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    News

    The Enterprise AI Show

    The Enterprise AI Show explores the AI journey for Enterprise companies around the world.  [formerly The Cloudcast] 

    As the AI revolution moves from experimentation to execution, The Enterprise AI Show provides the clarity needed to lead. Join Aaron Delp and Brian Gracely as they explore the intersection of generative AI, enterprise systems, and global business strategy. Each episode features clear-headed conversations with the people making actual decisions—founders, investors, and practitioners—focusing on the technical architectures and business models that drive real-world ROI.

    New shows every Wednesday and Sunday. 

    Topics: Enterprise AI strategy · The AI Economy ·  LLMs in production · AI leadership · Agentic AI ·  Digital Sovereignty · Machine Learning · AI startups ·  Cloud Computing 

    Advertise

    Copyright: © 2024 Massive Studios

    • Apple Podcasts
    • Google Play
    • Spotify

    Latest Episodes:
    When Will the Models be Good Enough? Jul 26, 2026
    Show notes

    SUMMARY: Brian and Aaron explore the current state and future of AI models, focusing on model size, model harnessing, and intelligent model routing. They discuss whether bigger models are always better, the economics of AI, and how enterprise applications can benefit from tailored AI solutions.

    SHOW: 1048

    SHOW TRANSCRIPT: The Enterprise AI Show #1048 Transcript

    SHOW VIDEO: https://youtu.be/1IHXNrYlYCA

    SHOW SPONSORS:

    • ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!
    • Nasuni - Activate your data for AI and request a demo

    Topic: When will the models/harnesses be good enough?

    • Why now? Benchmark Maxxing - cost to build/host/maintain 1+ trillion parameter model
    • Past: The “wow” moments in versions really stopped around GPT4… (maybe?)
    • Present: Race to the top/bottom, millions spent to gain SOTA for a few days
    • Future: Will the pendulum swing back? Will bigger/faster always rule?

    FEEDBACK?

    • Email: show @ the enterprise ai show dot com
    • Bluesky: @TheEntAIShow.bsky.social
    • Twitter/X: @TheEntAIShow
    • Instagram: @TheEntAIShow

    AI's Impact on Trust and Brand Jul 22, 2026
    Show notes

    SUMMARY: Brian talks with Melissa Rosenthal from Outlever about the intersection of AI, brand, and marketing. They explore how AI impacts trust, brand consistency, and operational efficiency, offering insights for organizations navigating AI adoption.

    SHOW: 1047

    SHOW TRANSCRIPT: The Enterprise AI Show #1047 Transcript

    SHOW VIDEO: https://youtu.be/PEqyOxE9PIw

    SHOW SPONSORS:

    • Nasuni - Activate your data for AI and request a demo
    • ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!

    RESOURCES:

    Outlever

    State of Brand Article

    KEY TOPICS:

    • AI's impact on trust and brand perception
    • Operational efficiencies and AI workflows
    • Challenges of AI implementation and guardrails
    • Measuring ROI and costs of AI
    • The importance of brand consistency in AI interactions

    TAKEAWAYS


    • AI can speed up engineering and operational tasks by 100X.
    • Many companies are still in pilot stages with AI, lacking governance.
    • Brand consistency is at risk when AI interactions don't align with brand values.
    • Experimentation with AI is costly and often lacks clear ROI.
    • Organizations need to orchestrate AI workflows across teams for better outcomes.

    CHAPTERS/TOPICS:

    00:00 Introduction to AI's impact on enterprise and brand

    00:30 Melissa Rosenthal's background and Outlever's focus

    01:05 The trust issue: AI replacing human interactions

    01:55 How AI speeds up workflows and system building

    03:00 Risks of AI in customer-facing interactions

    04:11 Brand touchpoints and AI's influence on brand perception

    05:05 Training AI to reflect brand values

    05:59 Responsibility and handling AI mistakes

    06:53 Current state of AI governance in companies

    08:12 ROI and costs of AI experimentation

    08:57 The early stage of AI adoption and lessons learned

    10:11 Future outlook: AI in marketing and brand orchestration

    10:58 The importance of workflow orchestration across teams

    12:03 Bridging the gap between technology and marketing

    12:54 The chaos and chaos in AI adoption today

    14:03 Risks of homogenized brand messaging with AI

    15:02 Predictions for AI in marketing in the next year

    16:04 Reorganizing teams around AI outcomes

    17:04 The missing link: connecting technology and brand strategy

    18:03 Final thoughts and key takeaways


    FEEDBACK?

    • Email: show @ the enterprise ai show dot com
    • Bluesky: @TheEntAIShow.bsky.social
    • Twitter/X: @TheEntAIShow
    • Instagram: @TheEntAIShow

    What is a Behavioral Agent Automation Platform? Jul 19, 2026
    Show notes

    SUMMARY: Steven Walchek, CEO at Liminal, discusses secure AI enablement for regulated industries and why most enterprises are stuck in perpetual AI pilots. We explore the "agentic cliff" and how Behavioral Agent Automation Platforms (BAAPs) discover and deploy agents by observing how work actually happens.

    SHOW: 1046

    SHOW TRANSCRIPT: The Enterprise AI Show #1046 Transcript

    SHOW VIDEO: https://youtu.be/nVte_ZKDID4

    SHOW SPONSORS:

    • ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!
    • Nasuni - Activate your data for AI and request a demo

    RESOURCES:

    • Liminal AI
    • Steven Walchek - LinkedIn

    KEY TOPICS:

    • Horizontal security for generative AI
    • Data privacy and compliance in AI
    • Security layers in AI deployment
    • Agentic AI and behavioral automation
    • Future industry trends in AI security

    TAKEAWAYS

    • Security for AI must be integrated at the application layer, not just network or perimeter.
    • Data privacy concerns are central to AI adoption in regulated industries.
    • Organizations need a security layer that supports multi-model, multi-provider AI engagement.
    • Behavioral automation and agentic AI require observability and policy enforcement.
    • The AI industry is still in early adoption, with significant growth expected in the next five years.

    CHAPTERS/TOPICS:

    00:00 Introduction and guest introduction

    02:09 Steven's background and journey in tech

    03:54 The core problem of AI security in regulated industries

    07:45 Data privacy concerns and industry challenges

    12:01 Liminal's approach to AI security and compliance

    15:52 Security at the application layer and network layer

    20:02 Agentic AI, behavioral automation, and observability

    30:04 Future trends and industry outlook

    31:46 How to connect with Liminal and closing remarks


    FEEDBACK?

    • Email: show @ the enterprise ai show dot com
    • Bluesky: @TheEntAIShow.bsky.social
    • Twitter/X: @TheEntAIShow
    • Instagram: @TheEntAIShow

    Does FinOps need an update for the AI world? Jul 15, 2026
    Show notes

    SUMMARY: On today’s "Models and Markets" - we explore about the FinOps experience from Cloud is having to adapt to the changing demands of Enterprise AI.

    SHOW: 1045

    SHOW TRANSCRIPT: The Enterprise AI Show #1045 Transcript

    SHOW VIDEO: https://youtu.be/Plb88y-IkZY

    SHOW SPONSORS:

    • Nasuni - Activate your data for AI and request a demo
    • ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!

    SHOW NOTES:

    Topic: Finops for AI?

    • Why now? Cost of tokens goes up as model performance increases, but still needs subsidies…
    • Past: FinOps for Cloud - prices grew out of control, needed centralization for expense management and capital allocation
    • Present: TokenMaxxing, the move from per-seat to per-token pricing
    • Future: What happens when you can’t afford the Ferrari anymore? Will there be a glut of FinOps for AI startups? What happens when usage is regulated and centralized?

    FEEDBACK?

    • Email: show @ the enterprise ai show dot com
    • Bluesky: @TheEntAIShow.bsky.social
    • Twitter/X: @TheEntAIShow
    • Instagram: @TheEntAIShow

    Buy, Build or Rent your AI? Jul 12, 2026
    Show notes

    SUMMARY: Something new - "Models and Markets" - Aaron and Brian explore how recent news and macro trends are causing more companies to explore whether they should Buy, Build or Rent their AI future.

    SHOW: 1044

    SHOW TRANSCRIPT: The Enterprise AI Show #1044 Transcript

    SHOW VIDEO: https://youtu.be/vcroGCXd3N4

    SHOW SPONSORS:

    • ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!
    • Nasuni - Activate your data for AI and request a demo

    SHOW NOTES:

    Topic: Own AI or Rent AI?

    • Why now? Fable 5 and GPT 5.6 get restricted in the US
    • Past: Private Cloud (on-prem/server huggers) vs. Public cloud vs. *gasp* hybrid cloud
    • Present: OSS Models vs. Big API models
    • Future: What happens when the subsidies go away, and rational business practices hit the industry??

    FEEDBACK?

    • Email: show @ the enterprise ai show dot com
    • Bluesky: @TheEntAIShow.bsky.social
    • Twitter/X: @TheEntAIShow
    • Instagram: @TheEntAIShow

    Unstructured Data in an AI World Jul 08, 2026
    Show notes

    SUMMARY: While we spend a lot of time discussing AI models, we don’t always spend enough time on the challenges of managing the unstructured data used to train, tune, and enable those models.

    SHOW: 1043

    SHOW TRANSCRIPT: The Enterprise AI Show #1043 Transcript

    SHOW VIDEO: https://youtu.be/OAqnuhorMJ4

    SHOW SPONSORS:

    • Nasuni - Activate your data for AI and request a demo
    • ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!

    SHOW NOTES:

    Topic 1 - Welcome to the show. Tell us a bit about your background and where you focus today at Nasuni

    Topic 2 - We’ve spent two years talking about models. Are we finally entering the era where the biggest differentiator is data quality rather than model quality?

    Topic 3 - When customers inventory their AI-ready data, what surprises them most?

    Topic 4 - Where is the intersection of file data, metadata, and RAG systems that augment a company’s AI experience with their own data?

    Topic 5 - People talk about AI governance, but isn’t most AI governance actually data governance?

    Topic 6 - Are today’s enterprise file systems designed for machine consumers (AI Agents) instead of human consumers?

    Topic 7 - What are the economics of data, in your world, as it relates to AI?

    Topic 8 - What’s next for enterprise file platforms?


    FEEDBACK?

    • Email: show @ the enterprise ai show dot com
    • Bluesky: @TheEntAIShow.bsky.social
    • Twitter/X: @TheEntAIShow
    • Instagram: @TheEntAIShow

    Are companies giving away their secrets to AI? Jul 05, 2026
    Show notes

    SUMMARY: Are CEO's frustrated with the lack of control, costs and sovereignty of their AI environments?

    SHOW: 1042

    SHOW TRANSCRIPT: The Enterprise AI Show #1042 Transcript

    SHOW VIDEO: https://youtu.be/xgQv8WP-DNI

    SHOW SPONSORS:

    • ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!
    • Nasuni - Activate your data for AI and request a demo

    SHOW NOTES:

    • Palantir and NVIDIA partnership (June 2026) - first 11 minutes
    • Palantir CEO (Alex Karp) on CNBC
    • “The VPC Privacy Illusion - Why Private LLMs still expose your data”
    • The biggest mistake organizations make isn’t choosing the right model, it’s focusing on models at all (via LinkedIn)


    1. There’s a level of unhappiness and distrust of the frontier labs from CEOs
    2. There needs to be an application layer on top of LLMs (e.g. “harness”, Palantir Ontology)
    3. This application layer prevents the LLMs from learning your business from your data
    4. “Alpha” is business differentiation (ability to outperform the market)
    5. He questions why the frontier model labs are charging by tokens and not outcomes (questions the entire AI business model)
    6. He questions “the true cost” of AI outputs
    7. He claims that CEOs are now concerned about frontier labs entering the business of the customers - brings up an interesting misunderstanding of how interacting with LLMs works (“we’re safe, it’s deployed in our VPC”)

    FEEDBACK?

    • Email: show @ the enterprise ai show dot com
    • Bluesky: @TheEntAIShow.bsky.social
    • Twitter/X: @TheEntAIShow
    • Instagram: @TheEntAIShow

    AI News of the Month - June 2026 Jul 01, 2026
    Show notes

    SUMMARY: Brian Gracely (@bgracely) and Aron Delp (@aarondelp) discuss the biggest AI news stories from the month of June, 2026.

    SHOW: 1041

    SHOW TRANSCRIPT: The Enterprise AI Show #1041 Transcript

    SHOW VIDEO: https://youtu.be/SXmPOgE5jGk

    SHOW SPONSORS:

    • Nasuni - Activate your data for AI and request a demo
    • ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!

    SHOW NOTES:

    • Links to all the AI News covered in this month’s show

    FEEDBACK?

    • Email: show @ the enterprise ai show dot com
    • Bluesky: @TheEntAIShow.bsky.social
    • Twitter/X: @TheEntAIShow
    • Instagram: @TheEntAIShow

    Enterprises are concerned about AI Costs, Governance and Trust Jun 28, 2026
    Show notes

    SUMMARY: As AI within the Enterprise matures, we look at 10 concerns and challenges that are still causing Chief AI Officers to worry about success in the future.

    SHOW: 1040

    SHOW TRANSCRIPT: The Enterprise AI Show #1040 Transcript

    SHOW VIDEO: https://youtu.be/RyB4m17YK_4

    SHOW SPONSORS:

    • Nasuni - Activate your data for AI and request a demo
    • OutShift by Cisco - “Scaling Out Superintelligence” The Internet of Cognition architecture
    • ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!

    SHOW NOTES:

    THESIS: After spending time with a number of Enterprise companies, what are a list of challenges and concerns they still have in implementing GenAI across a broad set of use-cases within the Financial Services industry?

    1. Everybody started with what was available (e.g. CoPilot)
    2. Enterprise implementations (now) aren’t autonomous
    3. Rising costs are the looming concern
    4. Governance is a rising concern
    5. Measurements of improvement are available, but varied
    6. Explaining measurements is complicated
    7. Explaining trust is more complicated
    8. Use-cases are fragmented, but there if you apply the technology, but not always obvious
    9. De-centralized (shadow AI) to Centralized to De-centralized (semi-controlled)
    10. The learning curves are very asymmetrical across teams
    11. Not everyone has access to Mythos or GPT-5.5-Cyber (yet)

    FEEDBACK?

    • Email: show @ the enterprise ai show dot com
    • Bluesky: @TheEntAIShow.bsky.social
    • Twitter/X: @TheEntAIShow
    • Instagram: @TheEntAIShow

    A Day in the Life of a Forward-Deployed Engineer Jun 24, 2026
    Show notes

    SUMMARY: What does a Forward-Deployed Engineer actually do? And what about deploying AI Harness? Let’s dig into the real-world with these evolving AI concepts and technologies.

    SHOW: 1039

    SHOW TRANSCRIPT: The Enterprise AI Show #1039 Transcript

    SHOW VIDEO: https://youtu.be/QY0fqu2O84M

    SHOW SPONSORS:

    • OutShift by Cisco - “Scaling Out Superintelligence” The Internet of Cognition architecture
    • ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!
    • Nasuni - Activate your data for AI and request a demo

    SHOW NOTES:

    • Mozilla Thunderbolt launched
    • Mozilla Thunderbolt (homepage)


    Topic 1 - Welcome to the show, tell us a bit about your background and what you focus on these days.

    Topic 2 - Let’s talk about the role of Forward Deployed Engineer, it’s being talked about a lot, but you’re living in that world now. What problems are FDEs usually tasked with trying to solve, or new things to implement?

    Topic 3 - We’ve seen other roles (DevOps, PlatformEng, etc.) that evolved from other roles or skills. What type of background lends itself to success in FDE? What skills are needed going forward?

    Topic 4 - You’re also working on some AI harness implementations. What can you tell us about those challenges and the technologies behind the harness?

    Topic 5 - At what point does an AI harness make sense for a company? What types of AI challenges typically require those next steps?

    Topic 6 - Working in the middle of this evolving AI space, what are some perspectives you’ve gained over the last 6-12 months? What do you wish you knew ahead of time?

    FEEDBACK?

    • Email: show @ the enterprise ai show dot com
    • Bluesky: @TheEntAIShow.bsky.social
    • Twitter/X: @TheEntAIShow
    • Instagram: @TheEntAIShow

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