AI Cybersecurity Companies: What They Do and How to Judge Them
Almost every security vendor now says its product uses AI. This guide explains what that usually means, how to test the claims, and which well-known vendors describe AI-driven products on their own pages.
Key Takeaways
- "AI-driven" covers very different things: anomaly detection, behavioural analytics, language-model assistants and automated response are not the same capability.
- Vendor figures are usually self-measured. Ask for the method behind any accuracy or time-saving claim.
- Test on your own data. A trial against your estate tells you more than any demonstration.
- Human approval of automated actions matters. Check what the tool does alone and what needs sign-off.
- This is not a ranking. The vendors named are examples taken from their own pages as at October 2026.
AI cybersecurity companies are security vendors whose products use machine learning or generative AI to detect threats, speed up investigation or automate parts of the response. In practice the label spans a wide range, from statistical models that flag unusual behaviour on a network to assistants that summarise an incident for an analyst.
That breadth is why the label alone tells you very little. Two products can both be described as AI-driven and differ completely in what they detect, what data they need and how much of your team's time they save.
This article explains the main ways AI is used in security, how to separate real capability from marketing, and which questions to put to a vendor. It also lists a small number of well-known vendors, described factually from their own product pages. It is not a ranking, and inclusion is not a recommendation.
How security vendors use AI
Most AI features in security products fall into four groups.
- Anomaly detection: the product learns what normal looks like for a network, user or device and flags deviations. It can find activity that no signature describes, but it can also raise false alarms when behaviour changes for legitimate reasons.
- Behavioural analytics: models score sequences of actions, such as a user signing in from a new location and then downloading files in bulk. Microsoft Learn lists User and Entity Behavior Analytics (UEBA) among the detection features of Microsoft Sentinel.
- Assistants for analysts: generative AI helps write queries, summarise alerts and draft reports. These tools save time but do not replace an analyst's judgement.
- Automated response: the product isolates a device, disables an account or blocks a message without waiting for a person. The value depends on how well the rules and approval steps are set.
Many products combine all four. The useful question is which of them is doing the work you are paying for.
Each also needs different inputs. Anomaly detection needs a period of learning before its baseline is reliable, assistants need access to your alert data, and automated response needs permissions that you should grant deliberately and review regularly.
↑ Back to ContentsSeparating capability from marketing
Be cautious of claims that cannot be tested. Three patterns appear often.
- Self-measured results. A vendor's own page may quote an accuracy or time-saving figure. For example, CrowdStrike's Charlotte AI page states that its analyst assistant has a triage accuracy figure measured against its own managed service team, and SentinelOne's platform page quotes detection and remediation time reductions without describing a method. Those are the vendors' claims, so ask for the test conditions before relying on them.
- AI as a label. Rules and signatures relabelled as AI. Ask what model is used, what it was trained on and whether it learns from your data.
- Full autonomy promised. Be sceptical of any suggestion that a person is no longer needed, because someone must still own the outcome when a tool makes a wrong call. CrowdStrike's own page says by default its assistant only generates information and recommendations, and that actions that change the environment need approval from an authorised team member.
The point is not that these claims are wrong. It is that they come from the seller, so you should verify them in a trial. Our AI roadmap for business guide covers how to approach AI adoption more broadly.
↑ Back to ContentsQuestions to ask any AI security vendor
Put the same questions to each vendor and record the answers in writing.
| Area | Question | What a good answer looks like |
|---|---|---|
| Data | What data does the model use, and is it trained on my data? | A clear description, with UK GDPR and data location terms in the contract |
| Method | How was the quoted accuracy or time saving measured? | Test conditions, sample size and who ran the test |
| False positives | How many alerts will my team have to review, and how do I tune them? | A trial result on your estate, plus tuning controls |
| Control | Which actions run automatically, and which need approval? | Configurable approval steps and an audit log |
| Explainability | Can an analyst see why something was flagged? | Evidence trail rather than a bare score |
| Integration | Does it work with the tools I already run? | Documented connectors and open data export |
| People | Who watches the alerts out of hours? | A named team, whether yours or a provider's |
A proof of concept on a realistic slice of your estate is the strongest test. If a vendor will not allow one, treat that as information.
↑ Back to ContentsWell-known vendors with AI-driven products
This is not a ranking
The vendors below are listed in no order of merit. They are examples whose own pages, opened in October 2026, describe AI-driven security features. Descriptions are the vendors' claims, summarised factually, not independent findings.
| Vendor | What its own page describes | Source |
|---|---|---|
| CrowdStrike | Charlotte AI, described as an agentic AI security analyst built into the Falcon platform, used to investigate threats, triage detections, write queries and generate reports across endpoints, identities, cloud and network. | CrowdStrike product FAQ |
| Darktrace | A range of products across cloud, email, network, endpoint and identity, with AI said to learn from each customer's own data to understand what is normal, plus a Cyber AI Analyst that investigates alerts. | Darktrace products page |
| Microsoft | Microsoft Defender XDR for correlated detection, Microsoft Sentinel as a cloud-native SIEM and SOAR with UEBA, and Security Copilot listed as an embedded experience in the Defender portal. | Microsoft Learn |
| SentinelOne | The Singularity Platform, described as covering endpoint, cloud, identity and AI security, with Purple AI used for investigation. | SentinelOne platform page |
Further reading is on Darktrace's products page and SentinelOne's platform page. Other credible vendors exist, including specialists in email, identity and cloud security; this short list is illustrative, not complete, and omits many firms that would suit particular needs.
↑ Back to ContentsA practical process for testing AI security tools
A trial is only useful if it is planned. Agree the success measures before it starts, not after you have seen the results.
- Define the use case. For example, faster triage of endpoint alerts, or earlier detection of unusual sign-ins.
- Record your baseline. Note how many alerts you receive today, how long investigation takes and how many are false alarms.
- Run it on live data. Use a representative group of users and devices, including remote workers and servers.
- Include a known test. A scoped penetration test or a controlled exercise shows whether the tool notices realistic activity.
- Compare against the baseline. Measure the same things again and ask the vendor to explain any gaps.
Keep the people who will operate the tool involved from the first day of the trial. If they find the output hard to understand or act on, the product will not deliver value however strong its models are.
↑ Back to ContentsWhat this means for UK SMEs and mid-market firms
Advanced AI tooling helps most when someone is available to act on its output, and when its alerts are tied to a defined response process. A tool that raises a high-priority alert at 2am is of limited use if nobody is on call.
For many UK organisations the practical choice is therefore between buying a platform and running it internally, or buying the outcome as a managed service. Our page on managed EDR services describes the second route, and our managed IT support service covers the surrounding IT operations.
Do not let AI features distract from the basics. Multi-factor authentication, patching, secure configuration and tested backups prevent a large share of incidents, and the Cyber Essentials scheme sets out a baseline. Staff also remain a target for convincing AI-written messages, so keep your phishing awareness training current.
↑ Back to ContentsAI for security versus AI that needs securing
Two questions are often mixed up. The first is whether your security tools use AI. The second is whether the AI tools your staff use are themselves secure.
Assistants such as Microsoft 365 Copilot work with the data your users can already access, so over-shared files and loose permissions become more visible. Our explainer on Microsoft 365 Copilot covers readiness, and an independent cyber security audit can show where permissions and configuration need attention before AI tools are rolled out.
↑ Back to ContentsChoosing among AI cybersecurity companies
The most reliable way to judge AI cybersecurity companies is to ignore the label, define the problem you need solved and test each product against it using your own data. Ask how claims were measured, what runs without approval and who responds when an alert fires.
If you would like help comparing tools or running a trial, speak to us via the contact page.
↑ Back to ContentsFrequently Asked Questions (FAQs)
What do AI cybersecurity companies actually do?
They build security products that use machine learning or generative AI for tasks such as spotting unusual behaviour, correlating alerts into incidents, helping analysts investigate and automating some responses. The label covers very different capabilities, so you need to ask which task the AI performs and how its results are measured.
Is this a ranking of the top AI cybersecurity companies?
No. The vendors named are examples whose own product pages describe AI-driven features, opened in October 2026. They are listed in no order and the descriptions are the vendors' own claims. Fit with your systems, team and budget matters more than any league table, so use the list as a starting point for your own research.
How can I tell if a vendor's AI claims are genuine?
Ask what the model does, what data it uses, and how any accuracy or time-saving figure was measured. Run a trial on your own estate and compare alert quality, false positives and response actions. Be wary of claims that cannot be tested or that suggest no human oversight is needed.
Can AI replace a security team?
Not in a way that removes accountability from your organisation or its leadership. AI can speed up triage and investigation, but people still decide priorities, approve disruptive actions and handle incidents. Some vendors state that their own assistants only recommend by default and need authorised approval for changes to the environment. Many firms pair tools with a managed service so that alerts are watched and acted on out of hours.
Are AI-driven security tools suitable for small businesses?
They can be, but a small business rarely has dedicated staff to tune and monitor them. Basic controls such as multi-factor authentication, patching and backups come first. If you do adopt AI-driven tools, a managed service that handles alerts is often more practical than running a platform yourself.
What should I ask AI cybersecurity companies before buying?
Ask about training data and UK GDPR handling, how performance claims were measured, how many false positives to expect, which actions are automatic, whether analysts can see why something was flagged, and who responds out of hours. Put the answers in writing and verify them in a proof of concept.
Speak to a NetMonkeys specialist
Practical, plain-English IT advice for UK businesses, from our Manchester headquarters and our teams in London and Nottingham.
Book a conversation
