IDC & NTT DATA Webinar

All organisations are under pressure to drive value from their AI activities. After the scramble to adopt AI, and Generative AI in particular, organisations need to move from proof-of-concept to value realisation. Innovate quickly to drive value.

However, there is a tension in many organisations between security leadership and line of business, due to the balance between AI governance and innovation. Executives claim that security is stifling innovation, imposing strict guardrails around emerging AI use cases.

But AI introduces new risk factors that must be managed. There are the obvious phishing and deep fake examples, but there are numerous other AI-based threats that are now apparent: data and model poisoning, prompt injection and deep network reconnaissance are just a few of the identified threats. And of course, organisations need to be protected from themselves, stopping employees uploading sensitive data into open models and causing data breaches. Innovation is good, but it needs to be responsible.

Forward-thinking security leaders not only recognise the threat from AI, but also understand the need to leverage AI as a defensive tool. Otherwise, the asymmetry of AI adoption skews the delicate balance between cyber attack and defence. Basic AI can be used to correlated and automate actions, while GenAI can compile incident reports and even suggest resolutions. The emergence of agentic AI creates the promise of autonomous SecOps, upskilling SOC analysts and driving recruitment and retention of new talent.

Agentic AI also establishes the prospect of loss of control and visibility, as agents make and take decisions without human oversight, starting yet a new threat. And the cycle of balancing the good uses of AI with the bad continues.