According to Presidio’s new report, AI adoption is advancing rapidly, with 80% of companies already integrating generative AI (GenAI) into their operations, yet a notable 50% admit to launching these initiatives without proper infrastructure, governance policies, or skill sets in place. The study unveiled the widespread enthusiasm for AI alongside critical readiness challenges and urgent concerns around data and security.

“While there’s undeniable momentum behind AI adoption, our findings show that some organizations are not fully prepared for the complexities involved. CIOs are eager to unlock AI’s potential but face critical challenges, particularly around data quality, security, and operational integration. Moving too quickly without the right infrastructure and skill sets can lead to costly setbacks,” said Rob Kim, Chief Technology Officer at Presidio.

AI has become a strategic priority for many organizations, with 96% of IT leaders identifying it as a critical competitive advantage. In fact, 71% report AI as their top investment area, and 90% of CIOs voice concerns over the complexity of AI integration. The concerns are especially prominent in financial services and healthcare sectors, where data sensitivity and regulatory requirements heighten the stakes.

Moreover, data barriers have proven to be a pervasive challenge, with 86% of respondents indicating data quality, availability, and insights issues. Among companies that have already launched GenAI, 84% faced problems in ensuring the integrity and accessibility of their data sources. This highlights an urgent need for better data infrastructure and management practices before AI systems can function optimally.

In addition, around 69% of respondents use AI as a security tool, yet many worry about its risks, especially concerning data privacy and regulatory compliance. As many as 37% of respondents rank data privacy and security as their top AI-related concerns, stressing the need for stringent internal controls and comprehensive employee training to mitigate risks.

The report also emphasises an adoption gap between the private and public sectors. GenAI adoption is high among private sector companies, with 85% reporting readiness, compared to just 62% in the public sector. The report shows that while the private sector forges ahead, government entities may require targeted support to bridge this gap and realize AI’s benefits.

Faced with these challenges, the report recommends a cautious approach: building a robust infrastructure, implementing rigorous governance, and launching small-scale AI projects before committing to larger-scale implementations.

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