It’s always gratifying when experts confirm what you’ve suspected. Research firm Gartner put a shot of reality into our morning coffee this past summer with its critical analysis that artificial intelligence (AI) had reached the “peak of inflated expectations.” Frankly, I think a lot of technology vendors are blowing smoke about their capabilities.
If your expectations were for Elon Musk-worrying AI, dial them back to the level of business software. It’s actually less mundane than it sounds. AI already has changed how we use data to make sense of our world. It’s also become a corporate fashion. For every AlphaGo Zero there are a thousand firms — startups and established companies — sticking the AI label on their wares like pinstripes on 1980s cars.
I don’t doubt that the last few years have seen significant and rapid progress in AI. What I mistrust is the crescendo of hype, which echoes the tech bubble of the late 1990s and early 2000s. The risk: buying into over-exuberant promises rather than products with a proven return on investment (ROI). Hype clouds our judgment, sometimes intentionally.
If you share my skepticism, but likewise sense an important opportunity and want to avoid excessive caution, here are six questions to help you tune your BS detector.
1. What business problem am I trying to solve?
This is the most important question, and it has nothing whatsoever to do with AI. Granted, a few firms will find value in experimentation, but open-ended projects should be treated with extreme caution. Better to clearly define the business problem you want to solve.
You should evaluate any business investment against three criteria: Will it increase revenue, reduce costs or mitigate risk? Anchoring new technology to at least one of these fundamentals will establish its value. After that, assigning ownership and accountability is the best way to keep a technology initiative on track.
2. Why do I need AI to solve this problem?
Maybe you don’t. True AI acquires and applies knowledge and skills. It’s good for situations in which variability and novelty exist, but it’s difficult to build and therefore commands a premium. Consider the complexity of a self-driving car navigating busy city streets. Does your business problem involve continual unpredictability?
Read the source article at Entrepreneur.