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The Morning Download: The ChatGPT-ification of American Business

By Steven Rosenbush | WSJ Leadership Institute

 

Thomas R. Lechleiter/WSJ

Good morning. Amidst the relentless wave of AI news, an important shift merits attention. OpenAI in recent weeks has seen a surge in businesses publishing so-called ChatGPT apps, including rollouts from Starbucks, Little Caesars Pizza and Wyndham Hotels last month.

The Wall Street Journal Leadership Institute’s Isabelle Bousquette reports on how these apps allow users to engage with brands directly inside the ChatGPT interface.

Often they will take users right up until the point of action, directing them to Little Caesars’s own mobile app or website, for example, when they are ready to place or pay for an order. OpenAI announced the capability in October 2025 but said it recently streamlined its process for approving apps.

 
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“We wanted to meet our customers where they are,” said Neelima Sharma, senior vice president of omnichannel and e-commerce technology at Lowe’s, whose ChatGPT app went live in February.

Isabelle found that the business value of some of these apps remains hazy, with brands citing issues with discoverability, data sharing and ownership of the customer relationship as challenges that still need to be worked out.

An OpenAI spokesperson said the company is seeing strong momentum around apps, with hundreds of apps live and new apps launching every day. The company said it recognizes there’s more work to do to make the experience better for brands and users alike. Over time, it expects ChatGPT to become the primary way many users interact with the products and services.

Is your company operating an app within ChatGPT, or does it plan to make that move? Let us know how it’s going.

 

On Tech Leadership

IBM CEO Arvind Krishna Steven Rosenbush

IBM CEO Arvind Krishna’s AI Risk Framework. My recent conversation with Krishna focused on how companies need new operating models as they scale AI. You can read that story here. We also spent a lot of time talking about his framework for assessing the right level of risk for IBM, especially when it comes to AI.

Here are edited highlights from that part of the discussion.

WSJ Leadership Institute: You argue that technology may be more important than a company’s balance sheet. How so?

Krishna: It’s a simple way of saying, “what's most important for a company to survive?” If you look at the long arc of history, it used to be physical security. Great, I have armies, I can protect myself. I have lots of people. Fast forward, it kind of went to the knowledge economy, the strength of my workforce, the talent that allows us to succeed. I think now it's technology that allows people to succeed...

Pre-internet, technology was probably a productivity (driver) and a cost saver. I don't think it allowed you to triple your business if you could use technology well. Now, you can.

WSJLI: You elected not to join the race to develop frontier large language models. Why?

Krishna: Many will thrive, some will disappoint. So that goes to the first question, is there real value? And the answer here I think is unambiguous. There's absolutely real value. We can use this to make companies far more productive. We can use it to generate a lot more revenue.

Why do I say that some will disappoint? I think that very large models -- you can switch between them. It is a cruel way of saying that it is a commodity. But it is a commodity like gold is a commodity. It's a valuable commodity. But if that's true, that means that the ones who are competing can only derive a certain price, they can't just take price … to the heavens.

So then I just do some simple math.

Over 100 gigawatts have been committed over the next three to five years.

It takes about $80 billion dollars to completely fill up a gigawatt (data) center, and I'm not counting the power investment and all that because that is often outside these companies' balance sheet. But filling up the data center is usually on a tech company's balance sheet.

If you put that much capital in the ground, what do you need to pay for it? So you need on the order of $2 to $4 trillion of revenue per year. Is that all moving out from current tech? Can I have that much incremental? I think that is tough. Maybe $1 trillion could be incremental. So that says the equation or the economics to me, doesn't close fully. The data center is good for probably 15 years, but what's inside you need to refresh every five years. So you need to get your money back in five years.

I for sure think a couple of these people (frontier model developers) will be very, very successful, out of the half dozen or so who are doing the spending. So some will disappoint.

WSJLI: Why isn’t that logic apparent to all of the players in the market?

Krishna: Maybe it is. But it's like this. In my downside scenario, there’s still $1 trillion dollars of extra revenue. If you think you have a chance of getting that trillion, wouldn't it behoove you to spend whatever it takes to get that?

WSJLI: What’s your framework, as CEO, for assessing the right level of risk for IBM?

Krishna: I actually have a core belief. Eighty percent of the time, good management knows what to do. But only 20% of the time is it actually done because you're going to be disturbing people.

You're going to be breaking loyalties. You've got to turn around and say, I need to change the business model. You need to turn around and say, I need to cannibalize my own existing revenue, and people find it really hard. I have a fundamental belief that the riskiest part is taking too little risk. Actually, you have to take risk. But don't make the risk so big that it is existential to survive.

 

Intelligence Layer

Cheaper tokens, massive growth. Although enterprise adoption of AI agents remains nascent, declining token costs are lowering the economic threshold for deployment, a shift that could see businesses not only embed agents into more user-initiated tasks, but also into "always-on" background processes.

Goldman Sachs Global Investment Research sees this process—where cheaper tokens enable more sophisticated agents—helping drive explosive growth in consumption. Collectively, agentic AI could amplify usage dramatically, potentially reaching 120 quadrillion tokens per month by 2030 (a 24X increase), according to their research.

However, this ROI will not materialize uniformly across all enterprise workflows.

They found that economics vary significantly by use case with coding agents consuming far fewer resources than call-center agents relying on real-time voice processing.

— Tom Loftus

 

The Doom Scroll

A lot of people move to SF because everyone says, “you should be here.” And sometimes that’s true, but often the customers, aka the gold, are not actually there. So yes, “during a gold rush, sell shovels” sounds smart, until everyone around you is also selling shovels. — Kamil Ruczynski (@unable0_)

 

Tech on the Town

Left to right: Kayla Webster, Inc. Magazine, Claire Duffy, CNN, Blomma CEO and cofounder, Silvia Oviedo Lopez, Isabelle Bousquette, WSJ, and Meredith Klein from Meredith & The Media.

Last night New York’s tech scene gathered for cocktails in Chelsea to celebrate the launch of Blomma, a new startup to provide personalized, proactive career coaching.

As someone who’s been through my own AI coaching journey (still reeling from when I let ChatGPT train me for the marathon), I’m confident there’s a lot of potential here, but also some major pitfalls. How do you make sure AI is giving you the cold, hard truth? 

That might be the advantage of using Blomma over a general model like ChatGPT. Silvia Oviedo Lopez, cofounder and CEO, told me the tool is trained on data from real executive coaches. And yes, it can be hard on you. (Recently it told her she was taking on too much).

But the party wasn’t all tech. In a nod to simpler times, a mysterious masked duo known as the Bumbys were offering to write “honest first impression assessments” of attendees in real time on type writers. Their assessment of this reporter confirmed she had “indie ingénue vibes” … but also that they could see her “crashing out at a press conference.” Honest, but fair.

— Isabelle Bousquette

 

What We're Following

  • The same day Anthropic announced higher usage limits for Claude Code and the Claude API, the startup said it planned to tap all of the compute capacity at SpaceX’s Colossus 1 data center--some 300 megawatts--by the end of the month.
  • Investors are driving big gains to a widening array of companies making components vital to AI infrastructure, from Toto, the Japanese toilet maker, which makes ceramics used in semiconductor components, to Caterpillar, which supplies power-generation equipment used in data centers. 
  • The growing concern over AI's economic disruption has revived debate among policymakers and economists over a "compute tax," a levy on AI processing power.
 

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About Us

Follow Isabelle Bousquette on LinkedIn, Instagram, X, and TikTok for more behind the scenes on her tech and AI coverage, and lately, her contributions to the WSJ Leadership Institute's new Executive Resilience series, where she's profiling America's top execs about their fitness and wellness habits.

Follow Belle Lin on LinkedIn and X for her latest reporting on enterprise technology and AI.

Steven Rosenbush is chief of the enterprise technology bureau at the WSJ Leadership Institute. He also has a column. You can follow him on LinkedIn.

Tom Loftus is the editor of The Morning Download. He suggests following Isabelle, Belle and Steve on their various social channels. But if you insist, here's his LinkedIn.

 
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