Cyber security has always been an arms race. New defences prompt new attacks, and so on. The rise of powerful, widely available AI tools has simply turned the treadmill up a notch.
By 2026, the most serious cyber threats facing SMEs will be AI-accelerated versions of familiar risks rather than entirely new categories. Phishing, fraud, account takeover and ransomware will all become more targeted, more convincing and harder to detect manually.
Start with phishing. Today, you can usually spot at least some dodgy emails by clumsy wording or obviously generic content. AI text and voice models change that. Attackers can generate perfectly localised, context-aware messages that reference public information about your company, staff and clients. Deepfake audio and video add another layer, enabling convincing “CEO voice” scams.
Then there’s scale. AI lets attackers customise thousands of messages cheaply. Instead of blasting the same email to everyone, they can tailor content to specific roles – finance, HR, IT – and even individual interests where data is available. Traditional rule-based filters will struggle; the line between malicious and legitimate communication will blur.
On the technical side, AI can help attackers probe systems more efficiently, generate exploit code, and adapt malware signatures to evade detection. Conversely, defenders are using AI for anomaly detection, behavioural analysis and automated response. The net result is more activity on both sides.
For SMEs, the risk is not that you’ll be specifically “targeted by AI”. It’s that you’ll be caught in a rising tide of more sophisticated attacks while still relying on 2018-era defences: basic antivirus, infrequent training, and a vague hope that “we’re too small to be interesting”.
What should a pragmatic 2026 security strategy look like?
First, accept that some perimeter defences will fail. Plan for compromise. That means robust multi-factor authentication (MFA) on all critical systems, strict role-based access control, and rapid revocation processes when something looks off. If a password is stolen, MFA should be the backstop.
Second, invest in endpoint and identity protection that uses behaviour, not just signatures. Modern security tools can flag unusual patterns: logins from odd locations, mass downloads, atypical command usage. You don’t need bleeding-edge AI; you do need something smarter than a static blacklist.
Third, upgrade your human defences. Traditional annual “click through this e-learning” training is nearly useless against AI-crafted attacks. Move towards shorter, more frequent, scenario-based sessions. Simulate realistic phishing attacks that use current tactics, and use them to coach rather than blame.
Teach staff simple rules of thumb that still work in an AI world:
- Don’t trust unexpected requests to move money or share data, even if they appear to come from senior people.
- Verify via a second channel you control (phone, known Teams contact, in person).
- Treat urgency and secrecy as red flags.
Fourth, pay attention to your third parties. Many breaches start via suppliers with weaker security. Ask key vendors basic questions: Do you enforce MFA? How do you handle access logs? What’s your breach notification process? You don’t need to audit everyone to ISO standards, but you should know where your riskiest dependencies are.
Fifth, plan your incident response. If the worst happens – a ransomware note appears, customer data is stolen, or systems are locked – who does what, in what order? Who talks to customers, regulators, insurers? Which systems are prioritised for restoration? A simple, rehearsed playbook beats a chaotic scramble every time.
Finally, be realistic about budget. You can’t protect against everything, but you can do a few important things well. Focus on protecting identities, email, cloud admin accounts and critical business data. Accept that convenience will occasionally have to give way to safety.
AI will continue to reshape the threat landscape, but the fundamentals remain: know your assets, reduce your attack surface, monitor for anomalies and respond quickly. The businesses that fare best in 2026 won’t be those with the fanciest algorithms. They’ll be the ones who took the basics seriously, early.
