While the percentage may be debatable, it is a common fact emerging across surveys that a significant percentage of ML initiatives fail (not Generative AI or deep learning, but ML). You must remember that ML is the fundamental rung on the AI ladder. The high percentages of failures you see do not include the projects initially declared as wins but doomed to fail from day one (Remember Rite-Aid face recognition example?). The fact is, even the most horrible of implementations can be shown as a win, with band-aids that will last a few years till everyone who benefited from the accolades moves on.

Many aspects contribute to this failure, but the most critical one is that when pitched with the promise of new and emerging technologies, we get mesmerized like a deer in headlights. FOMO and the opportunity to be a pioneer internally and in the industry essentially make us jump at these opportunities. The problems that we need to tackle have not changed. Challenges that could have been solved with RFID are not being handled with IoT, with the same dismal failure.

There are aspects beyond technology at play as well that lead to this behavior. Imagine someone in charge of warehouse operations’ “digital transformation” in a senior executive meeting, throwing RFID as a solution. They will be considered archaic, not in league with the latest and greatest in technology. If only we were more obsessed with solving problems rather than technology itself.

There is no doubt that IoT can help build solutions that can be way more innovative than what RFID can deliver. There is no doubt. The issue is that the foundational problems that could (and should) be solved with RFID have not been addressed. This indicates that technology is not an issue. People and processes are.

There are many ways around it. One of them is to challenge technology itself. If there is a new technology on the anvil, rather than getting mesmerized, we need to ask, “So What?”. The technology has the capability, but so what? What can it do for our specific business processes that could not have been done before? Why we could not do it with our existing technologies? The list of questions is long but starts with a simple “So What?”.

The video series that I will start publishing tonight is titled just that – “So What?”.

Every week, we will explore recent developments in AI and ML and apply our “So What?” method to understand what they mean for businesses. What benefits can they deliver? Are there any benefits at all?

The series follows the same approach as the series it replaces – “Think About It”. In “Think About It,” we challenged technology issues at a strategic level. This series is a more granular approach. We concluded the TAI series after 40 consecutive weeks. It was a maverick series that did not seek to earn brownie points. This series aims to do the same.

Because if a majority of us muster the courage and integrity to ask, “So What?” the technology landscape will be much different. It may not make you popular or likable, but cultures and thought processes change one bit at a time. And as Gandhi said, “Be the change you want to see”.