The Hidden Cost of AI Adoption: Who’s Doing the Heavy Lifting?

AI security tools promise instant threat detection and automated response. But in the real world? Security teams are burning weeks on integration, duct taping workflows, and re-training models just to get basic threat hunting working. While vendors collect ARR, your security team absorbs the hidden operational costs that never made it into the demo. 

This is the part no one talks about: organizations shoulder the heavy lifting while vendors collect recurring revenue for tools that look great in demos, then fall apart in production. In this article, we spotlight expert insights from Glen Willis, Director of Cyber and Technology at Kalles Group, on the often-overlooked operational realities of adopting AI in security environments. 

The Integration Burden 

Most AI security tools assume customer organizations have the time, skill, and resources to handle complex integration. Vendors build products that theoretically integrate into any environment and then leave the rest to you. 

Take a typical AI-powered threat hunting platform. The documentation may claim broad compatibility, but each integration demands custom configuration, data mapping, and constant upkeep. The reality? Most teams find their “AI-ready” stack still needs weeks of setup before the AI can even access clean, usable data. 

The complexity deepens when integrating business systems, identity platforms, asset databases, and network tools. Each connection adds friction, and little of it is supported by the vendor. 

Training: The Invisible Workload 

AI doesn’t come pre-trained for your environment. It ships with a general-purpose model that needs deep customization to align with your organization’s data, threats, and workflows. 

As Glen Willis (Director, Security and Technology at Kalles Group) puts it: 

“Most struggles extend from not having sufficient focus on use cases and intended value realization. Organizations often buy tools that can do a lot of things, which in a way, affects prioritization and operational value.” 

This is where having a partner makes the difference, helping security teams prioritize value, clean training data, validate AI outputs, and continuously refine their models. 

Scaling: Where Operational Reality Widens 

The gap between vendor promises and operational reality widens as you scale. Most tools work fine in proof-of-concept settings, but enterprise scale introduces the messiness that vendors often don’t plan for and rarely support. 

Glen notes: 

“Really sophisticated solutions may be lower touch and easier to roll out. Less sophisticated ones need a lot of engineering skill to optimize. Does the tool need PhD-level prompts? Or can it take natural language and generate precise instructions? Are the outputs all over the place or structured neatly in a console?” 

These are the kinds of questions security teams are left to solve while vendors focus on marketing slick demos. 

The Support Mirage 

Most vendor support is product-focused, not outcome-focused.  You’ll get help with bugs, but not with how to train your model effectively, align it to your team’s workflows, or drive meaningful results. 

And when something breaks, the hardest part is figuring out why. Is it a data issue? A model configuration? An integration gap? 

None of that is addressed in the ticketing system, but it’s exactly what derails your security roadmap. 

Glen explains: 

“Organizations often receive tactical help, but they’re left alone on strategic issues like model alignment or operational integration.” 

Who Does the Work? 

The truth is, most teams don’t have the internal capacity to carry this load, at least not without compromise. And external help isn’t always the answer either. 

“External resourcing is expensive and often lacks flexibility; that inflexibility can be unhelpful.  says Glen. 

The solution? Strategic, on-demand resourcing that can flex with your team, transfer knowledge, and reduce the burden without locking you in. 

The Real Cost Calculation 

AI adoption isn’t just about license fees. It’s also about the people and time required to make those tools work. 

Think about what never makes it into the budget: 

• Preparing clean datasets 

• Modifying infrastructure 

• Ongoing model tuning 

• Integration maintenance 

• Time spent by analysts supporting AI, not defending systems 

AI systems don’t just “run.” They demand attention, iteration, and continuous improvement. 

Where to Start: A 10-Minute Operational Fit Check 

Before you invest more time or dollars, pressure test your AI rollout readiness using this simple framework we use with clients: 

Kalles Group’s AI Operational Fit Check: 

1. Do we have defined use cases tied to business value?
    If your team is exploring features, not outcomes, you’re already off track. 
2. Do we have the right data available and clean enough for training?
    Most AI tools fail here. Garbage in, garbage AI. 
3. Who owns model tuning and workflow alignment?
    If it’s unclear, it’s likely not happening. 
4. Do we know what “good” output looks like,and how we’ll measure it?
    You can’t operationalize what you can’t evaluate. 
5. Is our team spending more time supporting the tool than using it?
   If yes, your AI tool is now your fourth intern. 

Want a copy of this checklist formatted for your team? 

 Message us-we’ll send the quick version and review your responses with you, no strings. 

Building Realistic Implementation Strategies 

Glen is clear: 

“Organizations new to AI need expert help navigating all of this.” 

That’s where Kalles Group comes in. Through our on-demand resourcing model, we can embed: 

• Security analysts 

• Project managers 

• Infrastructure engineers 

• Pen testers and tool specialists 

We don’t just advise, we execute, train your people, and help you scale with confidence. 

Organizations should ask vendors: “What will you support, and what are we on the hook for?” Then build a plan with the right people to carry that load. 

Conclusion 

The hidden cost of AI in security isn’t just financial: it’s operational. It’s the time, labour, and strategy it takes to go from promise to performance. Vendors won’t close that gap for you. But with the right partner, you don’t have to carry it alone. 

At Kalles Group, we embed the expertise and support security teams need to make AI work in the real world. Ready to put your setup to the test? Let’s dive in together, no obligations.