At a glance
- AI is increasing the speed, scale, and complexity of cyber risk.
- Continuous exposure management can help organizations prioritize what matters most.
- Strong identity, data governance, and human oversight are foundational to cyber resilience.
The future belongs to organizations that can anticipate, adapt, and act as cyber risk evolves—while keeping people firmly in control of consequential decisions.
The pace of cyber risk is challenging how organizations have traditionally approached cybersecurity. Technology can be deployed faster, threats can scale quickly, and the time available to understand and respond to exposure is shrinking.
Cybersecurity has become a speed problem, not a skill problem. The challenge is not simply keeping up with new threats. The cyber operating model itself needs to evolve. Cyber teams need to accelerate decision-making and become more closely integrated with business transformation, helping organizations consider security as new technologies and capabilities are introduced.
The traditional boundaries organizations once relied on to protect their environments are also becoming harder to define. The perimeter has not disappeared. It has multiplied. Cloud platforms, connected ecosystems, third parties, and AI are expanding the number of identities, applications, service accounts, and AI agents that can interact with organizational data.
How is AI changing cybersecurity risk?
AI is creating new governance challenges while also increasing the speed and scale at which cyber threats can develop.
AI adoption can introduce risk when organizations lack visibility and appropriate controls. As employees and business teams gain easier access to AI tools, organizations may have limited visibility into how those tools are being used, what information they can access, and whether appropriate governance and access controls are in place.
How organizations navigate these risks will depend partly on their operating environment. For credit unions and pension organizations, for example, modernization and AI adoption may need to progress alongside a strong focus on risk, safety, and trust.
At the same time, threat actors are using AI and automation to operate with greater speed and at greater scale. Activities that once required significant time, research, and technical capability can increasingly be accelerated. AI tools, for example, may help threat actors identify vulnerabilities, assess potential attack paths, and accelerate parts of exploit development.
AI-enabled capabilities can also support cyber teams by enriching alerts, prioritizing exposure, identifying suspicious activity, and automating defined actions where appropriate. AI can provide the speed and scale cyber teams need while keeping people responsible for decisions where judgment, business context, and accountability matter.
Why are identity and data foundational to cyber resilience?
Identity and data are becoming increasingly important to cyber resilience because people, service accounts, application programming interfaces (APIs), and AI agents can all access and act on organizational information.
As AI agents interact with applications and data, organizations need to think differently about identity. Human users are no longer the only identities accessing organizational information. Service accounts, APIs, and AI agents can also hold privileges and act across interconnected systems.
An AI agent, for example, may operate using the access privileges available to the person or system using it. If those privileges are broader than necessary, the resulting exposure may also increase.
As human and machine identities proliferate, gaps in traditional identity and access management can become more consequential. The fundamentals therefore matter even more:
- What data does the organization have?
- How sensitive is it?
- Who or what can access it?
- Is that access necessary?
Exposure can also be underestimated by organizations that do not consider themselves likely cyber targets. Smaller, family-owned automotive dealership groups, for example, may assume their size makes them less attractive to threat actors.
Yet cyber risk does not always take the form of a major system outage. Invoice payment fraud, for example, can result in direct financial losses without disrupting systems or customer operations.
Rethinking cybersecurity risk management
Traditional cyber programs have often measured activity: how many vulnerabilities were identified, how quickly they were patched, how many alerts were reviewed, or whether required assessments were completed.
These measures remain useful, but they do not necessarily show an organization's level of exposure.
From vulnerability management to exposure management
A critical vulnerability that an attacker cannot reach may pose less immediate risk than several lower-rated vulnerabilities that can be combined into an attack path.
Exposure management adds context by helping organizations understand which vulnerabilities are accessible and exploitable, what they could put at risk, and where action may need to be prioritized.
This evolution from periodic assessment toward perpetual defence requires a more continuous view of cybersecurity risk. Rather than relying primarily on point-in-time assessments, organizations can assess how their exposure changes as technologies, identities, vulnerabilities, and threats evolve.
The same thinking can change the conversation with leadership. Instead of focusing primarily on activity, cyber teams can provide greater visibility into what is exposed, what is changing, how quickly threats can be contained, and how prepared the organization is to recover.
AI-enabled threat detection and response
Cyber operations can become more responsive with capabilities such as security copilots, automated threat hunting, AI-enabled threat detection, and automated playbooks. These tools can help teams process large volumes of activity and surface what requires attention.
Where there is a high degree of confidence in a threat, an automated response may also be appropriate within defined controls. For example, an account showing several strong indicators of compromise could be blocked automatically to limit an attacker's opportunity to move through the environment.
As AI supports more of the speed and scale required for detection and response, human oversight remains essential. The appropriate level of automation should reflect both confidence in the threat and the potential business impact of the response.
The goal is to move faster and govern smarter, creating a cyber function that can respond at greater speed while keeping people at the centre of consequential decisions.
What can organizations do to strengthen cyber resilience?
To strengthen cyber resilience, organizations can focus on five areas:
Cyber resilience is not about eliminating every incident. It is about helping the organization make informed decisions sooner, absorb disruption, recover effectively, and maintain trust.
Start with what matters most. Move with urgency. Govern with evidence. Build the confidence to advance.
Build a cyber strategy that keeps pace
Building cyber resilience starts with understanding where your organization is most exposed and which capabilities need to evolve.
Our Cybersecurity team can help organizations support secure AI adoption, advance exposure management, and develop more responsive cyber operations. We work across cyber strategy and governance, incident readiness, threat management, cloud security, and related capabilities to identify practical next steps aligned with business priorities and transformation plans.