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New research uncovers the main challenges faced by security in implementing AI – and offers two possible solutions

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A recent survey conducted among security leaders has shed light on the stark contrast between the expectations and realities surrounding artificial intelligence (AI). While there is a high level of enthusiasm for the potential of AI, many teams are facing significant challenges when it comes to implementing AI effectively, demonstrating return on investment (ROI), and achieving tangible business impact.

The survey, sponsored by Tines and AWS and featured in IDC’s Voice of Security 2025 white paper, gathered data from over 900 security leaders in the US, Europe, and Australia. The initial findings from the survey show that security leaders are largely embracing AI, with 99% of teams incorporating AI into their operations. Additionally, 78% of leaders expressed confidence in their ability to manage the changes that AI implementation may bring to their roles.

Despite this positive sentiment, the data also revealed several concerns regarding AI, including frustration with the slow pace of adoption. A deeper analysis of the survey data suggests that these adoption challenges may be hindering teams from exploring more impactful applications of AI. While AI adoption is widespread, many leaders struggle to fully realize the potential benefits of AI for their organizations.

The white paper by IDC highlights that most security leaders view AI as a force multiplier, anticipating future benefits such as increased business efficiency, improved customer experience, and greater competitive advantage. However, in the present, these teams are faced with significant barriers to AI adoption, including concerns about training capacity, compliance, AI hallucinations, secure adoption, and slow implementation.

Further examination of the survey data suggests two potential solutions to help teams unlock the full potential of AI. The first solution involves shifting towards AI use cases that support critical decision-making. While current AI use cases primarily focus on data manipulation, such as summarization, threat intelligence analysis, and threat detection, more mature AI programs delve into risk assessments, attack surface management, and advanced triage. Progressing from short-term efficiency gains towards transformative applications is essential for achieving lasting business impact.

The second solution involves adopting a flexible and holistic approach to AI. This approach entails integrating AI with workflow orchestration, investing in skills development, creating an adaptive AI strategy, and implementing robust security and privacy measures. By addressing these challenges and embracing a comprehensive AI strategy, security teams can prepare for more sophisticated AI applications as technology continues to evolve.

In conclusion, a flexible and security-focused AI strategy can help security leaders navigate adoption complexities, overcome current challenges, and pave the way for impactful AI use cases. As AI matures, the potential for security applications will only continue to grow. By effectively managing concerns and leveraging the right tools and processes, security teams can build trust in AI and ultimately realize the promised ROI of artificial intelligence in the field of cybersecurity.

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