literacy will drive financial performance
Executive education emerges as a performance differentiator in Gartner’s analysis. The firm predicts that organisations prioritising AI literacy for executives will achieve 20% higher financial performance compared with those that do not by 2027.
This performance gap reflects the need for senior leadership to understand AI opportunities, risks and costs when making investment decisions. Gartner recommends that data and analytics leaders introduce experiential programmes for executives, including the development of domain-specific prototypes to demonstrate AI capabilities.
The approach aims to bridge the knowledge gap between technical teams implementing AI solutions and executives approving budgets and strategic direction. Without this literacy, organisations risk misallocating resources or failing to capitalise on AI opportunities that could accelerate business outcomes.
Decision intelligence, which combines data, analytics and AI to create automated decision flows, represents one area where executive understanding proves critical. AI agents enhance this process by managing the complexity and analysis of multiple data sources, but require governance frameworks that executives must approve and oversee.
“AI agents for decision intelligence aren’t a panacea, nor are they infallible,” says Carlie. “They must be used collectively with effective governance and risk management. Human decisions still require proper knowledge, as well as data and AI literacy.”
Synthetic data management presents governance and compliance risks
Synthetic data usage emerges as both an opportunity and a risk in Gartner’s predictions. The firm forecasts that 60% of data and analytics leaders will face failures in managing synthetic data by 2027, potentially compromising AI governance, model accuracy and regulatory compliance.
Organisations increasingly turn to synthetic data to train AI models whilst enhancing privacy protection and generating diverse datasets. However, the complexity of ensuring synthetic data accurately represents real-world scenarios creates implementation challenges.
The scaling requirements to meet growing data demand compound these difficulties, alongside the need to integrate synthetic data with existing pipelines and systems. Gartner identifies metadata management as essential for addressing these risks.
“To manage these risks, organisations need effective metadata management,” says Carlie. “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 decisions reshape generative AI implementation strategies
The maturation of organisational AI capabilities influences deployment strategies, according to Gartner’s research. The firm predicts that 30% of generative AI pilots advancing to large-scale production will involve building solutions internally rather than deploying packaged applications by 2028.
Nearly everything today – from the way we work to how we make decisions – is directly or indirectly influenced by AI
Gartner’s predictions extend to board-level governance, forecasting that 10% of global boards will use AI guidance to challenge executive decisions that materially affect their business by 2029.
“As AI becomes embedded in board-level strategy, the need for strong data governance, regulatory clarity and reputation management will intensify,” says Carlie.
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