I shared in this post that our research agenda is tracking four large software and services markets – vertical “edge” applications, applications for fast-growing global economies, custom development using low and no-code tools and Generative and other AI.
The interest and noise around Generative AI is off the charts. In my long career in technology, other than the Y2K scare, nothing else has generated this much attention, so quickly. Much of it is coming from:
- Investors – NVIDIA’s blowout quarter and ChatGPT’s eye popping user growth have woken up capital markets after the funk about tech in the last couple of years
- Chicken Littles – many in the media who thrive on anxiety are busy projecting massive job losses from the AI automation
- Politicians – who are never afraid to meddle are fascinated with the opportunity of regulating the new wave of “prompt gurus”
Enterprise Gen AI will be a major focus in one of my coming books. That I can say with some confidence. But in my very next one? Not so sure. My books are full of case studies and use cases, and the early Gen AI ones I have heard about in enterprise settings are still not that compelling. Maybe because they are still early in their deployment, and teams are acutely conscious of “hallucinations” and inadequate audit trails, potential loss of control over their data and IP. In some cases, they will end up with competitive offerings and they don't want to show their cards too early. Vendors, in turn, are being cautious of use cases they promise because they realize the vertical operational data (that will generate the best business payback) is locked up in customer data centers, not in their clouds. Besides, many don’t have explicit customer permissions to use their data to train machines.
I must add that just a few short years ago, I conducted a comprehensive look on automation (robotics, AI, drones, exoskeletons, autonomous vehicles etc across 50 industry settings) for my book, Silicon Collar. It covered over a century of UPC scanners, ATM machines, driver assistance, AI and other technologies. I summarized the findings in this Strategy+Business article and concluded “History shows that new technologies evolve faster than society adopts them.”
In the years since, COVID, Ukraine, climate change and massive digital transformations have turned every industry and country upside down. That is brought out vividly in the new book, we helped SAP executives write titled Business as Unusual.
In this changed world, perhaps Gen AI will have a more rapid impact on businesses. That’s why I am eager to learn about a variety of use cases across industries, business processes and countries. Not just in the back office, also customer facing, product creation, supply chain and vertical operational areas
All this will be sorted out – but it will will take some quarters, not mere weeks.
As Sayan Chakraborty, Co-President of Workday pointed out in his presentation at their AI and ML Innovation Summit in March we have been in a long “AI Winter”.
I am looking forward to the "AI Spring" and writing that book.
