Artificial intelligence is rapidly changing the threat landscape. It is making attacks faster to develop, easier to scale and harder to distinguish from legitimate activity.
For small and medium-sized businesses, this matters because the pace of change is accelerating faster than many can strengthen the governance, visibility and operational discipline needed to keep up.
That’s what we explore in this article, as follows:
AI means increased cyber security spending
Recent IDC research commissioned by Sage, SMBs in the age of AI: Navigating cyber complexity and building resilience, shows that 60% of small and medium-sized businesses expect to increase cyber security spending.
The issue is not a lack of awareness or intent. It is the widening gap between good intent and the ability to manage a more complex threat environment consistently.
AI does not need to create an entirely new category of attack to shift the balance.
Its immediate impact is to make familiar threats more efficient.
Vulnerability discovery and exploitation can happen at greater speed and scale. Phishing can become more convincing. Impersonation can become more realistic.
The same technology also offers defenders clear benefits.
AI can support code review, vulnerability discovery, threat analysis and remediation.
The advantage will not come from access to AI alone. It will come from the ability to use it safely, apply human judgement and translate insight into action quickly.
How the maturity gap is becoming operational
Many businesses already have essential controls in place, including email protection, patching, backups, endpoint security and multifactor authentication.
Those foundations remain critical.
The challenge is that cyber resilience increasingly depends on what happens beyond those foundations.
The research found that 44% of businesses surveyed cite a lack of internal expertise or time as a major challenge. That suggests the problem is no longer simply about having the right tools. It’s about having the capacity, visibility, and processes to use them effectively.
Effective security is ultimately an operational discipline and depends on clear ownership, current knowledge of systems and data, regular testing, informed prioritisation and the ability to respond when something changes.
Why risk prioritisation is critical
A growing volume of vulnerabilities does not mean every issue presents the same risk.
In practice, context matters. A weakness in an isolated, low-value system may create limited immediate exposure.
A lower-severity issue affecting an internet-facing service, critical workflow or sensitive dataset may require much faster action.
Several relatively minor weaknesses can also become more serious when combined.
Businesses need to understand which systems are exposed, which data matters most, how easily a weakness could be exploited and what the operational impact would be.
AI can help surface and analyse that information more quickly. What it cannot do is determine which services matter most to the business or what level of disruption the organisation can tolerate or which risks leaders should accept. Those remain human decisions.
As attackers and software providers operate at greater speed, businesses will also need to review their exposure more frequently.
This does not require every business to adopt continuous security testing overnight. It means shortening review cycles progressively, starting with the systems, suppliers and data that would create the greatest business impact if compromised.
How to fix cyber security for businesses
The answer is not for every business to recreate the security capability of a global enterprise. For most businesses that would be unrealistic and, in many cases, unnecessary.
Where internal capacity is limited, businesses can bring in specialist support through managed security providers, external advisers and trusted technology partners. In some cases, seeking external expertise is more effective than leaving known risks unaddressed because smaller, non-corporate businesses lack the time or resources to tackle them.
That does not remove the need for oversight.
When evaluating a provider, businesses should look beyond marketing claims and prioritise vendors that provide clear, auditable evidence of how they manage security, and review that trust regularly rather than treating it as a one-off check.
Capability can be outsourced. Accountability cannot.
The importance of being ready to respond to cyber threats
Only 36% of businesses surveyed have an incident response plan supported by exercises. This matters because no organisation can eliminate cyber risk completely.
But when an incident occurs, responsibility for decisions still sits with the business, even if they rely on external providers for support.
Leaders should know who is in charge, which services need to be restored first and how customers, regulators and partners will be informed.
A plan that has never been practised remains an assumption. Simple exercises can expose unclear ownership, missing information and unrealistic recovery expectations before a real breach does.
Why AI adoption requires better governance
AI is lowering the barriers to building and modifying software. Employees can now generate code, automate workflows and connect systems with minimal technical expertise.
As a result, businesses can introduce software risk without seeing themselves as software developers.
Before integrating an AI-enabled tool, leaders should understand what data it can access, what it retains, which systems it connects to, what permissions it requires and how its outputs will be used.
This is increasingly important in a market filled with ambitious claims and rapid product launches. Businesses need to separate useful innovation from marketing hype.
Human supervision remains necessary where AI influences sensitive data, customers, employees, financial decisions or other material business outcomes.
The aim is not to slow adoption but to ensure speed does not come at the expense of safety.
Why vendors must carry more of the load
Only 13% of businesses in the IDC research continuously monitor the security of their software-as-a-service providers but the reality is most businesses do not have the resources to conduct enterprise-grade assurance across every platform they use.
Technology providers need to make secure adoption easier. Customers should be able to understand, in plain English, how AI is being used, what data it can access and what controls are in place to protect it.
A poorly governed AI capability can expose customers to risk and erode trust. The strongest providers will not be those that release the most AI features, spend the most on security or adopt the latest tools first.
They will be the ones who understand their risks, know where accountability sits and have the operational discipline to respond as technology evolves. They’ll also ensure those capabilities are safe, understandable and easy to adopt.
As AI continues to lower barriers and increase speed, access to technology is becoming less of a differentiator. What increasingly matters is how organisations govern, deploy and manage those capabilities in practice.
The cyber maturity gap is not simply a technology challenge. It is increasingly an operational one.
Final thoughts
The next phase of AI adoption will be defined by more than speed and innovation.
Trust and operational resilience will determine which organisations can turn new capability into sustainable value.
Explore SMBs in the age of AI: Navigating cyber complexity and building resilience research for yourself and see how you can improve security in a changing technology landscape.
Frequently asked questions
AI’s biggest immediate effect is making familiar threats more efficient. It lets attackers find and exploit weaknesses at greater speed and scale, and makes phishing and impersonation far more convincing. The same tools also help defenders with code review, threat analysis and remediation—so the advantage goes to whoever can apply AI safely and turn its insight into action fastest.
Those foundations remain essential, but the next maturity gap sits above them. Effective security now depends on clear ownership, current knowledge of your systems and data, regular testing and the ability to respond when something changes. IDC research commissioned by Sage reveals that 44% of SMBs cited a lack of internal expertise or time as a major challenge—which points to a capability gap, not simply a technology one.
Not every vulnerability carries the same risk. A weakness in an isolated, low-value system may matter far less than a lower-severity issue on an internet-facing service or one holding sensitive data. It’s also worth watching for combinations, as several minor weaknesses together can become serious. AI can speed up that analysis, but it can’t decide which business service matters most or how much disruption you can tolerate. People stay accountable for the call.
Yes. And where internal capacity is limited, it’s often the responsible choice. Monitoring, vulnerability management, technical assurance and incident support can all be delivered by managed providers and trusted partners, which beats leaving known risks unaddressed. What can’t be handed over is ownership: leaders still need to know which services are critical, which risks they’re accepting and how their providers are being assessed. Capability can be outsourced; accountability cannot.
Before integrating any AI-enabled tool, understand what data it can access, what it retains, which systems it connects to, what permissions it needs and how its outputs will be used. Keep human oversight wherever AI touches sensitive data, customers, employees or financial decisions. It’s also fair to expect more from vendors—only 13% of SMBs continuously monitor their SaaS providers’ security, so safer defaults and plain-English controls should come built in, not bolted on by the customer.
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