WSJ What’s News - AI Agents Like OpenClaw Are Here. How Can You Use Them?
Episode Date: March 29, 2026AI agents—artificial-intelligence tools that can perform real-world tasks—are the buzziest thing in Silicon Valley. Some businesses and individuals are already using them, and the next generation ...of agents like OpenClaw could be even more promising. But they also come with significant risks. WSJ tech reporter Isabelle Bousquette joins host Alex Ossola to discuss how agentic AI is being used now and how it could be used in the future. Further Reading: China’s OpenClaw Craze Buoys Tech Stocks, Fuels AI Pivot The World’s First Viral AI Assistant Has Arrived, and Things Are Getting Weird This Viral AI Project Went From Side Hustle to Coveted Prize in Three Months Nvidia Software Aims to Bring OpenClaw to the Enterprise Silicon Valley’s New Obsession: Watching Bots Do Their Grunt Work Mark Zuckerberg Is Building an AI Agent to Help Him Be CEO Learn more about your ad choices. Visit megaphone.fm/adchoices
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I think the potential of Agenic is to rethink how work gets done overall.
It challenges all sorts of traditional orthodoxies around how organizations execute the work at hand.
That's Jason Gersatus, CEO of Deloitte U.S., talking about the transformational potential of Agenic AI.
Join him later to learn why agents are a game changer for businesses across industries.
Hey, what's news listeners. It's Sunday, March 29th.
I'm Alex O'Sullough 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 busiest 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 Busquette
joins me to discuss. Isbel, when developers or companies refer to an AI agent or AI assistant,
what do they mean? Like, what is that? This is a very overhites, 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, 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. One is in the coding space. There are a million companies that offer this
from the Claude Code Codex of the world to cursor, replet, lovable. Everyone has an AI coding
agent these days. Engineers are using this a lot. The other area we've started to see agents takeoff is
in customer service.
grows out of the traditional phone tree technology that was not really AI enabled at all.
But now it can be of a customer calls with a question about like 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.
OpenClaw was acquired by OpenAI last month, but other companies are getting on board with what agents like OpenClaw can do.
Here's Infidia CEO Jensen Wong speaking at the company's annual developers conference earlier this month.
Every company in the world today needs to have an OpenClaw strategy, an agentic system strategy.
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-cloth strategy was really bold.
It's hard to know how different an open-cloth strategy needs to be from an 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.
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Isabel, 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 shirt for me when the price hits $50.
But what if it purchases it for you?
while 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. What's sort of heart concerns? What's sort of hard
back to the early days of the internet when people were afraid to put their credit card information
to buy anything online.
Tech companies have been investing hundreds of billions of dollars into AI.
Are AI agents finally the way that AI makes companies money?
I don't know if we've seen that prove out yet.
It still seems like companies are investing a lot of money to use AI.
And it's been hard for them to point to a clear example.
example of an actual financial return. In a lot of ways, those financial returns are linked to the
size of the workforce they have. And so if they do layoffs and say, we're being a lot more
efficient with AI, is that an example of a return? So I do think over time, there will be some
right sizing of the workforce based on the fact that companies now have all these AI capabilities,
but that kind of seems like a longer-term horizon.
I do think revenue per employee is going up.
Companies are making more money on a per-employee basis than they have in the past,
but this is something that's just very hard to measure.
And so I think a lot of companies have given up on the phase.
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 not 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 SaaS Apocalypse 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. Like if you take Salesforce as an example, like 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
Lusket. Thanks, Isabel. Thanks again for having me.
And that's what's new Sunday for March 29th. Today's show was produced by Pierre Bienname,
with supervising producers Talley Arbell and Melanie Roy. I'm Alex Ocelah, and we'll be back
tomorrow morning with a brand new show. Until then, thanks for listening.
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