The Best AI Use Cases Start Where The Business Process Breaks

John Bruggeman, CISSP, consulting (CISO) for CBTS and OnX, both are MSPs and MSSPs.

​Two big problems are showing up in AI projects right now. First, companies are rushing to launch AI pilots before they have clearly defined the business problem they want or need to solve. Second, they can get pretty far into a pilot before realizing they don’t have the security framework in place to support it. ​

For organizations without a pilot yet, or ones that haven’t sunk a lot of money into their project, a good starting point is finding where the process breaks and how AI can help. Folks call this the breakpoint, and every process has one. It’s probably familiar. It is the spot where a decision stalls, data vanishes or the process stops being valuable. ​

Find that breakpoint, put a number on the cost, and identify the risk. When you do that, you get a much clearer idea of what job AI is being asked to do. ​

Common Breakpoints In Business Processes

Here are some examples to make this concrete:

Application maintenance knowledge isn’t written down and is known by just one person.

A programmer knows the systems inside and out and is the one person who patches the system. The cybersecurity risk is a single point of failure compounded by a lack of documentation, sometimes referred to as a “key person” risk. Operationally, the risk is: What happens when that person takes a vacation or leaves? With nothing written down, there is nothing reliable for an AI tool to work from to help automate.

Alert triage lives in an analyst’s head, not a runbook.

A security operations center (SOC) analyst escalates alerts based on years of pattern recognition, but none of that was written down. The cybersecurity risk is inconsistent triage and incomplete data. Feed an AI model incomplete data and it will produce incomplete results really fast. The operational risk is throughput. It is hard to scale and take advantage of AI to triage alerts when the process isn’t documented.