When “Essential Protection” Still Feels Like a Luxury
If you run IT security at a mid-market company, you’ve probably noticed the math stopped making sense. Even essential services like 24×7, good quality detection and response are still only affordable to large enterprises.
Under the hood, AI has finally made a lot of this work cheaper to deliver. Machines can read alerts, stitch signals together, and draft investigations faster than an overcaffeinated analyst. Foundation models have bottled up intelligence from hundreds of analysts and are now available via an API. But a lot of providers are behind the curve – your contracts and price lists are still the same as they were two years ago. And, worse, the quality of the service is still poor. They are still operating as if every decision requires a room full of analysts on the night shift.
When an airbag costs as much as a Ferrari, it isn’t a problem with product availability; it’s a problem of economics and the business model.
Why Sophisticated Security Used to Be So Expensive
Delivering IT security has been expensive for one simple reason: it requires people. It required experts, experts with 10+ years of experience.
A proper 24×7 operation meant seasoned analysts staring at a busy queue of noisy alerts at 3 a.m., piecing together data and signals from different tools by hand, trying to glean whether it is a real attack or just normal behavior.
The tools spat out signals; humans did almost all the thinking. It was 80% people, 20% technology, and the pricing was built around that. Whether you bought SIEM, XDR, or MDR, you were paying for scarce expert time.
In the mid-market, that created an ugly choice: buy the tools and hope one or two overworked security people can keep up, or outsource to a service provider whose pricing was quietly designed for Fortune 500 economics, not a 300-person manufacturer or SaaS company. And, the more affordable providers – the quality was nowhere close to what the customer expected.
Either way, sophisticated security felt like a luxury line item, not a baseline control that every enterprise could afford.
Also Read: CIO Influence Interview with Gera Dorfman, Chief Product Officer at Orca
What AI Changed in Security Operations
Modern AI is very good at boring, repetitive SOC tasks: reading ugly alerts, pulling context from different tools, and drafting a first pass at “what happened and what we should do.”
In fact, in one aspect, it is much better than even analysts with 10-15 years of experience – and that is breadth of knowledge. No analyst knows thousands of alerts in detail, the right questions to ask to investigate those, but foundation models from Anthropic and OpenAI do.
That flips the old 80/20 split to 20% human judgment on top of 80% machine assistance for triage, enrichment, and case writing.
The impact is real if you design for it: fewer midnight fire drills, fewer all-hands-on-deck incidents, and smaller teams handling more volume without burning out. In other words, the true cost per investigated alert is dropping. The question isn’t whether AI can help — it’s whether your current setup lets you capture that benefit instead of paying 2016 rates for 2026 work.
So, Why Are You Still Paying 2024 Prices?
Part of it is vendor inertia. Most MDR, XDR, and SOC tools were priced in a world where humans did almost everything. Then AI showed up, vendors wired it in under the hood, and… left the commercial model mostly alone. You’re still being charged as if you’re buying scarce analyst time, even when a lot of that work is now automated.
The rest is on your side of the table. Security budgets at mid-market companies tend to grow by accumulation, not design: a SIEM here, an MSSP contract there, a “temporary” tool that never got turned off. Everyone gets used to the number. “We’ve been paying roughly this much for monitoring.”
The result is a squeeze that feels familiar: overpay for services quietly tuned for larger company economics, or accept gaps — business-hours coverage, best-effort triage, and thin documentation when something actually goes wrong.
It’s time to demand significantly better quality at meaningfully lower cost.
A Mid-Market Team That Flipped the Equation
Consider a fast-growing SaaS company with a tiny security team: compliance boxes were checked, but 24×7 monitoring was a mirage.
Instead of trying to build a mini-SOC in-house, they changed the equation. They moved to a model where AI handles the heavy lifting on alert triage and investigation, and every case, decision, and escalation is documented in plain language for the lean internal team. SLAs are about outcomes — “every critical alert investigated, escalations within X minutes” — not just platform uptime.
The result wasn’t magic; it was sanity. They bought consistent coverage without a headcount binge, freed their security people to focus on risk and architecture, got away from weekend pages, and could finally tell leadership, “Here’s exactly what we’re getting for this spend.”
What Mid-Market CIOs/CISOs Should Do Now
Start by re-baselining your SOC economics. Lay out what you spend on three things: tools, outside services, and internal people. Then ask a brutal question: If we were designing this from scratch, knowing what AI can do now, would we still spend it this way?
Next, raise the bar with your vendors and service providers. Where does a human still touch every case, and where is AI actually doing the work? How have their unit costs changed in the last 2-3 years, and where does that show up in your pricing? Are their SLAs about uptime, or about investigated alerts, escalations within a defined window, and real documentation?
Finally, shift the mix. Cut overlapping tools whose “AI features” don’t reduce your workload and lean toward AI that is built-in and transparent.
Talking to Leadership: From “More Spend” to “Better Spend”
When you take this to leadership, don’t sell it as an AI science project. Frame it as a cost reset.
You’re not asking for more money; you’re saying that for roughly the same security budget, you can buy better coverage and better use of your team’s time.
Show the before/after equation in plain language:
- Before: most of our spend went to keeping the lights on—chasing alerts, watching dashboards, paying for tools and services that still leaned heavily on human labor.
- After: the same (or slightly higher) budget buys documented 24×7 coverage, faster investigations, and a security team that spends more time reducing risk than clearing queues.
AI has already made security cheaper to deliver. Many vendors have already captured those efficiency gains—they’re just not sharing them with you.
Your job now isn’t to throw more money at IT security. It’s to make sure your contracts, operating models, and vendor relationships finally catch up to the new economics. Stop paying 2016 rates for work that machines now handle. Demand the cost reset that AI has already made possible.
Catch more CIO Insights: Eyes on the Prize: How to Reimagine the “Discovery” Journey in the Agentic AI Era
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