By 2030, more than 401,300 organizations will experience security or compliance incidents related to unauthorized shadow AI.
O Gartner, Inc.., a business insights and technology company, identifies critical blind spots stemming from overlooked risks and unintended consequences of adopting Generative Artificial Intelligence (GenAI). You Chief Information Officers CIOs must proactively address these hidden challenges to ensure the generation of GenAI value and avoid failures in AI projects.
“"GenAI technologies and techniques are evolving at an unprecedented pace, matched only by the hype surrounding them, which makes it challenging for CIOs to navigate this dynamic landscape," he says. Arun Chandrasekaran, Vice President and Emeritus Analyst at Gartner.
Although organizations often focus on the immediate challenges of GenAI, such as business value, safety and data readiness, they can overlook critical blind spots, as these are second- or third-order effects that are often not initially visible. Risks such as shadow AI, Technical debt, skills erosion, data sovereignty demands, interoperability issues, and vendor lock-in represent hidden risks that can undermine long-term success.
Gartner predicts that, by 2030, these blind spots will create a dividing line between companies that... They scale the use of Artificial Intelligence (AI) in a safe way. Strategic and those that become stuck, outdated, or internally destabilized.
To remain competitive and resilient, CIOs must address the visible challenges and hidden risks associated with GenAI adoption and prioritize resolving the following blind spots:
Explosion of Shadow AI
A Gartner survey of 302 cybersecurity leaders, conducted between March and May 2025, revealed that 691,300 of organizations suspect or have evidence that their employees are using prohibited public GenAI.
The rapid adoption of unauthorized AI tools can lead to visible and invisible impacts, such as loss of intellectual property, data exposure, and increased security risks. Gartner predicts that by 2030, more than 401% of organizations will experience security or compliance incidents related to AI. shadow AI unauthorized.
“To address these risks, CIOs must define Clear policies for the use of AI tools. throughout the company, conduct regular audits of activities shadow AI "And incorporate GenAI's risk assessment into their Software as a Service (SaaS) assessment processes," says Chandrasekaran.
AI technical debt
Gartner predicts that, by 2030, 50% of organizations will face delays in AI upgrades and/or increased maintenance costs due to unmanaged GenAI technical debt.
“Companies are excited about GenAI’s speed of delivery. However, the punishingly high cost of maintaining, fixing, or replacing AI-generated artifacts, such as code, content, and design, can erode the return on investment promised by GenAI,” says Chandrasekaran. “By establishing clear standards for reviewing and documenting AI-generated assets and tracking technical debt metrics on IT dashboards, companies can take proactive steps to avoid costly disruptions.”
Increased demand for data sovereignty and AI.
Gartner predicts that, by 2028, 65% governments worldwide will introduce some technological sovereignty requirements to improve independence and protect against extraterritorial regulatory interference.
Regulatory restrictions on cross-border data sharing Other models can delay enterprise-wide AI implementations, increase total cost of ownership (TCO), and generate suboptimal results.
To address these challenges, CIOs must incorporate data sovereignty into their AI strategies from the outset, involving legal and compliance teams from the beginning and prioritizing vendors that meet their data sovereignty and AI requirements.
Skills erosion
Over-reliance on AI can erode critical human expertise, judgment, and tacit knowledge that are not easily codified or replaceable. This erosion occurs gradually and often goes unnoticed, so CIOs may not recognize the risk until the organization struggles to function without AI or when AI fails in extreme cases requiring human intuition.
“To avoid the gradual loss of business memory and capacity, organizations must identify where human judgment and skill are essential, designing AI solutions to complement, not replace, those skills,” says Chandrasekaran.
Ecosystem dependency and interoperability
Organizations eager to leverage the potential of GenAI at scale often choose a single vendor for the sake of speed and simplicity. This deep dependence can affect the company's technical agility and its future negotiating power regarding pricing, terms, or service levels.
Many CIOs underestimate how much their data, models, or workflows are tied to APIs, data lakes, and specific vendor platform tools.
“Prioritizing open standards, open APIs, and modular architectures in AI stack design helps companies avoid vendor lock-in,” says Chandrasekaran. “Furthermore, CIOs should make interoperability a standard in GenAI pilots and evaluations.”
Gartner customers can read more at “Generative AI's Invisible Undercurrents: 10 Blind Spots CIOs Aren't Watching but Should”.
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