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Chapter 1: What is the main topic discussed in this episode?
Hey, What's News listeners. It's Sunday, March 29th. I'm Alex Ocele for The Wall Street Journal. This is What's News Sunday, the show where we tackle the big questions about the biggest stories in the news by reaching out to our colleagues across the newsroom to help explain what's happening in our world. On today's show, agentic AI is the buzziest word in tech right now.
AI agents are taking on tasks like tracking customer orders and making restaurant reservations. And the next generation promises to be even more powerful, becoming kind of like a personal assistant. But AI agents also come with big risks, even as they may stand to finally help tech companies make money off artificial intelligence. Journal tech reporter Isabel Bousquet joins me to discuss.
Isabel, when developers or companies refer to an AI agent or AI assistant, what do they mean? Like, what is that?
This is a very overhyped, overused term, and I don't think the industry has a common definition. But at its base, an agent is an AI that can do something for you. It becomes agentic when you say agent. make this restaurant reservation for me, book this doctor's appointment for me, book this flight for me, buy this dress for me.
Anything where it's going out into the world and executing some behavior on your behalf, that's the point at which it becomes an agent.
When companies talk about using AI agents, how are they using them?
We're seeing two kind of big categories emerge so far.
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Chapter 2: What are AI agents and how are they currently being used?
One is in the coding space. There are a million companies that offer this from the Cloud Code and OpenAI Codex of the world to Cursor, Replit, Lovable. Everyone has an AI coding agent these days. Engineers are using this a lot. The other area we've started to see agents take off is in customer service.
It kind of grows out of the traditional phone tree technology that was not really AI-enabled at all. But now it can be. If a customer calls with a question about where their order is, an AI agent can handle that call and give status updates or replace a missing loyalty card or things like that.
How do these tools actually help companies make money?
We know companies are spending a lot of money to use them. If we take engineering, this is the example a lot of people use because it's just the most mature use case by far. So every time a coder uses an agent, it costs money. It costs what they call tokens. And some companies give their engineers a certain allotted number of tokens.
And some companies are more flexible, saying have as many tokens as you want. But some companies compare the salary of the engineer to the amount of tokens they're using. And they're saying that in a lot of cases, this person is costing more in tokens than they are an actual salary. But on the flip side of that, they're also looking at the amount of work this person is doing.
And they're saying this person is being like 10 times or 50 times more productive than they would if they didn't have a coding agent. So although they're costing two times an engineer salary, they're delivering like 10x of what an engineer can do. So that's how they're weighing the returns at this point.
The kinds of agents we've been talking about are out there in the world, but there's something else that's coming, right? And it's something called OpenClaw.
Yeah. So OpenClaw is an open source orchestration framework. For it to be a true personal assistant, you have to give it access to everything, which is a huge security concern because there have been instances where it goes and deletes a bunch of your files or deletes a bunch of your emails or It could get your credit card into a fraud situation.
It's very insecure, but the potential is massive for you to just connect it to everything in your system and all of your logins and all of your data. And then these agents, they're doing all these complicated things. You can set it to do a task and then walk away. It's just become this whole other level in terms of what agents are capable of doing.
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Chapter 3: What distinguishes agentic AI from traditional AI assistants?
This is the new computer.
Isabel, what is the promise for this next generation of AI agents for companies?
Jensen's saying every company needs to have an open-close strategy was really bold. It's hard to know how different an open-close strategy needs to be from... and agent strategy. The potential for businesses is vast. And I think the direction this is all going is that knowledge workers will engage with fewer and fewer interfaces.
And if you could think about a way, way, way future state as a knowledge worker, you might just have to engage with your open-claw agent. The agent handles the back end of everything. And you just have a much simpler, cleaner experience.
Coming up, the risks that agentic AI brings with it, and where AI agents go from here. That's after the break. Isabella, what are the risks that come with the use of agentic AI?
The idea that an agent can take action is great, but also not great for businesses because an AI, by its nature, can hallucinate. It can get things wrong. If you're issuing a customer a refund, what if you issue them, like, too big a refund? Or what if you promise them a deal that doesn't exist? You have to put a lot of faith in the agent. In order to let it act fully autonomously.
So a lot of companies still want to have a human in the loop. They want the agent to do a lot of the legwork and then the human employee can sign off on that. And then agentic shopping is going to be a huge trend, like giving an agent your credit card information and saying purchase this item. shirt for me when the price hits $50. But what if it purchases it for you? Well, the price is still $80.
If you're a credit card company, the one that operates that credit card that was used, are you liable? Is the AI liable? How responsible are people for the actions their agents take? And can agents be hacked to give away your personal, sensitive, valuable data, things like your credit card information? So, there's a lot of unknowns and a lot of security concerns.
It sort of harkens back to the early days of the internet when people were afraid to put their credit card information to buy anything online.
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Chapter 4: How are businesses implementing AI agents in coding and customer service?
Companies are making more money on a per-employee basis than they have in the past, but companies This is something that's just very hard to measure. And so I think a lot of companies have given up on the phase of we made X percent return on the amount of money we spent on AI and have just accepted that this is a necessary technology for them to be using as a company.
And even if they can't prove it out with a specific number value, that doesn't make the investment all worth it.
One of the other bigger conversations that's going on in this moment is particularly investor skepticism about what AI means for companies built around software. Some people are calling it the SaaSpocalypse, referring to software as a service. What does the rise of AI agents tell us about where that conversation is headed?
The rise of these super capable AI agents is another thing that puts pressure on these traditional legacy SaaS companies, especially the coding agents, because that's where you saw a lot of the SaaSpocalypse fears stem from, which is with this great new coding agent, I don't need those expensive legacy providers. The more nimble startups with
super cutting edge AI agents we see, the more pressure it does put on those companies. From what I've seen, most of those companies are pretty aware of where things are headed and they've made huge investments themselves in agents. If you take Salesforce as an example, they're making it very front and center in terms of their strategy.
I think it's just a question of how fast can those companies move and how good are the agents they're building compared to the AI-native startups and the agents they're building.
That was Wall Street Journal tech reporter Isabel Busquets. Thanks, Isabel.
Thanks again for having me.
And that's What's New Sunday for March 29th. Today's show was produced by Pierre Bien-Aimé with supervising producers Tali Arbel and Melanie Roy. I'm Alex Ozola, and we'll be back tomorrow morning with a brand new show. Until then, thanks for listening.
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