How to Tell If That AI Tool Will Actually Help Your Business

Entrepreneur

2 days ago

Just like loading up your kitchen with chef-worthy appliances won't automatically make you a better cook, cluttering your life with new AI tools won't necessarily make your business more efficient or profitable.
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The first time I used ChatGPT, I was blown away. Both with its capabilities at the time, but also because of what I knew it represented for the future. From that first prompt, my mind began to race with the possibilities for my business: automated customer support, faster product development and my personal favorite, an even more ruthlessly tamed inbox. Like many founders, I felt like I had discovered a secret weapon.
But that excitement quickly gave way to overwhelm. New AI tools were launching every day — each one promising to boost productivity, streamline operations or revolutionize how Jotform's teams worked. The question became: Which ones were actually worth using? And which ones were just a lot of hype?
If you're running a business today, you've likely felt the same. AI usage has surged in the last few years, with 78% of businesses having integrated it into operations in at least some way, up from just 55% in 2022.
But not every AI tool is useful, and some are a waste of time. Just like loading up your kitchen with chef-worthy appliances won't automatically make you a better cook, cluttering your life with new AI tools won't necessarily make your business more efficient or profitable. Learning to vet AI tools — quickly, strategically and without getting distracted by inflated promises — is a skill every business leader has to develop. Here's how I do it.
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Start with the problem, not the tool
These days, even pet food bowls are wired with AI capabilities — quite unnecessarily, according to some.
Before you even begin wading into the deep waters of AI solutions, take a step back and ask yourself about the problem you're trying to solve. It's easy to get swept up in the latest platform everyone's talking about, but if it doesn't address a real bottleneck in your workflow, it's just a distraction.
For example, don't start with "We need an AI chatbot." Start with "Our support team is overwhelmed, and response times aren't as fast as they could be." That shift in mindset helps you focus on outcomes, not features. Maybe a chatbot is the answer — but maybe it's not. Maybe you need a better knowledge base or smarter ticket routing.
When you anchor your search in a clearly defined pain point — whether it's wasted time, high error rates or missed opportunities — you're far more likely to find an AI solution that delivers real value. Otherwise, you risk solving problems you don't have with tools you don't need.
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Beware of over-promises and jargon
As much as AI is legitimately transforming how business is done, its genuine value risks being drowned in a wave of unrealistic expectations. In fact, Pomona College economics professor Gary Smith argues that generative AI companies need to generate an estimated $600 billion annually to justify current investment levels — which he believes can't be done. It calls to mind the dot-com bubble of the 1990s, which infamously burst after revenue failed to live up to sky-high projections.
That's why it's so important to approach AI tools with a healthy dose of skepticism. One of the clearest signs a product or feature won't deliver is when its pitch is heavy on buzzwords and light on substance. Terms like "revolutionary," "ground-breaking" or "fully autonomous" might sound exciting — but they often mask the fact that the product doesn't do anything specific, or doesn't do it well. If a tool claims to "automate everything" or "replace your entire workflow," be skeptical.
Instead, look for products that explain exactly what they do: "automatically tags customer support tickets based on urgency," for example, or "summarizes meetings into bullet points within Slack." Bonus points if the product page includes examples, integrations and known limitations. Any worthwhile tool will be backed by clarity and transparency. If you can't tell what it actually does in under a minute, it's probably not worth your time.
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Assess time-to-value
When evaluating an AI tool, one of the most important questions to ask is: How quickly will I see value? Time is an entrepreneur's most limited resource, and anything that requires long onboarding periods, extensive training or complex integrations may not be practical, especially in the early stages. There are exceptions, of course, and I'm a firm believer in the principle of spending time upfront to make time down the line.
But you also don't want to lose hours — or days — of your life establishing a complex system that may not deliver. A strong AI tool should prove itself quickly. You don't need perfection on day one, but you should see traction — whether that's more streamlined lead generation, quicker task completion or fewer manual errors — within the first week or two.
I like the advice offered by Vox senior tech correspondent Adam Clark Estes, which is to start by having AI "do something annoying that you've been meaning to do but haven't had the time."
For him, that meant meal planning. For entrepreneurs, it might mean summarizing a stack of unread meeting notes. If the tool can lighten that kind of mental load right away, it's a good sign you're on the right track. If it requires weeks of setup before you even know whether it works, that's a red flag. Look for low-friction onboarding, quick wins and simple ways to test it using your own data. In other words: Don't just buy potential — buy measurable progress.
Just because an AI tool claims to do something doesn't mean it does. Entrepreneurs are constantly pitched solutions that promise to save time, unlock productivity or give us a competitive edge. But ultimately, it's up to us to separate the truly valuable from the noisy distractions.