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.