Artificial Intelligence is an incredibly hot technology, which means IT teams are trying to apply AI tools to almost every problem, even those that AI may not solve well. Here are five questions to ask about any project before diving in.
1. Is This Tool a Security Risk?
AI developers have been busy putting guardrails on their tools to limit information disclosure or inappropriate use, and users are just as busy trying to get around them. Any new tool that has indirect or direct access to sensitive or regulated information must be thoroughly secured and controlled. If this is one of your first AI projects, it may be better to gain experience that doesn’t create a security risk. Starting with tools for internal use only is a better way to get your feet wet than diving right into something that customers or partners will use.
Click the banner below to learn how artificial intelligence can transform your business.
2. Is This Tool Worth the Resources?
Most IT teams don’t think about computing requirements for typical applications, but AI is a different beast. Apps can cost a lot to run, whether on local servers or via cloud-based services. Make sure you have a very clear idea of how much money a given application is going to cost, and make sure the budget is lined up, including for the ongoing cost, right from the start.
3. Is Training the AI Going To Cause a Problem?
There are many types of AI tools, but a lot of buzz surrounds large language models, which require enormous amounts of data to train. When you feed existing data into an LLM, you are training the tool to include whatever biases and inequities exist in that data. For example, you probably don’t want your tool making different product recommendations for customers based on their race. Make sure that the LLM or neural network training gets the real data that matters and not inappropriate or stereotyped proxy indicators.
Click the banner below to read the 2025 CDW AI Research Report.
4. Is AI the Right Technology for Our Needs?
When bitcoin and blockchain first burst onto the scene, lots of IT teams wanted to apply their underlying technologies to almost every problem, even when it made no sense. AI isn’t as niche as blockchain, but it’s not necessarily always the right answer. Make sure whoever is pitching an AI project isn’t going for the buzzword du jour but instead has selected the correct technology to solve a real problem.
5. Is This an Ethical Use of Technology?
AI has real potential to do unintended harm. For example, companies that deploy AI technologies into their hiring practices may unwittingly introduce biases that are illegal or simply unwise. For this reason, it’s important that businesses create responsible AI frameworks before getting started. It’s a good idea for a business to establish an AI Center of Excellence to oversee projects, and ethics should be part of the CoE’s charge.
