With the ease of availability and access of AI tools and technology, people are putting AI into a wide range of products and services, and even in applications where AI is a dubious fit, at best. Many times, organizations are feeling the motivation, “fear of missing out”, and perhaps customer or shareholder pressure to add AI capability to their offerings.
When we say think big, what this really means is we're trying to solve a big business or organizational problem that is worth solving with AI, because there are a lot of big problems that we can't really solve with AI or are better suited to solve with other approaches. In addition, the big idea that drives the AI investment needs to be long-term enough so that you don’t have to think big every two weeks.
If what you're trying to do maybe incorporates three different patterns of AI, by starting small, we can pick just one of them, and we don't need to be doing all of them simultaneously within that same iteration. This is the core of the first phase of the six-phase best practices CPMAI methodology that is being used to achieve success with AI projects.
So at each iteration ask the question: has this met the objectives? And of course there's only two answers for that. If the answer is yes, that you've done it for that project or iteration and then can move to the next project that supports the overall goals, or iterate the current project in a way that delivers those goals even better.