▼ Summary
– 73% of IT leaders believe reducing information complexity is essential for AI readiness and a strong security posture, with unstructured data being a major contributor.
– A Ponemon Institute survey found that most organizations lack the information readiness to deploy AI securely, despite it being a high priority for 57% of respondents.
– Budget constraints are the top governance challenge, with 31% citing insufficient funds for AI technologies, followed by time constraints and lack of alignment or skilled personnel.
– Generative AI is gaining adoption, with a third of organizations already using it and 26% planning to within six months, primarily for security, productivity, and development.
– Best practices for AI readiness include protecting sensitive data, implementing responsible AI practices like governance and bias checks, and strengthening encryption throughout the AI lifecycle.
Businesses everywhere are racing to harness the power of artificial intelligence, yet many are hitting a major roadblock: their own data. A recent survey highlights that while enthusiasm for AI is high, a lack of trusted, well-governed information is holding back meaningful progress. Without a solid data foundation, even the most advanced AI systems can’t deliver reliable or secure outcomes.
When asked who holds final responsibility for AI strategy within their organizations, a significant number of IT leaders pointed to the C-suite. Still, alignment remains a challenge. Nearly three-quarters of CIOs and CISOs agree that cutting through information complexity is essential to preparing for AI integration. As one industry expert noted, AI’s potential can only be realized when built on a framework of clean, secure, and well-managed data.
Complexity isn’t just a technical issue, it’s a security liability. Unstructured data, in particular, adds layers of difficulty, with 73% of respondents identifying simplification as vital for maintaining a strong security posture. Less than half feel highly confident in their ability to measure return on investment when it comes to securing information assets, underscoring the uncertainty many are facing.
Despite widespread optimism about AI’s value, readiness levels remain concerningly low. More than half of organizations consider AI adoption a top priority, and a similar percentage believe they can demonstrate ROI. Yet many admit they struggle to mitigate security and legal risks tied to AI implementation.
Budget constraints are the most frequently cited governance challenge, mentioned by nearly a third of those surveyed. Other hurdles include lack of time for integration, misalignment between IT and security teams, and difficulty recruiting AI-skilled personnel.
Generative AI is gaining momentum, with a third of organizations already using it and more than a quarter planning to adopt it within six months. Common applications include improving security operations, boosting employee productivity, and accelerating software development. In contrast, agentic AI has seen slower uptake, with less than a quarter of organizations currently using it and only 16% planning near-term adoption.
For those looking to strengthen their AI readiness, several best practices have emerged. Protecting sensitive data begins with knowing where it lives, who can access it, and how it’s being used. Implementing strong access controls, classification policies, and anomaly detection can significantly reduce exposure.
Responsible AI adoption requires a comprehensive approach. This includes cleansing and governing data, validating inputs and outputs, training employees, and regularly checking for model bias. Encryption also plays a critical role, data should be protected not only at rest and in transit, but also during AI processing to ensure end-to-end security.
(Source: HelpNet Security)
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