4 Tactics For Picking The Right AI Solutions For Your Company
AI is everywhere—at least from a high-level perspective. But does it belong in your business? That depends.
There’s little argument that AI offers companies plenty of capabilities and opportunities, and most executives know it. When polled by PwC, 86% of professionals said AI was a fairly established part of corporate life. Yet even if it’s mainstream, AI shouldn’t be treated as just another tool.
To get the most out of AI, you have to understand it first so you can deploy it strategically in the way that makes the most sense for you, your team, and your goals. Ultimately, you’ll optimize your spending and get the most out of every solution and system you bring into your organization. The following steps will help you figure out how to bring AI into your fold.
AI can do quite a lot. Nevertheless, it isn’t right for all situations. For example, if you want to aggregate and analyze large pools of data, AI can be helpful. The same holds if you’re interested in adding an AI-powered chatbot feature to your website to give customers self-service mechanisms.
What if your focus is on driving innovation within your company, though? AI can’t brainstorm on its own. An AI-enhanced program may be able to help your employees come up with concepts, of course. However, AI itself won’t turn out clever ideas because it has limitations that the human brain doesn’t, namely that it doesn’t really think or have common sense, as pointed out in an MIT Technology Review by Boston Globe writer Brian Bergstein.
So, where can you begin if you want to weigh the pros and cons of AI for your company? One method to sift through all the information available about AI is to determine how your industry competitors use it. Then, evaluate whether those uses will be just as advantageous for you. By being selective, you can make well-informed choices.
It can be tempting to bring all kinds of AI products into your tech stack simultaneously. However, making too many sudden changes could backfire. Plus, you might not be able to tell which AI solutions are working and which ones need to go.
To avoid this problem, Tiago Ramalho, the CEO of AI consultancy Recursive, recommends taking a scientific approach by setting up small tests. “Break [AI] down into minimum viable objectives,” writes Ramalho. “Develop a model for the lowest-hanging fruit and build up from there.” He points out that tackling everything in micro-bites will show any flawed assumptions quickly. When they appear, you can address them right away.
