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Subvolts take Enterprise AI leaders reveal why most projects fail and where real value lies. Dec 23, 2025
For you
Developers
Learn about the shift from LLMs to proprietary data and agentic systems for building valuable enterprise AI applications.
Business
Understand why most AI projects fail and how to build durable advantage through data and workflow integration.
Hype note
3/5Notable

This interview provides a candid, operator-level discussion on enterprise AI from two prominent CEOs, offering practical insights.

BG2 Pod
BG2 Pod Episode

AI Enterprise - Databricks & Glean | BG2 Guest Interview

45 min Interview Hosts: Bill Gurley, Brad Gerstner
0:0045:00

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From Subvolts

Summary and analysis by Subvolts editorial, AI-assisted.

Summary

BG2 Pod features Databricks CEO Ali Ghodsi and Glean CEO Arvind Jain discussing enterprise AI realities. They explore why most AI projects fail, the commoditization of LLMs, and the shift towards proprietary data and agentic systems for durable advantage. The conversation covers real-world use cases, the AGI debate, and AI spending projections.

Explained simply

This episode talks about why most computer "smart helper" projects don't work out in companies. It explains that the basic AI technology is becoming common, and what really matters now is a company's own private information and how AI can be built into daily work.

Why listen

This episode offers a grounded perspective on enterprise AI from two prominent CEOs. It's valuable for builders and investors navigating AI adoption, explaining practical challenges and success factors beyond the hype. The discussion on data as a moat and agentic systems provides context for how companies like Google Gemini and OpenAI are evolving their enterprise strategies, focusing on integration and workflow automation.

On the mic
  • HostBill Gurley
  • HostBrad Gerstner
  • GuestAli GhodsiCEO, Databricks
  • GuestArvind JainCEO, Glean
About
GoogleOpenAIEnterpriseAgentsModels
Key facts
  • Guest and Title: AI Enterprise - Databricks & Glean | BG2 Guest Interview
  • Show: BG2 Pod
  • Length: 45 minutes
  • AI Project Failure Rate: 95%
  • Key to Advantage: Proprietary data, agentic systems, workflow integration
  • LLM Status: Rapidly commoditizing
Show notes from BG2Pod

In this BG2 guest interview, Altimeter partner Apoorv Agrawal sits down with Ali Ghodsi (Databricks) and Arvind Jain (Glean) for a candid, operator-level discussion on what’s actually working in enterprise AI—and what isn’t.

They unpack why 95% of AI projects fail, why LLMs are rapidly commoditizing, and why durable advantage is shifting to proprietary data, agentic systems, and workflow integration. The conversation dives deep into real-world use cases across finance, healthcare, and retail; the debate over whether we already have AGI; and how AI spend, CapEx, and valuation bubbles will realistically play out. A must-watch for builder, and investors navigating the AI transition inside real organizations.


Timestamps:

(00:00) Intro

(01:00) Consumer AI vs. Enterprise Reality

(02:15) Why 95% of AI Projects Fail

(04:15) RBC, Merck, and 7-Eleven Use Cases

(06:45) What Actually Makes AI Work

(07:00) LLMs Are Commodities—Data Is the Moat

(08:45) Failed AI Bets at Databricks & Glean

(11:00) RPA vs. Generative AI

(14:15) Advice for CIOs Planning AI Budgets

(16:00) AI CapEx and the Revenue Math

(18:00) The Three Camps of AI

(21:00) Making AI Useful Inside Enterprises

(24:30) Why Apps Capture the Value

(30:00) The Future of UI, Voice, and Data Entry

(37:30) Rapid Fire: Winners, Bubbles, Long/Short


Produced by Dan Shevchuk

Music by Yung Spielberg

Available on Apple, Spotify, www.bg2pod.com


Follow:

Apoorv Agrawal @apoorv03 https://x.com/apoorv03
BG2 Pod @bg2pod https://x.com/BG2Pod

Jargon decoded
LLMs
Ali Ghodsi (Databricks) and Arvind Jain (Glean)
Large Language Models, the AI technology behind tools like ChatGPT.
AGI
Ali Ghodsi (Databricks) and Arvind Jain (Glean)
Artificial General Intelligence, AI with human-like cognitive abilities.
RPA
Ali Ghodsi (Databricks) and Arvind Jain (Glean)
Robotic Process Automation, software that mimics human actions to perform digital tasks.
Agentic systems
Ali Ghodsi (Databricks) and Arvind Jain (Glean)
AI systems that can independently plan and execute tasks to achieve goals.
Published
Show
BG2 Pod · BG2Pod
Length
45 min
Companies
Google, OpenAI
Summary by
Subvolts, using an AI model (how we work). Spotted a mistake? Tell us.
#Enterprise#Agents#Models

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Questions people ask

Why do most AI projects fail?
The episode suggests that 95% of AI projects fail, implying a disconnect between consumer AI hype and enterprise reality, and a lack of focus on what truly makes AI work.
What is the key to durable advantage in AI?
Durable advantage is shifting to proprietary data, agentic systems, and workflow integration, rather than just LLMs which are rapidly commoditizing.

Page generated Oct 19, 2026. Summaries are Subvolts' own; the audio, artwork and notes belong to BG2Pod.