Growth strategy business trend concept.
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When thinking about the application of AI in the business world, there are various approach aspects to choose from. Research the market to see where the opportunities are and solve customer pain points. You can design something that will make your stakeholders and consumers say “wow.” You can try to predict what things will be like in two years, five years, 10 years, and that’s where thought leadership comes into play.
Or you can apply all kinds of jargon. At the intersection of procurement and ROI, you can consider applying AI to SaaS B2B situations. You can consider deploying your 3PL strategy tools to LLM and porting model distillation to the platform.
Okay – maybe that’s enough. Another option is to follow what I’m hearing now from a business ROI perspective. One of these is the “vertical” market.
What is a vertical market?
So what do people mean when they talk about vertical markets?
Well, if you’re a student of English rather than corporate jargon, it’s not a stretch to think that vertical markets will somehow scale up like skyscrapers.
Rather, a vertical market refers to a market that serves a particular “vertical” or business area.
“A vertical market is a specialized business sector that focuses on a specific niche market, where companies tailor their products and services to the unique needs of a defined customer group, unlike horizontal markets, which serve a broader range of customers across industries.” writes Julie Young on Investopedia. “Targeting vertical markets, such as software built specifically for hospitals or financial companies, can provide deeper expertise and potentially higher profit margins. However, vertical markets often have limited market size and high barriers to entry, creating both concentrated opportunities and more intense competition.”
This was difficult to read, so I asked ChatGPT to simplify it for me. Twice. This is what came out.
“A vertical market is when a company focuses on a specific type of customer. For example, it only makes software for hospitals instead of all types of businesses. This may be good because you know that customer well, but there are fewer buyers and more challenges are introduced.”
If I ask it to simplify again, I get this:
“A vertical market is when a company focuses on one type of customer. For example, it makes software specifically for hospitals. It’s more specialized, but it has fewer customers.”
There. That’s better.
Applying AI to vertical software
Perhaps they called it a “vertical market” because it serves a single defined type of business at multiple levels. And by “vertical software” we mean software that serves a specific vertical or customer base, such as hospitals.
With that in mind, I would like you to Part of the panel discussion I saw at Stanford University Recently, a series of experts spoke about this under the title “Applied AI: Transforming industries into innovation engines.” The group included Sri Pangular of Mayfield, Bratin Saha of DigitalOcean, Lisa Dolan of Link Ventures, and Philip Rathle of Neo4J. (Disclaimer: I am also involved with Link Ventures).
The opening panel discussion discussed workflow, training, and knowledge work automation. This is rapidly happening in the context of providing software to various industries and business areas.
Dolan said of his old training:
“If you remember, when we were training junior employees, we wouldn’t allow them to move up to the next level until they were successful in their lower-level tasks,” she said. “So what we need to do is actually train the agents within the companies, the same way we train lower-level employees, so that companies can gain trust and actually deploy it in different areas.”
“This is the first time that we can actually automate knowledge work using generative AI and LLM,” Saha said, listing related domains such as healthcare, finance, and law, to name a few.
“The average cost of employees and knowledge labor is quite high,” he continued. “So if you can automate some of that, you get an ROI.”
Find the core application
“If you just look at day-to-day processes, there are a lot of cost-saving opportunities there,” says Rathle. “But where the real money is and the real value is in the core domains and core applications where the stakes are high. So by definition, when the stakes are high, the quality of a good answer can be very valuable and the impact of a bad answer can be very detrimental.”
Dolan then balances this kind of thinking, suggesting that those tinkering with CRM and other siled ERP components aren’t at risk, but that it’s important to automate centralized processes, while also acknowledging that “you have to walk before you run.”
The panel also discussed pricing.
You have to choose “Ultimately, are you horizontal or vertical?” Rasul said. “The benefit of going vertical is that the higher up the stack you get, the closer you are to the end customer, the more you are perceived to be creating the bulk of the value, and the more you can get people to buy into new kinds of value-based pricing models.”
Dolan talks about moving from seat-based pricing to throughput, and you can hear her explain it all in the video. She concluded her thoughts this way:
“I would say most companies are just wrappers and ultimately dedicate a lot of their ‘lunch’ to Claude. They’re actually looking for companies that own their customers,” she said. “And that means owning the workflow and then owning the learning process. So companies are constantly iterating on their models and self-learning over time, but to do that effectively they need to own their own (sic) customers.”
Rathle agreed. Don’t price AI agents like humans.
“There’s no telling how many people are going to be on the other side of that job in a few years,” he says. “We’ve already seen some of the big players charging per agent and treating AI agents like human seats. And buyers really don’t like that. And it can lead to all sorts of definitional fuzzyness. So this is not a sustainable model in the long term.”
Teammates, not tools
Finally, moderator Pangular asked about making AI “not just a tool, but a teammate” for companies.
“I think it’s going to be an ongoing thing,” Saha said. “It starts with (AI) being a tool, it starts with (AI) being a really, really good tool, and then gradually (AI) becomes a teammate, because I think there’s an element of trust involved in what kinds of tasks you delegate and what answers you get.”
Also…
“I think it’s a continuum,” he reiterated. “You start at a certain point, and you delegate more and more, and you work more and more closely. And then eventually, when you get to a point where some real tasks are handed off, you become real teammates. And in terms of organizational structure, you’ll probably end up with one person managing a bunch of agents. That’s probably where we’ll end up.”
All of this highlights some basic, or perhaps more advanced, ideas about the impact of AI on business. People are or will be automated. Companies will need to analyze cost savings. Agents will become more sophisticated. At the end of the day, we continue to think about the right way to leverage this incredibly powerful technology.
