Brannin McBee: Companies face budget overruns from rising AI compute costs, demand for AI technology in enterprises is unrelenting, and CoreWeave’s client diversification signals market growth | Odd Lots

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Key takeaways

Companies are facing unexpected budget overruns due to rising AI compute costs.
Efficient query routing models are anticipated to see increased investment.
Securing locations for GPU deployment is now as challenging as acquiring the GPUs themselves.
There is a strong demand for AI technology, especially in enterprise use cases.
AI adoption is expected to expand beyond traditional sectors like coding and finance.
Major clients continue to show unrelenting demand for AI technology.
CoreWeave has significantly diversified its customer base in recent years.
Different AI models require varied infrastructure, impacting deployment strategies.
Financial services clients are approaching a $10 billion backlog, indicating high demand.
Financial services are directly interfacing with infrastructure providers, bypassing AI labs.
The rapid increase in compute costs is causing a corporate reckoning with AI spending.
The challenge of GPU deployment locations reflects a shift in industry difficulties.
The adoption of AI technology is likely to spread to broader enterprise applications.
CoreWeave’s client diversification indicates significant business growth.
Financial services’ direct interaction with infrastructure providers marks a change in industry dynamics.

Guest intro

Brannin McBee is co-founder and chief development officer of CoreWeave, the cloud infrastructure company focused on high-performance compute for AI workloads. He has helped build CoreWeave from an early-stage GPU-constrained business into a public company that has expanded its financing and deepened its partnerships with Nvidia.

The financial impact of AI compute costs

Companies are experiencing significant budget overruns in AI compute costs.
CFOs around the world are getting sticker shock about their compute budgets.

— Brannin McBee
Uber burned through its entire 2026 AI budget in just four months.
This highlights the need for better budget management in AI investments.
The rapid increase in compute costs is leading to a corporate reckoning with AI spending.
Understanding the financial implications of AI spending is crucial for corporations.
The sustainability of AI investments is a critical issue in the industry.
This is a critical issue in the industry regarding the sustainability of AI investments.

— Brannin McBee

Investment trends in AI technology

Investment in efficient query routing models is expected to increase.
I have a feeling we’re gonna see a lot of investment in that area specifically.

— Brannin McBee
The advancement of technology may or may not lead to cheaper models overall.
There is a clear expectation of future investment trends in AI technology.
Understanding current trends in AI and cloud computing investment is essential.
The challenge of securing suitable locations for GPU deployment is significant.
Finding a suitable place to plug in your GPUs is as much of a challenge as securing the GPUs themselves.

— Brannin McBee
This reflects a shift in the challenges faced by companies in the AI and GPU sectors.

Demand for AI technology in enterprises

There is a strong and authentic demand for AI technology in enterprise use cases.
All we’re really doing is talking about how much consumption there is of AI.

— Brannin McBee
AI adoption will likely expand beyond coding and finance professionals.
Where we see this moving towards next is broader enterprise use.

— Brannin McBee
The current demand for AI technology remains strong with no signs of pullback.
We’re not seeing any pullback on what they’re doing on inference today.

— Brannin McBee
Major clients continue to show unrelenting demand for AI technology.
Understanding the sectors driving AI adoption is crucial for future growth.

CoreWeave’s market strategy and growth

CoreWeave has significantly diversified its customer base over the past three years.
In Q4 alone, we added twice as many logos to our client base as any previous quarter.

— Brannin McBee
The company serves hyperscaler clients, AI labs, and enterprise bases.
Nine of the top 10 AI labs globally choose CoreWeave.
This diversification indicates growth and a shift in market strategy.
Understanding the shift in CoreWeave’s customer composition is essential for business growth.
The company’s market strategy reflects substantial change and client acquisition.
CoreWeave’s growth is indicative of its strategic positioning in the AI sector.

Infrastructure needs for AI workloads

Different AI models serve various use cases, affecting infrastructure needs.
Not everyone needs just the latest model; different types of models hit different use cases.

— Brannin McBee
The diversity of AI models changes the conversation around infrastructure.
You can conceptualize this matrix of different sizes of workloads relative to different sizes of GPUs.

— Brannin McBee
Understanding AI model types and infrastructure requirements is crucial.
This insight highlights operational efficiencies in AI deployment.
The infrastructure needed for AI workloads impacts deployment strategies.
AI model diversity is a key factor in planning infrastructure needs.

Financial services demand for AI infrastructure

Financial services clients are approaching a $10 billion backlog.
Our financial service clients are approaching $10 billion in backlog.

— Brannin McBee
This indicates significant demand for infrastructure solutions in financial services.
Financial services are interfacing directly with infrastructure providers.
They are interfacing with and managing the infrastructure directly.

— Brannin McBee
This marks a shift in how financial services operate with AI infrastructure.
Understanding the context of financial services demand is essential for market trends.
The direct interaction with infrastructure providers reflects a change in industry dynamics.