As AI vendors like Anthropic release agentic AI tools that eliminate the need for entry-level workers in industries like finance and law, some service industry organizations should consider redesigning their business models.
Traditionally, in those industries, experience is gained over time. AI Agent By 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 value and present value to their customers.
For cloud-based professional services automation vendor Contata, the answer is to get humans and agents working together and provide an expertise engine that businesses can use to provide their customers with a different metrics framework.
In this Q&A, Sarah Edwards, Chief Product Officer at Contata, discusses the challenges that AI is forcing some service industries and the changes they need to make.
When we talk about service industry, how are AI and agents Are career trajectories changing for people in entry-level jobs? How long does it typically take for these employees to reach that level of expertise?
Sarah Edwards: When you think about service businesses, traditionally, it’s an industry that has grown with the number of people.
It depends on people being experts. And you’ve built up 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, people are no longer the only experts. You have agents who become experts. Expertise is evolving faster than ever.
Even when you look at people skills and technology skills, the data shows that you worked for five, 10, 15 years to develop a skill. 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 would bring in a junior advisor, then require people at the top of the pyramid to become senior advisors and partners, has now actually been turned upside down.
It’s an inverted pyramid, but at the bottom, I actually have agents. I don’t necessarily want to bring in those juniors anymore. But I still need my mid and top tier experts.
No one is saying that people should go away. I need people who are deep experts, but in reality, the skills of those people are also changing. those people need to be able to Work with agents.
If the roles people play are changing and we don’t need so many roles anymore entry level professionalDoesn’t it make a difference? And if so, how do you bridge the gap between experienced professionals and those just entering the service industry?
Edwards: I don’t think anyone magically knows the answer. Then, we have continuously developed people over many years, from doing low-level work to learning and becoming experts. And that is no longer the case. People are expected to become experts overnight. Some of that comes from working with agents, which enables them to become experts.
You can take your good advisors and potentially make them great if you bring up everyone’s expertise in the business.
So, it’s really a question: How can I take all that secret knowledge from all my best people and bring it to the fore in a way that enables others to step up and become experts more quickly than traditional?
It’s really changing, and it’s changing fast. I think that the more I talk to customers, and I think last year was somewhat 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 translate into operations, how I run my business, how I build for my work. There is a lot of pressure on consulting and service businesses to adapt and move faster.
Which axis are people on? service industry Will they have to do something in terms of changing their business model and getting up to speed with AI?
Edwards: The problem that service companies really have to solve in this kind of AI native world is expertise. What is my expertise? How does it change? And how can I evolve faster than ever before?
So Cantata is building an expertise engine, and essentially, what that engine does is not only takes the rich data sets we have in Cantata today, but also builds a knowledge graph and an engine that understands the business of services.
And then how do you use that to build an engine that’s constantly learning from every interaction you have with a customer, from every project that comes under your scope, from every project you deliver?
It’s an engine that actually connects that data but also understands the professional services business. It provides context and really enables organizations to take advantage of that expertise.
A lot of people are using AI at that surface level. Everyone is using agents to some extent. But are you using it to really transform your distribution as a business?
I must provide resources to people and agents for projects. I need to understand the value those agents and people bring. And those agents have a cost. I need to understand its value. People are now realizing, ‘Okay, I’m starting to see that we are creating some agents to deliver to our customers. Well, how do I track and manage those agents now that we’re starting to provide our services?’
editor’s Note: This Q&A has been edited for clarity and brevity.
