Every SaaS and its mother claims to be AI-powered these days, as they endeavor to make the most out of the AI hype train, but there’s a fine line between having Artificial Intelligence and actually being AI-powered. How do you know if a product is truly built around a robust, tried-and-tested core of AI? Or, on the flip side, how can you tell if a software has just slotted in ChatGPT and called it a day?

Setting Your Criteria

As with choosing any new tool, you have to decide what your criteria are. What are your nice-to-haves and your can’t-live-withouts? Do you need one kind of task or a powerful tool that can perform multiple? We’ve compiled a list of criteria to think about when choosing a test automation tool, but that was before the launch of ChatGPT and Generative AI took over the public eye. Now, as with many areas, AI has thrown a wrench into what used to be an established and straightforward process, making it trickier to navigate. So first off, you have to define your objectives.

What problem are you trying to solve?

While this one seems extremely obvious, it’s important to be able to answer this question specifically. If you’re looking for a test automation tool, why do you need one? Whether you’re seeking to replace your current testing tool, upskill your manual testers, or upgrade to low-code/no-code, you should have a very specific objective.

Do you need to integrate with existing systems?

Integrating with your current tech stack is another consideration when picking a new tool. Do you need something that can or do you only need a standalone tool? For example, we use an AI tool for our SEO that really doesn’t need to integrate with anything. I write my articles there and it works on its own. But for test automation, you might want to get a Slack alert or for a GitHub instance to be created if a bug is detected. You may even need a tool that fits into systems beyond the technical, like slotting into your business processes without being disruptive. 

Do you really need AI?

After narrowing down all your objectives, there comes a perhaps unexpected question: do you really need AI to meet your goals? AI, while incredibly versatile, isn’t really needed for every single task. For instance, if you’re trying to write up a piece on something completely new (like our ebook on composable test automation), getting the AI from an AI writing tool to write something up is going to be nigh impossible. Sometimes you only need a particular subset of AI, like Natural Language Programming or a Machine-Learning model to help cut down on those pesky, repetitive tasks. But, of course, there are areas where full-blown AI will be absolutely necessary to fulfill your goals.

What level of security do you need?

Deciding how much security you need is all dependent on your industry and the type of data you are putting through your needed software. Are you a healthcare software housing patient data or an insurance company processing claims? You would need software with a significant amount of security and regular penetration testing to reassure you that any data you run through it is protected to the fullest extent. But if you’re using an AI tool to help with your SEO or something else of relatively low priority in terms of data protection, you might not need anything out-of-the-ordinary.

How much data do you need to handle?

And speaking of data, how much data do you need to process to enable you to make data-driven decisions? One of the things that AI is best at is handling huge amounts of data quickly and accurately, but it can only do so much. Data needs to be clean and prepped to get the best results, so looking objectively at how much you need processed is essential. Finding an AI tool that can help you clean your imported data would be a huge time saver and potentially ensure the data is prepped more accurately so you can make informed decisions to support your business objectives.

Scalability

Most people don’t like switching tools, even if they’re upgrading to an objectively better software, so the last thing you want is to have to switch again because your first pick couldn’t scale with your business. While there isn’t much of a choice in the scalability category, it’s still worth mentioning, as the only viable choice is the capability of handling growth. No matter your business, pick a software that can grow with you. While on-premise platforms are limited by their hardware

Now What?

The above criteria aren’t the only ones you need to consider when going through the evaluation process for an AI tool. There is a wide range of other areas like timeline to ROI, user experience, customization options, an intuitive interface, performance, and more, but these are things that need to be thought through when making an informed choice for any tool. Now you’ve done all this prep, so it’s time for research! Websites like G2 and Capterra are great for getting suggestions for software, and then it’s time for some free-trial and error until you find what you’re looking for. Good luck!