A shift is underway in cybersecurity: machine-to-machine interactions now rival human digital activity within organisations. From AI agents to automated scripts and APIs, these non-human entities operate at speed and scale, handling sensitive tasks across IT environments. In the UK, cybersecurity leaders are increasingly focused on this new, quickly expanding attack surface – machine identities. Their rapid growth, coupled with high-level access, makes them an emerging priority in threat mitigation strategies.
While human identities remain a target, machine identities are often granted broader access, introducing substantial risk if mismanaged. A compromised API key or service account can allow attackers to escalate privileges or move laterally across networks. Recent findings show 88% of cybersecurity leaders in the UK believe machine identities will be the next major target for cyberattacks. Alarmingly, over half of these organisations have already experienced security incidents tied to machine credentials.
Traditional tools can’t keep up: enter AI
Traditional Identity and Access Management (IAM) tools are not always equipped to handle the scale or complexity of machine identity governance. Manual monitoring is no longer sustainable, particularly as multi-cloud environments and hybrid working complicate visibility. As a result, even well-intentioned security teams may be leaving doors wide open to sophisticated attackers.
Artificial Intelligence (AI) offers a much-needed solution. With the ability to analyse large volumes of behavioural data in real time, AI enables organisations to detect abnormal patterns and respond to threats faster. Whether it’s flagging a suspicious API call or identifying privilege misuse, AI can shorten response times significantly.
But AI is not without its challenges. This highlights the importance of not only deploying AI but governing it effectively. Without robust oversight, AI might introduce blind spots instead of eliminating them. As organisations introduce more automation, the attack surface expands – making it vital to close security gaps before they’re exploited. Used correctly, however, it remains one of the most promising tools in combating identity-related threats. AI-enhanced IAM tools are not just a convenience; they’re becoming a business necessity.
The shifting cybersecurity landscape
Identity-related breaches remain among the most common vectors for attack, contributing to 25% of data breaches globally in 2024. It’s no surprise then that a significant portion of cybersecurity investment is being channelled into identity security, with 78% of organisations planning to increase spending in 2025. This investment reflects the evolving perception of identity as a strategic enabler, not just a compliance checkbox – especially as the volume of machine identities increases
Another trend gaining momentum is IAM consolidation. A full 88% of businesses are now considering reducing the number of identity vendors they use in favour of centralised platforms. Fewer vendors mean tighter controls, unified policies, simpler audits, and faster incident response. As machine identities multiply, these benefits become even more essential.
These shifts are part of a broader reimagining of cybersecurity’s role. What was once seen as a technical function is now integral to business resilience and trust. Customers, regulators, and investors all expect demonstrable proof that security is being taken seriously – especially in light of stricter UK data protection oversight from bodies like the Information Commissioner’s Office (ICO). Organisations that fail to keep pace with identity threats risk more than operational disruption – they risk reputational damage and financial penalties.
The path forward: secure every identity, human or machine
Looking forward, securing machine identities will define the next era of cybersecurity. These credentials, often overlooked, are integral to modern business operations and must be treated with the same rigour as human users. The complexity of today’s digital environments demands automation, intelligence, and integration. With AI at the core, organisations have an opportunity to transform identity from a vulnerability into a competitive advantage.
As we near the halfway mark of 2025, identity must be at the core of every business’s security strategy. From cloud-native applications to legacy systems, every component of the digital enterprise depends on trust.
Establishing that trust requires securing not only who is accessing systems – but what. In this landscape, machine identity security isn’t just emerging; it’s essential.
