AIを活用した専門サービスの変革への対応

5 Min Read

As AI vendors such as Anthropic release agentic AI tools that eliminate the need for entry-level workers in industries like finance and law, some service industry organizations must consider revamping their business models.

Traditionally, in those industries, experience is gained over time, but with AI agents providing expertise and helping mid- to experienced career professionals earn more, entry-level workers are at a disadvantage.

It's also changing how these service industries price their customers and present their value.

For cloud-based professional services automation vendor Kantata, the answer is to have humans and agents work together and to provide an expertise engine that businesses can use to provide a different metric framework to their customers.

In this Q&A, Kantata's chief product officer, Sarah Edwards, discusses the challenges AI is forcing some service industries and the changes they need to make.

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When we talk about the service industry, how are AI and agents changing the career trajectory for people in entry-level jobs? How long does it usually take for these employees to reach a level of expertise?

Sarah Edwards: When you think about the services business, traditionally, it's an industry that has grown with head count, with people.

It's relied on experts being people. And you have built those experts over the years. I started as a consultant many years ago, and it took me 20 years to become an expert. The world is changing. With AI, it is no longer just people being experts. You have agents becoming experts. Expertise is evolving faster than ever.

Even when you look at the skills of people and the skills of technology, data shows it used to be you worked to develop a skill for five, 10, 15 years. Now it's less than two and a half years, and those skills are redundant. So, when you think about what services a business is selling, it's my people, it's my knowledge, it's how I deliver my projects, it's really evolving, and it's evolving at a rapid pace.

This idea of the traditional pyramid, where you'd bring on a junior consultant, then need people up the pyramid to become senior consultants and partners, is really reversed now.

It's an upside-down pyramid, but at the bottom, I've really got agents. I'm not necessarily looking to bring on those juniors anymore. But I still need my middle- and top-tier experts.

No one's saying that people go away. I need people who are deep experts, but actually, the skills of those people are also changing. Those people need to be able to work with the agents.

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If the roles people play are changing and we no longer need many entry-level professionals, doesn't that create a gap? And if so, how do you fill the gap between seasoned professionals and those just entering the service industry?

Edwards: I don't think anyone magically knows the answer. Again, we've consistently grown people over many years, from doing low-level work to learning along the way and becoming experts. And no longer is that the case. People are expected to be experts overnight. Some of that comes from them working with agents, which enables them to become experts.

You can take your good consultants and probably make them great if you surface everyone's expertise across the business.

So, it's actually a question of: how do I take all that siloed knowledge from all my best people and surface it in a way that enables others to step up and become experts much more quickly than they would have traditionally?

This is really changing, and it is changing quickly. I think the more customers I speak to, and I think last year was a bit of a year of discovery. Still, I think this year, looking ahead, people are now, you know, showing success and really looking at, okay, how does this change operationally, how I run my business, how I build for my work. There's a lot of pressure on consulting and services businesses to drive that adoption and pivot pretty quickly.

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What pivot do people in the service industry have to make in regard to changing their business model and getting up to speed with AI?

Edwards: The problem that services firms really have to solve in this sort of AI native world is expertise. What is my expertise? How does that change? And how do I evolve that quicker than ever?

So Kantata is building an expertise engine, and essentially, what that engine does is take not only the rich data set we've got in Kantata today, but also build a knowledge graph and an engine that understands the business of services.

And then how do you use that to build an engine that is learning continuously from every conversation that someone has with a client, from every project you scope, from every project you deliver?

It's an engine that really connects that data but also understands the business of professional services. It provides the context and really enables organizations to capitalize on that expertise.

A lot of people are using AI at that surface level. Everyone's using an agent to a degree. But are you using that to really transform how you deliver as a business?

I should be resourcing people and agents onto projects. I need to understand the value those agents and people bring. And those agents have a cost. I need to understand the cost of that. People are now realizing, 'Okay, I'm starting to see that we are building some agents to deliver to our customers. Well, how am I now tracking and managing those agents as we begin to provide our services?'

Editor's note: This Q&A has been edited for clarity and conciseness.

About the Author

News Writer, AI Business

Esther Shittu brings four years of expertise covering artificial intelligence technologies and industry trends. As co-host of the "Targeting AI" podcast, she talks to thought leaders and practitioners exploring critical AI developments. Previous to AI Business, she wrote for several publications including the New York Daily News, Bklyner and the Brooklyn Daily Eagle. When she's not diving deep into the world of AI, she spends her time on passion projects and raising her three daughters.