The Role of AI in Corporate Governance and Decision-Making
Artificial intelligence will shift from being a complementary tool to becoming a decisive agent in corporate governance, strategic decision-making, and operational efficiency. This is the assertion made by Gartner in their latest report presented during the Data & Analytics Summit held in Sydney, where analysts from the firm outlined the key predictions for the period 2025-2029 regarding data, analytics, and artificial intelligence.
Among the most compelling forecasts is that by 2027, 50% of business decisions will be augmented or directly automated by artificial intelligence agents. This new approach, termed “decision intelligence,” combines data, analytics, and AI to create more efficient decision flows that assist humans or even operate independently in defined contexts.
“AI does not provide value on its own. It needs to be closely aligned with data, analytics, and governance to enable intelligent and adaptive decisions across the organization,” explained Carlie Idoine, Vice President and Analyst at Gartner.
AI Literacy: Key to Financial Performance
Another significant takeaway from the report indicates that organizations investing in AI training for their executives will achieve, on average, 20% better financial performance than those that do not. This forecast emphasizes the necessity for business leaders to not only delegate to their technical teams but also acquire key insights about the risks, opportunities, and costs associated with AI.
In this regard, Gartner recommends implementing executive training programs that include the development of sector-specific prototypes, allowing executives to tangibly understand the potential and limitations of AI.
Emerging Risks: Mismanagement of Synthetic Data
While AI offers an undeniable competitive advantage, Gartner warns of increasing risks associated with the use of synthetic data to train models. According to their forecasts, 60% of data and analytics leaders will face critical failures in managing synthetic data by 2027. This jeopardizes not only the accuracy of AI models but also their governance and regulatory compliance.
Analysts recommend strengthening metadata management to provide context, traceability, and verification mechanisms, which are essential for ensuring the quality and validity of artificially generated data.
Building Tailored AI: More Control, Less Dependence
Another growing trend identified by Gartner is the development of customized generative AI (GenAI) solutions instead of purchasing packaged applications. By 2028, 30% of GenAI projects that scale to production will be built internally, allowing organizations to reduce costs and increase control over the solution.
This option gains traction as organizations mature in their internal capabilities and better assess critical factors when deciding between building or buying: development time, internal skills, integration, compliance, and risk.
Semantics and Accuracy: A Crucial Pair for GenAI
The semantic quality of data will be a determining factor in improving the accuracy and reducing the cost of generative models. According to Gartner, prioritizing semantics in “AI-ready” data can enhance accuracy by up to 80% and lower operational costs by 60%. This measure will help reduce the “hallucinations” of models, decrease token consumption, and improve computational resource efficiency.
AI on Corporate Boards
Finally, the firm forecasts a structural shift in business governance: by 2029, 10% of global boards will use artificial intelligence to question executive decisions of material impact. This perspective necessitates defining clear boundaries regarding the role of AI in strategic oversight, as well as robust policies around accountability, transparency, and regulatory compliance.
Conclusion
Gartner’s predictions underscore that artificial intelligence is not just a technological tool but a transformative force that will redefine decision-making structures, organizational performance, and corporate accountability. The key to capitalizing on its potential lies in careful integration with data, people, and processes, accompanied by solid governance and appropriate executive literacy.
Companies that embrace this evolution with critical insight and strategy will be the ones to lead in the new digital landscape.
Source: Gartner