Artificial intelligence is rapidly changing the threat landscape. It makes attacks faster to develop, easier to scale and harder to distinguish from legitimate activity.
For small and medium-sized businesses, this is important because the pace of change is accelerating faster than many can establish the governance, visibility and operational disciplines necessary to keep up.
That’s what we explore in this article, as follows:
AI means increased use of cyber security
A recent IDC study 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 their use of cyber security.
The issue is not a lack of awareness or intention. It’s a growing gap between good intentions and the ability to consistently manage a complex threat environment.
The AI doesn’t need to create a new attack class to tip the balance.
Its immediate effect is to make conventional threats more effective.
Vulnerability discovery and exploitation can occur at high speed and scale. Phishing can be very convincing. Pretending to be someone you’re not can be more realistic.
The same technology also offers defenders clear advantages.
AI can support code review, vulnerability detection, threat analysis and remediation.
The benefit will not come from access to AI alone. It will come from the ability to use it safely, use human judgment and translate insight into action quickly.
How the maturity gap comes into effect
Most businesses already have key controls in place, including email protection, patching, backups, endpoint security and multifactor authentication.
Those foundations are always critical.
The challenge is that resilience in the Internet is highly dependent on what happens beyond those foundations.
The study found that 44% of surveyed businesses cited a lack of internal expertise or time as a major challenge. That suggests that the problem is no longer just having the right tools. It’s about having the power, the visibility, and the processes to use it effectively.
Effective security is ultimately an operational discipline and depends on clear ownership, current knowledge of systems and data, regular testing, prioritization of information and the ability to respond when something changes.
Why prioritizing risk is important
The increasing volume of vulnerability does not mean that everything presents the same vulnerability.
In fact, context matters. Weaknesses in a different, lower-cost system may create limited exposure quickly.
A low-severity problem affecting an Internet-facing service, a critical workflow or a sensitive data set may require the most immediate action.
Several relatively small weaknesses can be very large when combined.
Businesses need to understand what systems are exposed, what data is most important, how easily vulnerabilities can be exploited and what the operational impact could be.
AI can help reveal and analyze that information much faster. What it cannot do is decide which services are most important to the business or what level of disruption the organization can tolerate or what risks leaders should accept. Those are still people’s decisions.
As attackers and application providers move at a faster pace, businesses will need to review their exposure more often.
This does not require all businesses to implement continuous security testing overnight. It means shortening review cycles incrementally, starting with systems, suppliers and data that can cause the biggest business impact if compromised.
How to improve cyber security for businesses
The answer is not for each business to recreate the security capabilities of a global business. For most businesses that would be impractical and, in many cases, unnecessary.
Where internal capabilities are limited, businesses can deliver specialized support through managed security providers, external consultants and trusted technology partners. In some cases, seeking outside expertise is more effective than leaving known risks unaddressed because small, non-corporate businesses lack the time or resources to address them.
That does not eliminate the need for oversight.
When evaluating a provider, businesses should look beyond marketing claims and prioritize vendors that provide clear, verifiable evidence of how they handle security, and review that trust regularly rather than taking it as a reality check.
Power can be supplied externally. Accountability cannot.
The importance of being prepared to respond to cyber threats
Only 36% of surveyed businesses have an incident response system supported by exercises. This is important because no organization can eliminate cyber risk completely.
But in the event of an incident, the responsibility for decisions still rests with the business, even if it relies on external providers for support.
Leaders must know who is in charge, which services need to be restored first and how customers, regulators and partners will be informed.
A plan that is never implemented is always an idea. A simple exercise can reveal unclear identities, lost information and unrealistic recovery expectations before the actual breach occurs.
Why AI adoption requires better governance
AI lowers barriers to building and modifying software. Workers can now generate code, automate workflows and connect systems with minimal technical expertise.
As a result, businesses can introduce software risk without identifying themselves as software developers.
Before integrating an AI-enabled tool, leaders must understand what data it can access, what it stores, what systems it connects to, what permissions it needs and how its results will be used.
This is especially important in a market full of ambitious claims and rapid product launches. Businesses need to separate useful innovation from marketing hype.
Human supervision is always necessary when AI influences sensitive data, customers, employees, financial decisions or other business outcomes.
The goal is not to reduce child adoption but to ensure that speed does not come at the expense of safety.
Why sellers should bear more responsibility
Only 13% of businesses in the IDC survey continue to monitor the security of their software-as-a-service providers, but the reality is that many businesses don’t have the resources to conduct enterprise-level 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 used, what data it can access and what controls are in place to protect it.
The power of poorly managed AI can expose customers to risk and erode trust. The strongest providers won’t be the ones that release the most AI features, spend the most on security or use the latest tools first.
They will be the ones who understand their risks, know where accountability lies and have the operational discipline to respond as technology advances. They will also ensure that those skills are safe, understandable and easy to use.
As AI continues to lower barriers and increase speed, access to technology is becoming less diverse. What is increasingly important is how organizations manage, use and manage those skills in practice.
The online growth gap is not just a technical challenge. It is becoming more and more effective.
Final thoughts
The next phase of AI adoption will be defined more by speed and innovation.
Trust and operational resilience will determine which organizations can turn new energy into sustainable value.
Explore SMBs in the age of AI: Navigating the complexities of the Internet and build your own resilience research and see how you can improve security in a changing technology environment.
Frequently Asked Questions
The biggest immediate impact of AI is to make conventional threats more efficient. It allows attackers to find and exploit vulnerabilities at high speed and scale, and makes phishing and impersonation more believable. The same tools also help defenders with code reviews, threat analysis and remediation—so the benefit goes to anyone who can use AI safely and turn its insights into action quickly.
Those foundations remain important, but the next growth gap lies beyond 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. In an IDC study presented by Sage, it revealed that 44% of SMBs cited a lack of internal knowledge or time as the biggest challenge – pointing to a skills gap, not just a technology one.
Not all risks have the same risk. A vulnerability in an isolated, low-cost system may be more important than a low-severity problem in an Internet-facing service or one that carries sensitive data. It is also worth looking at combinations, as several small weaknesses together can be large. AI can accelerate that analysis, but it can’t decide which business resource is most important or how much disruption you can tolerate. People always answer to themselves on the phone.
Yes. And when internal capacity is limited, it is often the right choice. Monitoring, risk management, technical assurance and incident support can all be delivered by managed providers and trusted partners, rather than leaving known risks unaddressed. What cannot be given ownership: leaders still need to know what services are important, what risks they accept and how their suppliers are evaluated. Power can be provided externally; accountability cannot.
Before integrating any AI-enabled tool, understand what data it can access, what it stores, what systems it connects to, what permissions it needs and how the output will be used. Maintain human oversight wherever AI affects sensitive data, customers, employees or financial decisions. It’s also fair to expect more from vendors—only 13% of SMBs regularly monitor the security of their SaaS providers, so secure automation and plain-English controls should come built-in, not sponsored by the customer.
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