This is one in a series of posts with excerpts from our new fiction mystery book, The AI Analyst (click on badge on left to go to the Amazon page with description, sample download, reviews etc.)
At CES this week, Jensen Huang of NVIDIA showed his vision of the evolution of Digital Agents. Satya of Microsoft and Benioff of Salesforce have been talking up Agentic AI quite a bit, Jensen is thinking of the next evolution where agents don’t just focus on white collar tasks but also physical, blue collar and trade related.
I would like to introduce you to Barry Roman, a key character in the book and his company, Polestar. That is a next-gen tech vendor which combines agentic AI with humanoid robots, drones, UAVs etc. Not just a software or silicon focus. Polestar has an expansive definition of its verticals as each of the 800+ occupations the Bureau of Labor Statistics tracks. Their solutions automate limbs, eyesight and other human faculties, not just cognitive skills.
In a scene, before Barry presents, there is a slick video which show Polestar products on shop floors, hospitals, labs, delivery trucks, and warehouses. Barry then enters the stage led by one of his robots doing backflips, and another walking menacingly next to him as his bodyguard. Four drones they make fly into the audience, with two of them dropping music boxes at a couple of tables. When the boxes were opened, they played Lumiere and friends singing “Be Our Guest” from Disney’s Beauty and the Beast. One of the drones with sensitive mics amplifies the music, and the other with a high-resolution camera projects Barry and the bots on stage onto a large screen.
In a scene which did not make the final cut in the book, Barry becomes convinced about a focus on micro-verticals when he asks his team to bring in his father, a retired fireman, as an adviser while working with a fire and rescue customer. “Barry, all they have bought from you is some crew scheduling software. Give me a team for a week and I will show them technology a modern fireman uses and you could be selling in addition” That opened their eyes to wearable sensors, augmented reality, thermal vision glasses to allow firemen to see through smoke and fire, drones with sonic fire extinguishers to create acoustic boundaries to prevent wildfires from spreading, using AI to monitor imaging feeds from fires and so much more.
There is a scene where Barry visits the GE Global Research Center in Upstate New York and at lunch, he finds himself surrounded by chemical engineers, astrophysicists, and nuclear scientists. This was, of course, back in GE’s glory days, and the Center had over 1,500 technologists, many with PhDs covering every STEM (Science, Technology, Engineering, and Math) discipline. He challenges his executives to build him one of those centers. He tells them: ‘I want us to be able to boast about Nobel Prize winners on our staff too.’ Of course, they had to manage his expectations—GE had 30 to 40 times more revenue than Polestar at that point.
Polestar is easy to do business with. Barry never fails to point out to his sales team how easy he had made it for retailers to contract their warehouse bots. “Not everyone is an Amazon and needs large distribution centers. We saw a growth in smaller warehouses located close to customer demand. I told Swanson (the CFO) to offer our bots as-a-service, and deliver as few as five as a start. Then seasonally we would deliver five or 10 or 15 more bots, as their customer demand spiked. Customers loved this flexibility, and it was one of our most successful product introductions.”
There is other discussion around LLMs, narrow models, KV cache in GPU RAM and other AI lingo. There is plenty of cyber crime in the book.
Don’t worry - it is a fast paced read with plenty of SV glamor and settings, not a geeky book. But read it to see that something like Polestar is not just fiction. Companies like that are being imagined and funded as we speak. Jensen, Marc and Satya’s vision is being given real life business context and ROI by someone like Barry.
The next-gen technology analyst and AR
This is one in a series of posts with excerpts from our new fiction mystery book, The AI Analyst (click on badge on left to go to the Amazon page with description, sample download, reviews etc.)
I previously excerpted about next-gen vendors like Polestar and next-gen buyers like Sheldon Freres from the book. Lots of ripple effects from these changes are also causing technology analysts and AR to evolve.
Oxford Research is headquartered in Cambridge, MA but has recently opened a new executive briefing and research center on the waterfront in St. Petersburg, FL. It is hosting an analyst offsite there and lots is discussed about the past, present and future of the analyst world and how they are now using LLMs and copilots and have their own labs for product testing.
A fireside chat between Tucker Newberry, the CEO; Martha Weingarten, the Head of Research and Patrick Brennan, the Chief Analyst sets the stage
“After the golf, the beach, and the Dali, the guests got changed in their rooms at the Vinoy and proceeded to dinner. The group included all the analysts and research staff, as well as six client executives—three from vendors (including Polestar) and three from user organizations. These executives each sat at the head of a table and chatted with Oxford folks about their IT projects and market intelligence needs. There was lots of chatter about Generative AI in particular though most shortened it to GenAI
After dinner, Tucker kicked off the proceedings. He had founded Oxford Research almost 30 years ago and had watched it grow to its present dominating position of helping IT professionals making technology decisions…. “Boy, did we have executive access!” Tucker exclaimed. “I spent many weekends working with CEOs of the largest corporations in the world—often at their beach houses.”…
Martha: “I have mentored a number of analysts throughout my career. Good analysts have two qualities—they are both curious and skeptical...One of her favorite expressions, even today, was “Sacred cows make the best hamburgers.” She described how she once tore apart a vendor presentation: “You are allowed to be stupid or lazy, but not both.”
Tucker and Martha discussed the Gartner IPO in 1993 that literally made hundreds of analysts, overnight millionaires. It led to a glowing New York Times article, from which Martha read a quote: “Gartner may well be the richest publishing house in the world—a ‘mini-Microsoft’ in its field.”
Patrick had been worried that the audience would be bored with this walk down memory lane. Then he saw that even the youngest analysts were listening closely. Few of them knew much about the history and evolution of the technology analyst profession.
Martha said, “But that was decades ago. If you put today’s enterprise applications on a grid of industries and countries, Gartner today barely covers 25 percent. And they have nowhere near the access they once enjoyed to the technology buyer. They make vendors fill out long surveys for their Magic Quadrants (their equivalent of Oxford’s Golden Circle). Vendors, in turn, use a cottage industry of ‘analyst relations’ advisers who coach them how to game their responses. It’s become formulaic—and analysts still cling to application categories which have been around for decades.”
Tucker summarized, “So we need to catch up to the velocity of change in business, not just technology. Clients don’t want to merely read our research and talk to us on Zoom calls. They want customized advice. They still want it in bite-sized chunks, not long projects. But they want us to present it coherently. Nothing annoys them more than being handed off from one analyst to another. They have complex problems and they want us to respond accordingly. We also need to recognize that there are other critical markets we should be analyzing. The Russian invasion of Ukraine showed us we will be dependent on hydrocarbons for a long time. How do we use fossil fuels while neutering their emissions? We should be able to talk authoritatively about carbon capture and storage, and about the total cost of ownership of electric vehicles. Honestly, if I was starting my career today, I would join an energy research firm. Or a healthcare research firm. In the US, nearly a quarter of our GDP is spent on our health and yet our outcomes are miserable. Or look at how the world is changing. So many emerging countries are becoming the ‘new world.’ They’re growing much quicker than the US, EU, China, and Japan. We have an opportunity to help multinationals rebalance their global portfolios and help customers in those fast-growing economies. I don’t want to steal his thunder, but Patrick will talk more about these new horizons tomorrow. Don’t get me wrong. IT, especially AI, will keep us busy for a long time. But it was such an invigorating time that Martha and I experienced in the ’80s and ’90s. There’s no reason we cannot recreate that excitement again, in a variety of new directions. The technology world today feels like it did back then.”
Patrick discussed several new markets
“COVID, the 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 sectors, CPQ for industrials to handle complex outcome-based pricing which bundles products’ spare parts, all kinds of monitoring and maintenance services . . . the list is virtually endless. There’s also a growing number of application areas aimed at rapidly growing economies around the globe—they must factor in unique business practices, local languages, scripts, currencies, taxes, customs, payroll, and other nuances. Beyond these new vertical and geographic applications, we’re seeing a new generation of AI and data-enabled applications. The vertical and global data sets of most enterprise vendors are skin deep. Given how expensive GPUs and good AI talent is likely to be for the next few years, enterprises will prioritize unique products and market-insight projects, like drug discovery, mineral insights, product design advantages, trading patterns, etc. Smart customers will protect that data for themselves, train their own large language models, or LLMs, and commercialize that data asset. Vendors will continue to generate proposals, job descriptions, demand forecasts, etc. with their AI—clearly useful stuff, but not deserving significant premium pricing. We need to be associated with the first group of customers, the smart ones.”
Patrick next invited Henry Novak, the head of Oxford’s labs, to show off the AI copilot named Curmudgeon that Oxford analysts were busy developing. It would access tools like OpenAI and Google Gemini to gather news, reports, and press releases about vendors. It would also tap into Wall Street and other proprietary databases for more vendor analysis. In addition, it would access Oxford’s own client query database to see how corporations were using vendor capabilities. Finally, analysts would enter details from vendor briefings, vendor events, their own observations on each vendor, and their competition. The human expertise would validate and enrich the machine learning. The tool would help generate first drafts of Oxford’s twice-a-year Golden Circle report foreach market category. The analyst group clapped loudly when Henry finished describing the multifunctional tool. Several analysts offered to be guinea pigs for the project.
Next up was Irene Kaplan, an “AR consultant.” Raised in the public relations world, she now helped vendors make themselves more coherent to analyst firms like Oxford. She had the audience in titters as she shared anecdotes and “inside baseball” stories of what vendors thought of individual analysts. She highlighted “Bill Lou”—the analyst who spoke with a pronounced Southern drawl like the senator from Louisiana, but with devastating impact. And Megan Lewis—Ms. Multitasker, who was physically at one event while tweeting about another on the other coast. And Jean DePasquale, who asked softball questions but made sure he announced his name and company, so it would become part of the event transcript. And “Vinnie Vertical,” who managed to squeeze in a healthcare, banking, or automotive sector question at every event. All super sharp, all quirky.
Talking about quirky, she shared with them that she, too, had built an AI tool, called Gideon—presumably out of respect to the late founder of Gartner—to keep track of analysts with details on their spouses and hobbies, links to their latest research, and more. “It’s fascinating how many analysts are good musicians. One of you has amassed a giant collection of mobile devices, covering the last couple of decades. Another has a collection of soda cans from around the world. A couple of your peers have been to over 100 countries. It is amazing how many of you know the byzantine rules of the game of cricket.”
Patrick made a note to talk to Irene and compare Gideon, Curmudgeon, and Sherlock, a law enforcement digital agent that Henry’s team had developed and which Polestar was now enhancing and commercializing.
Irene then changed tone. “You analysts are under the delusion vendors want your intelligence. They may pretend to, just to stroke your ego. The vast majority of them want you to take their slides and just include them in your research reports. They seem to forget if they can convince you to do that, so can every one of their competitors. Honestly, they should use you more for intelligence. It should bug the heck out of them their customers have 100, 400, or 900 application vendors. Each of them is just a small piece in the customer’s jigsaw puzzle.”
A vendor executive in the audience raised her hand and said, “Irene, not a question, more of a suggestion: Don’t spill our secrets to all these analysts.” Everyone laughed."
There are plenty more angles in the book about analysts and vendor AR.
Don’t worry - it is a fast paced read with plenty of SV glamor and settings, not a geeky book. But read it to see why a buyer like Sheldon Freres or a vendor like Polestar is no longer fiction. And why we need next gen analysts like Oxford and next gen AR to keep up with rapidly changing technology markets.
January 13, 2025 in Agentic AI, Humanoid Robots, Industry Commentary, The AI Analyst - a fiction thriller, Vertical Applications | Permalink | Comments (0)