How Your Body Data Could Reshape Sectors

Welcome to Thoughts on the Market. I’m Shawn Kim, Head of Morgan Stanley’s Europe and Asia Technology Team.

Today: A foundational shift in the development of AI and its broad market implications.

It’s Tuesday, May 5th, at 3pm in London.

Think about the last time you asked a chatbot to write a summary or a draft. Or maybe answer a query. It was probably useful. But you were also still driving the interaction: asking, refining, copying, checking, and moving the work forward.

Now imagine a system that does not just respond, but acts. It remembers what you asked last week, understands your preferences, works across digital tools, plans a workflow, and adapts as circumstances change.

That is the shift from GenAI to agentic AI: from AI that helps with thinking to AI that helps with doing. GenAI is mostly passive. It takes a prompt and produces an answer. Agentic AI is active – less a copilot for one task but an autopilot for multi-step workflows.

The distinction is key because computing requirements are changing. In GenAI, large language models and GPUs handle much of the thinking. GPUs, or graphics processing units, process many calculations in parallel, making them central to modern AI models. In agentic AI, CPU becomes more important. CPUs, or central processing units, coordinate tasks and connect systems to the broader digital infrastructure.

Agentic AI also depends on three stacks: the brain, or the large language model; orchestration, where the CPU manages the doing; and knowledge, which is memory.

Memory may be the most important layer. An agent that knows your preferences, documents, tone, and task history becomes more useful over time. That creates a context flywheel. The more context it collects, the more personalized it becomes, and the harder it is to leave.

Typically, in computing, we think of memory as storage, mainly. We need to rethink this. Memory is also continuity. When an AI system can use past experiences, memory becomes a long-term state, shared knowledge, and behavioral grounding.

And that matters because LLMs have fixed context windows. Once a conversation exceeds that window, older content falls off. For simple questions, that may be fine. But for a coding agent working across a large codebase over days or weeks, it is a major limitation. Serious work requires persistent memory, short-term orientation, and active retrieval – remembering prior decisions, understanding changed files, and finding relevant codes without the user pointing to every dependency.

For investors, the implication is clear – agentic AI changes the bottlenecks. We see CPUs as the new bottleneck, with memory seeing the highest content increase. We estimate as much as 60 percent, or $60 billion of incremental CPU total addressable market by 2030, within a total CPU market of more than $100 billion. We also estimate up to 70 percent of incremental DRAM bit shipment tied to this theme.

That makes us more positive on supply chains including memory, foundry, substrates, CPU and memory interface, and capacitors and CPU sockets. These areas benefit from content growth, pricing power, and capacity constraints into 2027.

As AI moves from answering questions to taking actions, investors should watch the infrastructure behind the shift. Because in the agentic era, the next big AI leap may be less about the prompt, but more about the processor.

Thanks for listening. If you enjoy the show, please leave us a review wherever you listen and share Thoughts on the Market with a friend or colleague today.

Welcome to Thoughts on the Market. I'm Mike Wilson, Morgan Stanley’s CIO and Chief U.S.  Equity Strategist. 

Today on the podcast I’ll be discussing why earnings remains the most important variable for equity markets.

It's Monday, May 4th at 2pm in New York.  

So, let’s get after it.

The more I think about what’s been driving this market, and the more time I spend with the data, the more I keep coming back to the same conclusion: it’s earnings. Not the headlines, not even the Fed. Earnings are doing the heavy lifting right now.

When I look at this reporting season, what stands out isn’t just resilience, it’s strength that’s broader than most people appreciate. The typical company in the S&P 500 is growing earnings at about 16 percent, and the median earnings surprise is running around 6 percent. That’s the strongest we’ve seen in four years.

What’s really interesting to me is that this strength is no longer confined to just the biggest tech names. Yes, hyper scalers and semiconductors are still playing a leading role, but the story is expanding. We’re seeing earnings revisions move higher across Financials, Industrials, and Consumer Cyclicals, in particular. That kind of breadth tells me this isn’t just a narrow leadership story; it’s something more sustainable.

At the same time, many investors are focused on the geopolitical backdrop, particularly the Iran conflict and what it means for oil, inflation, and supply chains.

To be fair, companies are feeling some of that pressure. When you listen to earnings calls, you hear about rising freight costs, tighter supply chains, and higher input prices across industries like chemicals and machinery.

But here’s the nuance: those impacts are uneven. They’re not hitting the entire market in the same way. In fact, at the index level, they’re being offset. Energy has become a positive contributor to earnings growth, and the higher-end consumer remains relatively strong. Even with higher fuel costs, we’re not seeing a meaningful pullback in overall consumption – at least not yet.

That tells me  that we’re not dealing with a classic demand shock. We’re dealing with a redistribution of pressure, and companies are adapting. In many cases, they’re passing through higher costs. Revenue surprises are running above historical norms, which suggests pricing power is improving.

Now, of course, earnings aren’t the only piece of the puzzle. Policy still matters, and the shift in rate expectations this year has been meaningful. The Fed has clearly become more concerned about inflation, and the market has repriced expectations to fewer cuts, and maybe even a higher probability of hikes. That repricing is a big reason why valuations corrected so sharply over the past six months.

It’s notable  that even with that headwind, equities have managed to stabilize, thanks to earnings. When earnings are growing at an above-trend pace, equities can deliver solid returns regardless of whether the Fed is cutting or not.

That said, I do think there’s one area of risk that deserves further attention, and that’s liquidity. We’ve seen periods of funding stress over the past six months, and those moments have coincided with pressure on valuations. The Fed and the Treasury have stepped in at times to stabilize these conditions, helping to reduce bond volatility and support equity multiples.

Bottom line, we have already had a meaningful correction in valuations this year with price earnings multiples falling 18 percent from their peak last fall. That adjustment occurred as the market digested the many risks that we have been highlighting. Meanwhile, earnings are not only holding up, they’re accelerating and broadening across sectors. The risks we’re all focused on – geopolitics, oil, supply chains – are real. But they’re being absorbed at the company level. As a result, the price declines were much more modest than the compression in valuations. 

Meanwhile, monetary policy is providing some headwinds, but it’s not overwhelming the earnings story.  Equity markets move on two things: earnings and liquidity. Right now, earnings are more than offsetting the lingering liquidity concerns. In short, earnings growth is greater than the valuation reset. This is classic bull market behavior and as long as that continues, I think the U.S. equity market will grind higher for the rest of the year with intermittent bouts of volatility. 

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