Change Agents: What agentic AI means for hardware and software

**Dom Rizzo** (0:06)
And so all of a sudden, you're not just attacking enterprise IT software market, you're attacking the trillions of dollar knowledge workflow.

**Jennifer Martin** (0:21)
Welcome to The Angle from T. Rowe Price, a podcast for curious investors. Just a reminder that outside of the US and Australia, this podcast is for investment professionals only. I'm your host, Jennifer Martin, a global equity portfolio specialist at T. Rowe Price Associates here in Baltimore, Maryland. The next phase of the AI revolution is here. Chat bots answered questions. AI agents are going a step further and executing digital tasks for us. Here to help us understand the rise of agentic AI and its implications for investors are Dom Rizzo and Frank Shi.
Dom has been with T. Rowe Price for more than a decade and is a sector portfolio manager who also co-leads our technology analysts. I like to think of Dom as half man, half GPU.
He has a lot of processing power. Frank Shi is an analyst covering global semiconductors and has stayed up late to join us from Hong Kong. And in many ways, Frank is like AI. He's on 24-7. Dom and Frank, welcome to The Angle.

**Dom Rizzo** (1:22)
Thanks for having us, Jennifer.

**Frank Shi** (1:24)
It's great to be here. Thanks, Jennifer.

**Jennifer Martin** (1:25)
Dom, the last time you were on The Angle, you asserted that AI could become the greatest productivity enhancer since electricity. As we are transitioning from chatbots to agents, what does that mean for this story and the pace and scale of AI adoption?

**Dom Rizzo** (1:43)
Well, let's first take a step back, Jennifer. It's amazing to think about all that's changed over the past few years. But what did I mean when we said AI has potential to be the biggest productivity enhancer since electricity? I think AI is going to result in an unlock of productivity that's going to result in a strong economic boom. And there's only three ways to grow an economy. There's capital, throw more money at the problem. Labor, throw more people at the problem. Or productivity, do more with the money and people that you throw at a problem. And I think we're at the early stages of an economic acceleration, driven by a productivity boom.
And the big change, since I was on the podcast last, is the change from simple chatbots to agentic workflows.
A chatbot gives you a response. You're just talking with ChatGBT. But an agent can complete tasks on your behalf. It can break a goal into steps, use tools, check the results, and keep going for hours. That is the economic leap. We're moving from just talking about information to doing work.
Now, where have we seen that pop up? The first and best use case for agentic workflows is coding. And it's the clearest early proof because the feedback loop is just brutally objective. The code runs or it doesn't.
Let's look at some of these numbers. I mean, these numbers have been phenomenal. Last summer, Anthropic was just on a $5 billion run rate in revenue. Now, because of the rise of Clawed Code, they're close to $50 billion.

**Jennifer Martin** (3:34)
Dom, that is huge. Put that into context. Five to 50 billion. How many enterprise software companies is that?

**Dom Rizzo** (3:40)
It's so funny to think about it that way. It's almost three service now, Jennifer. So, I mean, I've never seen growth of an enterprise application like this. This is true virality within an enterprise on the back of coding agents, and it's tools like OpenAI Codecs, tools like Clawed Code, tools like Cursor that are really starting to take off within the enterprise, and I think it's going to result in this economic boom.
And if you think about what is coding, coding is the unlock that allows you to get into different work flows, finance, legal, HR. And so all of a sudden, you're not just attacking enterprise IT software market, you're attacking the trillions of dollar knowledge workflow. And how do we make all of these people, whether in finance, legal, coding, more efficient, make them more productive, and will enterprises pay for that productivity? So far, the evidence is absolutely.

**Jennifer Martin** (4:47)
Yes, definitely. And you're seeing the adoption, even at our own organization, which I know we're going to talk about. We've had some really good milestones internally.
And so maybe I would like to ask Frank, it's easy to see why the proliferation of agents, which increases the demand for tokens, would be a broad tailwind for infrastructure. However, nuance always matters in these discussions. Could you explain what parts of the hardware supply chain appear well positioned as AI goes from answering questions to executing complex tasks? And maybe we start with, what is a token?