When someone says, “We should use AI,” I think the first step is understanding the problem they are trying to solve rather than immediately choosing an AI tool. I would ask questions such as: What specific challenge are we facing? What outcome are we trying to achieve? How would AI improve the current process? I would also consider whether AI is the right solution, what data it would need, and any potential risks involving privacy, security, accuracy, or bias. For example, if a company wants to use AI to improve customer service, we should first determine whether the goal is to reduce response times, improve customer satisfaction, or lower operating costs. Ultimately, AI should be used with a clear purpose, not simply because it is available or popular. The focus should be on identifying a real problem, determining whether AI adds value, and establishing measurable results while maintaining human oversight. Saving Changes...
Here's an answer you can use or adapt: I start by shifting the conversation from the technology to the problem. I ask what business problem we're trying to solve, what's not working today, and what outcome would count as success. Then I check whether the problem actually calls for AI, or whether a simpler fix like automation, better processes, or rules would do the job. If AI does fit, I identify what the system needs to do: recognize, predict, detect anomalies, personalize, converse, optimize toward a goal, or act autonomously. That maps the request to one or more of the seven AI patterns. Finally, I confirm we have the right data, involve the people closest to the work, and set clear expectations that AI should support human judgment rather than replace it. Saving Changes...
From a cybersecurity perspective, “we should use AI” is a prompt to ask: “For what, and with what safeguards?”
Artificial intelligence can detect threats, manage alerts, and prioritise vulnerabilities. But it can also expose sensitive data, make errors, expand the attack surface, and give attackers better tools.
Before you adopt it, clarify the problem it solves, the data and access it requires, how you will measure success, and who will review its decisions. Use least privilege, protect data, test and monitor the system, and keep human oversight for high-impact actions. Saving Changes...
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