Despite some of the popular fears that all AI agent use-cases could get sucked into a single platform, I'd argue the other side of this for the enterprise.
AI agents, possibly more than any prior era of tech, need to have a relatively high degree of specialization per domain or vertical. The model can be the same across fields, but the manifestation needs to be highly tuned.
The reason is tied to what the AI agent is doing for the customer. What the customer is doing is "renting work" from the AI agent provider. This is similar to when a company either hires someone for a job or hires agencies or firms to help them.
When you hire people, you hire experts. And when you hire consultancies or professional services firms, you hire a bunch of experts in a particular field. There's a reason you tend to not hire people that are "just generalists", and why professional services firms tend to be optimized around focus areas, like tax, IT, legal, marketing, and so on. The consulting firm does everything either doesn’t exist or eventually specializes by practice area.
The same is true for AI agents. Companies are looking to solve problems in their workflow and business processes, and they're going to want experts to solve those problems, not generalists. You're no longer providing the tool for a person to do their work better, but you're actually supplying a worker to them.
For anything important and value-added for that customer, they’re going to want the best agents that they can afford, similar to hiring talent in the rest of the market. Of course for lots of general purpose work this may not be the case, but for anything where their business is on the line it is.
This dramatically increases the need for a deep domain understanding for the use-cases you're going after; custom UI that is tailored to the domain; access to relevant data just for the domain; and so on. The more general you are the worse off the results will be.
Of course there are nuances to this. Generalists can do specialization if they divide things up to approximate specialization well enough. And equally, specialists can accidentally remain too small and not bite off enough of the problem for the customer. But either way, it's clear that specialization is going to win out in AI for the same reason it has in people.
AI agents, possibly more than any prior era of tech, need to have a relatively high degree of specialization per domain or vertical. The model can be the same across fields, but the manifestation needs to be highly tuned.
The reason is tied to what the AI agent is doing for the customer. What the customer is doing is "renting work" from the AI agent provider. This is similar to when a company either hires someone for a job or hires agencies or firms to help them.
When you hire people, you hire experts. And when you hire consultancies or professional services firms, you hire a bunch of experts in a particular field. There's a reason you tend to not hire people that are "just generalists", and why professional services firms tend to be optimized around focus areas, like tax, IT, legal, marketing, and so on. The consulting firm does everything either doesn’t exist or eventually specializes by practice area.
The same is true for AI agents. Companies are looking to solve problems in their workflow and business processes, and they're going to want experts to solve those problems, not generalists. You're no longer providing the tool for a person to do their work better, but you're actually supplying a worker to them.
For anything important and value-added for that customer, they’re going to want the best agents that they can afford, similar to hiring talent in the rest of the market. Of course for lots of general purpose work this may not be the case, but for anything where their business is on the line it is.
This dramatically increases the need for a deep domain understanding for the use-cases you're going after; custom UI that is tailored to the domain; access to relevant data just for the domain; and so on. The more general you are the worse off the results will be.
Of course there are nuances to this. Generalists can do specialization if they divide things up to approximate specialization well enough. And equally, specialists can accidentally remain too small and not bite off enough of the problem for the customer. But either way, it's clear that specialization is going to win out in AI for the same reason it has in people.
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