AI has been transformational for the workplace, saving time on repetitive tasks and freeing skilled staff to focus on higher-value work. It has become so embedded in organisations that ISACA’s research recently found that 82% of European companies expressly permit the use of AI at work.

However, there is a difference between using AI and governing AI use safely. Only 42% of organisations have a formal AI policy in place, and one in five (20%) don’t know who would be accountable if an AI system caused harm.

To further complicate things, it turns out that Microsoft Copilot now sits inside 80% of organisations using AI at work, well ahead of ChatGPT (56%), Gemini (37%), and Claude (21%). That means the majority of companies using AI are depending on just one vendor as an executive assistant, IT support, and sounding board.

In practice, this means that most of the business world is leaning on a single AI provider, with little planning for what happens if that provider is compromised or experiences an outage.

We use AI professionally and personally so much that, for many organisations, it is easy for compliance to become an afterthought. A tool people rely on daily doesn’t feel like a security risk – even when it is.

Leadership needs to challenge this by asking: what happens if this tool goes down, and what happens if it’s compromised? Some analysts expect over 200 high-signal disruption days across AI platforms this year and the negative impact that this will have on organisations’ productivity is considerable. Once staff begin to rely on AI-generated first drafts and summaries, reverting to manual work isn’t impossible, but it isn’t frictionless.

An over-reliance on AI – particularly on individual AI tools – can create a false sense of security, and the AI governance gap only gets worse when things go wrong. Three-fifths (59%) of companies do not know how quickly their organisation could halt an AI system in the event of a security incident, and only a fifth (21%) said they could do so within half an hour.

When a tool people rely on every day goes down, staff don’t stop working – they improvise. More than a quarter (26%) of organisations use no risk framework for AI at all, so when something does go wrong, there’s often no process to fall back on. That often means turning to whatever other AI tool is at hand, personal accounts, unapproved apps, and work-arounds that nobody has checked, at exactly the moment when careful handling of data matters most. This is why the fallback plan must exist before it’s needed, rather than being invented on the fly. The outage isn’t really the risk – how people cope during the aftermath is.

EU regulators have recognised and begun to address the AI governance gap, formally naming major cloud and AI providers, including Microsoft, as critical services to finance under the Digital Operational Resilience Act (DORA). Other sectors should expect similar action in line with NIS2 and the UK Cyber Security and Resilience Bill as the concentration risk argument spreads beyond finance.

What can businesses actually do about the AI governance gap? Firstly, they should review their AI use and record which important day-to-day work depends on a single AI tool. Where possible, they should try to diversify their provider use in order to mitigate the knock on effect of an outage.

This should be done as early as possible, as swapping AI providers isn’t like switching a light-touch SaaS tool. Foundation model capability sits with a small number of providers, so diversifying means retraining workflows and testing outputs.

Businesses should then look at their continuity plan and consider what the next steps are should their AI tools suffer an outage. Every organisation using AI should have a designated team that is responsible for managing an AI outage. But assigning ownership alone isn’t enough. Organisations also need a structured, maturity-based approach that embeds governance, accountability and resilience into day-to-day AI operations. Frameworks such as CMMI AIM provide a practical way to assess current capabilities, identify gaps and improve governance over time. That is not a decision that should be made mid-crisis, but before anything happens.

A backup option is also essential for operations that can’t afford to be put on hold until the AI is operational. Staff should be made aware of this contingency plan so that if their usual AI tool is unavailable, they don’t reach for something less secure out of habit.

This kind of business foresight is what will prevent your most useful tool becoming your biggest cybersecurity oversight.

None of this is to say that businesses should not use AI – rather that AI should be treated like any other critical part of the business, with a plan for when things don’t go smoothly. A designated owner and a tested fallback plan won’t stop the next outage, but it will decide whether it’s a minor disruption or a major one.

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Keeper Security has urged schools, colleges and universities to strengthen their cyber defences ahead of the new academic year, warning that AI-powered phishing and a growing number of unmanaged machine identities are widening the education sector’s attack surface.

The identity security and privileged access management (PAM) provider said the annual rush to provision accounts, issue credentials and connect new devices creates a particularly attractive window for cybercriminals.

At the start of an academic year, IT teams can be responsible for onboarding thousands of students, faculty and staff while simultaneously enrolling devices and integrating third-party applications. Keeper warned that this combination can increase the likelihood of misconfigurations, stale credentials and excessive access going unnoticed.

Education institutions are already frequent targets for ransomware, credential theft and data breaches, in part because of the valuable information they hold, ranging from student and financial records to academic research.

Keeper said the threat is being compounded by relatively low levels of security awareness. Its research found that just 14% of schools mandate security awareness training, while almost one in five students and parents reported reusing passwords across personal and school accounts.

Artificial intelligence is adding another layer to the problem. AI-generated phishing messages can imitate communications from IT helpdesks, student funding departments and senior university figures with greater accuracy, potentially removing many of the spelling, grammar and formatting mistakes traditionally associated with phishing campaigns.

Deepfake technology also gives attackers the ability to impersonate trusted individuals through voice and video.

According to Keeper research, 52% of education leaders identify deepfake impersonation as a major concern, but only 26% are confident in their ability to recognise AI-enabled threats. The company also found that 41% of institutions reported being targeted by AI-generated phishing attempts or misinformation campaigns.

Beyond attacks targeting students and staff, Keeper highlighted what it describes as a less visible threat to education environments: non-human identities (NHIs).

These identities include service accounts used to synchronise student information and learning management systems, API keys connecting third-party EdTech applications, machine certificates authenticating connected equipment and cloud identities supporting automated workloads.

Increasingly, the category also includes AI agents and bots used for functions such as admissions, IT helpdesks and grading.

Keeper warned that credentials associated with these systems can be overlooked by conventional identity management practices. Service account passwords may remain unchanged for long periods, while API tokens belonging to applications that are no longer used can potentially remain active.

Cloud workloads can similarly accumulate permissions beyond those required for their function, while expired or incorrectly configured certificates can create additional security gaps.

Darren Guccione, CEO and co-founder of Keeper Security, said the education sector needed to broaden its approach to identity security.

“The conversation about education cybersecurity has historically focused on human accounts: students, teachers and administrators,” said Guccione. “But the real blind spot is the vast ecosystem of machine identities that power modern EdTech. Back-to-school is the right moment for education IT teams to take stock of every identity on their network, human and non-human alike.”

Keeper is recommending that education IT teams use the period before students return to review both human and machine access to their environments.

Among its recommendations is enforcing multi-factor authentication (MFA) across student, faculty and staff accounts, alongside deploying enterprise password management to reduce weak, reused and shared credentials.

Institutions should also audit privileged access and remove permissions associated with former employees, expired service accounts and applications that are no longer required, the company said.

For non-human identities, Keeper recommends creating an inventory covering service accounts, API keys, machine certificates, cloud identities and AI agents. Credential rotation policies should then be established, particularly for third-party EdTech integrations and AI systems introduced for the coming academic year.

The company also advised institutions to update phishing awareness programmes to account for increasingly convincing AI-generated communications.

Keeper said its zero-trust and zero-knowledge security platform can be used to discover, govern and rotate credentials belonging to both human and non-human identities. Its KeeperPAM platform additionally provides privileged access controls, session recording and audit capabilities.

As education environments become increasingly dependent on cloud services, connected equipment, third-party applications and AI, Keeper argues that knowing which identities have access (and whether they still require it) is becoming as important as protecting the students and staff behind traditional user accounts.

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