Cyber security in 2026 will be shaped by speed. Threat actors will move faster, using AI offensively to mimic human behaviour, and exploit systems in ways traditional defences cannot keep up with.
At the same time, defenders are racing to deploy AI in defence, using it to accelerate detection and automate remediation, writes Richard Ford, chief technology officer at Integrity360.
Obvious signs of phishing, such as awkward language or far-fetched requests, will become less reliable.
In their place, attackers will use sophisticated, AI-augmented social engineering techniques that mimic real interactions, tailored to specific organisations or individuals.
This is already happening. Tools like Black Mamba, a proof-of-concept (PoC) malware, demonstrate how polymorphic malware can dynamically change its structure in real-time to evade detection.
AI bots are already scanning for weaknesses, writing exploit code, and identifying high-value targets faster than any human can.
As the balance of power shifts, defenders face a new kind of challenge that plays out in real time.
So how can security leaders build the right foundations before the pressure mounts?
Deep-targeted social engineering and identity risk
Social engineering will become harder to detect and even harder to defend against. Deepfake audio and video will blur the lines of trust, especially in high-pressure or time-sensitive situations.
Employees may not be able to distinguish a real colleague’s voice from a synthetic one, and that uncertainty creates dangerous openings.
These tactics are now powered by AI. Attackers can analyse a company’s public content, learn internal language patterns, and launch highly convincing impersonation attempts at speed.
This shift toward AI-augmented social engineering will put new pressure on frontline defences.
Businesses must rethink how they prepare their teams.
Traditional phishing simulations are no longer enough. Instead, training needs to be role-specific and scenario-based, reflecting real-world attacks like simulated voice impersonation or deepfake-led requests. High-risk teams need to rehearse responses to convincing, high-stakes fraud attempts.
Identity-first security will become essential. Workflows for authorising payments or confirming instructions must be locked down and verifiable, particularly for executives.
Verified multi-step authorisation must become standard. Involving senior leaders in simulations will help prepare the wider workforce to respond calmly and effectively.
AI-augmented SOC: shifting roles and automation
Security operations centres (SOCs) will look very different in 2026. The traditional three-tier structure will be replaced by leaner teams with targeted skills. As AI automates lower-level tasks, human analysts can focus on high-value threat hunting and decision-making.
AI will suggest responses and surface relevant patterns across large datasets. SOC teams will work alongside AI co-pilots – interactive, context-aware tools that support analysts with everything from anomaly detection to reporting.
These co-pilot models are changing the operational landscape, turning analysts into strategic advisors.
This shift brings new challenges. Security teams must trust AI without relying on it blindly. Training will need to focus on validating AI outputs and building critical thinking to prevent deskilling.
A new kind of literacy – AI literacy – will become essential to ensure tools enhance, not dilute, human expertise.
The widening attack surface in hybrid-cloud and SaaS landscapes
As cloud adoption grows and organisations expand across hybrid environments, the attack surface increases. Many companies lack visibility over assets, users, and access points, making breaches more likely and harder to contain.
The sprawl of Software-as-a-Service (SaaS) adds further risk, as individual configurations and permissions can easily go unmanaged.
According to Gartner, cloud security services are expected to experience the most growth of any other area by 2028, with a projected 25% increase in compound annual growth. This reflects just how urgent and complex the cloud risk landscape has become.
Real-time exposure management will be critical. This includes monitoring SaaS configurations, and credential use. Static assessments will no longer be enough. Businesses must continuously assess what is exposed and how attractive those assets are to attackers.
Access controls must be contextual, based on device health and behaviour. Frameworks like Zero Trust can help reduce standing privileges and prevent lateral movement. The perimeter is now a moving target; only dynamic, identity-aware models can keep pace.
Regulation, AI risk and the quantum challenge
Regulatory demands will grow significantly in 2026. In the EU, organisations must comply with the AI Act, the NIS2 Directive, and DORA. In the UK, the Cyber Security and Resilience Bill will raise expectations around ransomware reporting and third-party oversight.
Companies must show that their AI systems are secure and auditable. This means maintaining model inventories and supplier monitoring. Regulators will expect visibility into how AI decisions are made and who is accountable when things go wrong.
Quantum computing is no longer a distant threat. While large-scale attacks may still be years away, sectors like finance must start preparing now. That includes mapping cryptographic exposure and upgrading infrastructure for quantum-safe algorithms. Resilience starts with awareness and builds through action.
Lead now or fall behind
2026 will not wait. Threats are evolving faster than many organisations are prepared for. But the winners will not be those who simply predict what is coming; they will be the ones who act now.
Security leaders must modernise defences and prepare for a regulatory landscape that demands more by default. This is about readiness because those who move early will not only stay protected, but they will also stand out as trusted partners in an uncertain world.