t cht lk increasingly paramount . Expanding AI usage requires robust , secure solutions , which will drive demand for startups and consultancies specialising in AI security to help organisations safeguard against data breaches and comply with privacy regulations . hole targets – compromise one frontier model , and the impact cascades across multiple agencies . We are building a monoculture of AI systems connected by unmanaged APIs , while simultaneously reducing oversight and governance .
t cht lk increasingly paramount . Expanding AI usage requires robust , secure solutions , which will drive demand for startups and consultancies specialising in AI security to help organisations safeguard against data breaches and comply with privacy regulations . hole targets – compromise one frontier model , and the impact cascades across multiple agencies . We are building a monoculture of AI systems connected by unmanaged APIs , while simultaneously reducing oversight and governance .
Prioritising stringent data security protocols is crucial not only for stakeholder confidence but also for meeting evolving regulatory standards . By embedding security into AI strategies , companies can protect valuable data assets while safely scaling their AI capabilities across various functions .
Focusing on data security will help organisations manage risks , ensuring trust and compliance as AI continues to reshape operations .
Chuck Herrin , Field CISO , F5
A world of AI is a world of APIs , with 50 % APIs unmonitored and unmanaged
We are seeing a confluence of three dangerous trends : the centralisation of risk in relation to key AI platforms , the proliferation of unmanaged APIs connecting these systems , and a reduction in human oversight precisely when it is needed the most . This creates both technical vulnerability and institutional brittleness .
Looking ahead to next year , we will continue in a global AI race condition , where everyone from small businesses to nation states are adopting AI at breakneck speed because if we do not , they will , and every organisation has they to worry about .
However , the AI race condition is not just about adoption speed . It is creating a dangerous feedback loop where the pressure to deploy AI faster makes us more dependent on it to manage the complexity we are creating . I expect to see a push for government efficiency through rapid AI adoption , which is likely to create significant security vulnerabilities .
In many ways , we are seeing a dangerous parallel to the rushed cloud adoption of the early 2010s , but with higher stakes . Organisations need to focus on AI architecture and defence in depth , with API security as a critical control point . Every AI interaction happens through APIs , making them both the enabler and the potential Achilles ’ heel of this transformation .
Organisations today are woefully unaware of their API ecosystem and attack surface , and I often say , a world of AI is a world of APIs . APIs are how AI models are trained , used , and attacked , and our estimates are that roughly 50 % of APIs are unmonitored and unmanaged .
Budget cuts and efficiency mandates will accelerate the push of agencies toward shadow AI solutions , inadvertently centralising vulnerabilities around a handful of AI vendors . This creates perfect watering
Supply chain nationalism is not just about reshoring – it is forcing a fundamental rethinking of digital architecture . As geopolitical tensions rise and new tariffs may take effect , organisations caught between
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