I arrived at Gartner in 1995. My colleagues there were doing Congressional Hearings, had thrown out a number of $600 billion for enterprises to fix the Y2K bug – stuff which woke up CEOs and Boards to their technology challenges. Over the next 5 years, our applications analysts handled a fire hose of client calls about TLAs we had coined – ERP, CRM etc. In my case, it approximated 10,000 30 minute calls (yes!) related to the software vendors and related Sis – we logged every call in a database Gartner had built. The patterns across those calls meant our Magic Quadrants basically wrote themselves.
At Deal Architect, we have already been tracking a stream of new applications this decade. COVID. Ukraine war, climate change and massive digital transformations have made many vertical edge applications viable – telemedicine and personalized medicine in healthcare, EV battery management and billing in utilities, intelligent returns and reverse logistics around eCommerce, Direct to Consumer and related last-mile, small-lot logistics in consumer industries, CPQ for industrials to handle complex outcome based pricing which bundles product, spare parts, all kinds of monitoring and maintenance services, financing etc. And many more for other sectors.
There is also a growing number of applications aimed at rapidly growing economies around the globe – they factor unique business practices and digital trends, local languages, currency, scripts. taxes, regulatory and other nuances.
Beyond these new vertical and geographic applications we are seeing a new generation of AI and data enabled applications. This week at Dreamforce I saw Marc Benioff interview Sam Altman of OpenAI – the man who without needing any industry analysts has single handedly started a new Y2K type stampede. And in addition to the multitude of use cases I heard about during the event, Sam threw out another potential category. In his keynote, Marc had said “They call them hallucinations; I call them lies. These LLMs are very convincing liars.” Sam basically said hallucinations are not a bug, they are a feature. “A lot of value from these systems is heavily related to the fact that they do hallucinate….If you want to look something up in a database, we already have good stuff for that…The thought before was that physical and repetitive tasks would be transformed first before moving on to creative endeavors. The model takes existing data and presents it in different, novel ways (so can be used for creative and strategic work as well)
In a different session, Peter Schwartz, Futurist at Salesforce responded to my question how his Shell (the global oil company) Scenarios Group in the 70s (and comparable ones today) could benefit from today’s AI
“Most people are uncomfortable with uncertainty. They'd rather deny the uncertainty that's inherent in most of the methodologies around things like scenarios. It's not about predicting the future. It's about making better decisions today by looking at the alternatives and managing the risks both the upside and downside far better. I think AI will be a very useful tool in that. Think about it as a current conversational strategic planning partner that presents alternatives. In fact, one of my very first applications of ChatGPT was writing an article on the future of electric vehicles. And I said, give me three scenarios on the future of electric vehicles. And it gave me three really smart ones. I didn't use them literally in what I was writing, but it was a great start. And it was really amazing and actually being able to create alternatives. So when I think about it, frankly, most companies, especially small and medium sized companies, don't have somebody like me working for them. Now imagine an AI strategic planning partner that's trained on various alternatives on the methods. the mathematics of various kinds of models, and can generate real alternatives for small and medium sized businesses”
To Peter’s point about uncertainty, Gartner had taken those scenarios a step further. We assigned probabilities to them and were actively discouraged from publishing any which had a probability of 0.4 or higher. That meant it likely was not bold, edgy enough – it likely did not have enough uncertainty factored.
Couple of weeks ago, reacting to Snowflake CEO’s comments about Nvidia’s blowout quarter, I had written the premium costs driven by GPUs and scarce AI talent would lead to “premium AI applications” being prioritized. Drug discovery, mineral insights, trading patterns, design nuances are some of the use cases which would justify them. I also said “For many vendors, their predictive AI may offer more value to customers than generative AI. If you can preclude unplanned shutdowns of expensive assets with preventive maintenance AI or you can reduce production and logistics footprint, waste and scrap through better demand forecasting AI, that may be exactly what your customers need.”
The good news about Dreamforce (and likely again at Workday Rising coming up in a couple of weeks) I heard plenty of generative AI use cases. Between the vertical, geographic and now AI enabled applications, it should allow the Gartners to come up with a new gen of TLAs. I also heard about CEOs and Boards really energized (trust me, they grudgingly go along with compliance, ESG type projects). Except, that given the shocks of the last few years – COVID, Ukraine etc. – most enterprises have seen their industries and countries radically transformed and they expect a lot more agility than they did around Y2k.
Besides the agility, I hope companies are also less wasteful than they were around Y2K. In the 90s, I saw massive project overruns, plenty of shelfware, suites which underperformed and had to be ring-fenced with best of breed solutions. I also expect enterprises will want their projects to be much more automated. AI should also allow SIs to rethink their labor-intensive delivery models.
I am looking forward to another fire hose of application functionality, architecture and implementation conversations. It’s the got the same feeling I got when I got to Gartner in 1995.
As Yogi Berra famously said: "It's déjà vu all over again."
