A fully staffed Security Operations Centre costs somewhere between $1.5 million and $4 million per year to run. That’s analyst salaries, tooling, facility costs, and 24/7 coverage. For a large enterprise, it’s a necessary expense. For an Australian SMB doing $5-20 million in revenue, it’s out of the question.

But the threats don’t care about your revenue size. The same ransomware gangs targeting hospitals and government agencies are hitting small accounting firms and construction companies. So what do you do when you can’t afford human eyes on your security alerts around the clock?

Increasingly, the answer is AI-driven security monitoring. And in 2026, these tools have matured to the point where they’re genuinely useful — with some important caveats.

What AI Security Monitoring Actually Does

Let’s strip away the marketing language. AI-powered security monitoring tools do three core things:

Log aggregation and correlation. They pull logs from your endpoints, network devices, cloud services, email platform, and identity provider into a single place. Then they correlate events across those sources. A failed login attempt on its own means nothing. A failed login from an unusual IP, followed by a successful login, followed by a large file download from SharePoint — that’s a pattern worth investigating.

Anomaly detection. Machine learning models build a baseline of “normal” behaviour for your environment. When something deviates — a user accessing systems they’ve never touched, network traffic to a country your business doesn’t operate in, a server process making unusual DNS queries — the system flags it. This is where AI adds genuine value over static rule-based systems. Rules catch known patterns. ML catches novel ones.

Automated response. The more advanced tools can take predefined actions when certain threat patterns are detected. Isolate a compromised endpoint from the network. Disable a user account that’s showing signs of compromise. Block an IP address that’s conducting a brute-force attack. These automated responses happen in seconds rather than the hours it might take a human team to notice and react.

The Tools Worth Looking At

The market has consolidated quite a bit. Here are the platforms that are realistically accessible for Australian SMBs:

Microsoft Sentinel is the default choice for businesses already running Microsoft 365. It’s a cloud-native SIEM (Security Information and Event Management) that integrates natively with Azure AD, Defender, and the rest of the Microsoft security stack. Pricing is consumption-based — you pay per GB of log data ingested — which can be unpredictable but typically runs $2,000-$8,000 per month for a 50-100 person business.

CrowdStrike Falcon LogScale (formerly Humio) pairs with CrowdStrike’s excellent endpoint protection. If you’re already running Falcon on your endpoints — and it’s one of the best EDR tools going — adding LogScale for SIEM functionality is a logical step. CrowdStrike has strong AI-driven detection capabilities and their managed detection service (Falcon Complete) adds human oversight for around $40-60 per endpoint per month.

SentinelOne Singularity takes an integrated platform approach, combining endpoint, identity, cloud, and network security with AI-driven detection. Their Purple AI assistant lets you query your security data in natural language, which is genuinely useful for businesses without dedicated security analysts.

Blumira is specifically designed for SMBs without security teams. It’s simpler than the enterprise tools, with automated detection rules, guided response steps, and a price point that’s more accessible — typically $3-6 per user per month.

What These Tools Get Right

The genuine improvement over the past two years has been in reducing alert fatigue. Earlier-generation SIEM tools would drown you in thousands of alerts per day, most of them false positives. AI-driven correlation and scoring has dramatically reduced this. Modern tools prioritise alerts by severity, confidence, and business context, presenting a manageable queue of items that actually need attention.

The Australian Cyber Security Centre recommends that all businesses implement some form of security event monitoring, and their Essential Eight framework specifically calls out centralised logging as a baseline requirement. AI-driven tools make this achievable for businesses that previously couldn’t justify the investment.

For businesses exploring how to integrate AI into operational workflows beyond just security, providers of AI automation services can help assess where intelligent automation fits across your entire business — not just the SOC.

Where They Fall Short

Let me be honest about the limitations.

They don’t replace human judgment. When an AI tool flags a potential incident, someone still needs to investigate and decide on the appropriate response. For straightforward scenarios (brute-force login attempts, known malware signatures), automated responses work well. For ambiguous situations — is that unusual data access a threat or a legitimate business need? — you need a person.

Configuration matters enormously. An AI security tool with default settings and no tuning is better than nothing, but not by much. You need someone to configure log sources, tune detection rules, set up automated responses, and review false positives regularly. This is typically where a managed security service provider (MSSP) comes in — they handle the ongoing tuning for a monthly fee that’s far less than running your own SOC.

They can’t fix fundamental weaknesses. AI monitoring can detect a compromised password being used. It can’t fix the fact that you don’t have multi-factor authentication enabled. These tools are a detection layer, not a replacement for basic security hygiene. MFA, patching, backup testing, and access control remain essential foundations.

Cloud dependency introduces risk. Most AI security tools are cloud-based. If your internet connection goes down, or if the provider experiences an outage, your monitoring goes dark. For most SMBs this is an acceptable tradeoff, but it’s worth understanding.

A Practical Setup for a 50-Person Business

Here’s what a realistic AI-driven security monitoring setup looks like for a typical Australian SMB:

Endpoint protection with EDR: CrowdStrike Falcon or SentinelOne on every device. This is your first line of defence and your richest data source. Budget $15-25 per endpoint per month.

Cloud SIEM: Microsoft Sentinel if you’re a Microsoft shop, or Blumira if you want something simpler. Ingest logs from endpoints, Microsoft 365, your firewall, and any cloud infrastructure. Budget $2,000-5,000 per month.

Managed detection and response (MDR): Unless you have an in-house IT person with strong security skills, pair the tools with an MDR service. This gives you a team of analysts who review alerts, investigate incidents, and guide response. Budget $2,000-4,000 per month.

Total: roughly $5,000-$12,000 per month. That’s 3-8% of what a dedicated SOC would cost, and for most SMBs, it provides 80% of the protection. Not perfect, but a massive improvement over the alternative of hoping nothing bad happens.

The Bottom Line

AI-driven security monitoring isn’t a silver bullet, and anyone telling you otherwise is selling something. But for Australian SMBs facing real, growing threats without the budget for enterprise security teams, these tools represent a genuine step forward.

The key is being realistic about what they do and don’t provide, investing in proper configuration and tuning, and pairing the technology with some level of human expertise — even if that’s an external MSSP rather than a full-time hire.

Don’t wait for a breach to justify the investment. The average cost of a data breach for an Australian SMB is now north of $200,000 according to recent OAIC reporting. A properly configured AI monitoring setup at $5,000-12,000 per month is insurance that actually works.