The Enterprise AI Show

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Chaotic AI Markets: Focus on what you can control Jun 21, 2026

Show notes

SUMMARY: On Father's Day, how would you explain some of the volatility of the AI market to your father? What advice might he give you to navigate the ups and downs and uncertainties?

SHOW: 1038

SHOW TRANSCRIPT: The Enterprise AI Show #1038 Transcript

SHOW VIDEO: https://youtu.be/T2ZIYLpl_cE

SHOW SPONSORS:

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

SHOW NOTES:

THESIS: On this Father’s Day, with an AI market that often times doesn’t make any sense, I thought about the type of advice that my father gave me over the years and how it would apply to this time of significant change.

Show up, keep up and shut up
Make yourself invaluable
Focus on what you can control
Be an expert in something
When in doubt, get closer to people and how money is made
When things don’t make sense, focus on fundamentals
Markets can be irrational way longer than you can be solvent
Try and think a couple steps ahead

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AI Cyber is expanding a Vulnerability Gap Jun 17, 2026

Show notes

SUMMARY: As tools like Mythos create new AI-cybersecurity concerns, CIOs and CISOs need to be prepared for two challenges: Security Remediation and Patch to Production acceleration.

SHOW: 1037

SHOW TRANSCRIPT: The Enterprise AI Show #1037 Transcript

SHOW VIDEO: https://youtu.be/H5KxoiEIfUo

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: Major initiatives are forming to help enterprise organizations combat security vulnerability threats found or created using new AI-cyber tools such as Anthropic Mythos. What are the key considerations, and what additional steps do organizations need to take to be advantaged by these capabilities?

Part 1

The Breaking Point and the Mythos Moment
The scope of open source security and support
Patches, disclosures and upstream open source
Clearinghouses, EOs, Laws and Communities
Remediation - Build vs. Buy

Part 2

How fast can you get from Patch to Production?
Mitigation before patching
Fast path and stable patch pipelines?
Automation in patching vs. automation in deployment

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Do CIOs need to create an Enterprise AI Harness? Jun 12, 2026

Show notes

SUMMARY: How can CIOs balance innovation and control as they roll our AI capabilities across their organization. How can they balance onboarding, experience, security and flexibility?

SHOW: 1036

SHOW TRANSCRIPT: The Enterprise AI Show #1036 Transcript

SHOW VIDEO: https://youtu.be/ZgkMF7G3Yfo

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:

THESIS: It comes up as different control points, but CIOs are ultimately trying to figure out how to get the value from Enterprise AI while delivering a set of consistency across different teams and use-cases. Let’s explore what this “Enterprise Harness” is starting to look like.

Enterprise Clearinghouse
Enterprise Intelligence (a.k.a. Middleware)
Enterprise Catalog - Models as a Service, Agents as a Service
Enterprise Skills or Shareable Prompt Harnesses
Symantec Routing to Models
AI Gateway Controls

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Should CIOs have a backup plan for AI? Jun 10, 2026

Show notes

SUMMARY: If the cost of public AI continues to rise, because of various market shortages, should CIOs start looking at backup plans to better own their AI journeys and futures?

SHOW: 1035

SHOW TRANSCRIPT: The Enterprise AI Show #1035 Transcript

SHOW VIDEO: https://youtu.be/ngBBpP2Lgdo

SHOW SPONSORS:

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

SHOW NOTES:

THESIS: Between pending IPOs (Wall St. demands), high user-demand, GPU/TPU shortages, Data Center shortages, Model prices increasing (open models fading away), the cost of using AI is going to get more expensive over time. Should CIOs start thinking about a Backup plan to their current AI adoption that has lower cost alternatives?

Topic 1 - Assuming you could get access to GPUs/TPUs/Accelerators, and suitable data center space to host them, what would be your thinking as a CIO if you felt like you needed to own some aspect of your AI roadmap/journey?

Topic 2 - Assuming the normal “Shadow AI” backlash that you’d receive for offering something that wasn’t “frontier” level, how would you go about trying to communicate that within your organization?

Topic 3 - What metrics or KPIs would you initially target to try and get buy-in that your approach was acceptable and moving towards the company goals?

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What are the incentives to share AI learning curves with teammates? Jun 05, 2026

Show notes

SUMMARY: When we get to the end of 2026, how will enterprise companies be measuring the success of their AI projects? And how well will their teams be sharing their AI learning curves?

SHOW: 1034

SHOW TRANSCRIPT: The Enterprise AI Show #1034 Transcript

SHOW VIDEO: https://youtu.be/TvIFwNN-6ck

SHOW SPONSORS:

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

SHOW NOTES:

Topic 1 - How do we measure AI-adoption success?

Number of workloads?
Financial metrics (Spend, ROI, Costs-Saved, etc.)?
Speed improvements?
People-level?

Topic 2 Right now the AI tools are very individual-centric

The machinery to share, even at the basic enterprise-level, is very difficult
The experience to share is non-deterministic, just as everyone’s working style is different.

Topic 3 - The motivation to share is still unknown.

How do you encourage collaboration when so many companies are laying off people, or the specter of that happening is growing?
What was the motivation before (team goals?) and how does that change now?
People don’t want to be monitored, so how does a manager have visibility?
What happens when companies remove the managers (“the counters”)?

FEEDBACK?

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Cerebras is disrupting the market with Fast Inference Jun 03, 2026

Show notes

SUMMARY: After the first successful AI IPO of 2026, we dig into what makes the Cerebras WSE architecture unique in the market for fast inference.

GUEST: Andy Hock, Chief Strategy Officer at Cerebras AI

SHOW: 1033

SHOW TRANSCRIPT: The Enterprise AI Show #1033 Transcript

SHOW VIDEO: https://youtu.be/ed2nVbOtZiA

SHOW SPONSORS:

OutShift - “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:

Topic 1 - Welcome to the show. Tell us about your background, and what you focus on today.

Topic 2 - For anyone that’s not familiar with Cerebras, give us an overview of the company, and especially an overview on the Cerebras technologies (e.g. Wafer-Scale Engine).

Topic 3 - Cerebras’ WSE architecture is different from many of the GPU or GPU-like architectures in the market today. Centralized vs. distributed architectures always have their tradeoffs. Walk us through the technical and economic value of the Cerebras architecture.

Topic 4 - Congratulations on the recent IPO (raised $5.55B). Let’s use that as a point in time vs the previous planned IPO. How has the market changed in that timeframe, and how has the Cerebras position changed?

Topic 5 - Cerebras (today) offer both WSE hardware, and Cerebras Cloud (API) - very different GTM paths. Can we expect both of those to stay top priorities, or have the market dynamics shifted such that the priorities shift more towards the WSE business - as we’re seeing OpenAI, AWS and other engagements announced?

Topic 6 - Is Cerebras a training and inference company, or are the economics of inference significantly different enough that it needs to be the sole focus of the company (for now)?

Topic 7 - How much effort is it for any company to add support for the Cerebras chips if they have previously been using other architectures?

Topic 8 - An IPO is a major milestone for any company, but the markets will now look for your future story. How do you see the AI market evolving over the next 2-5 years, and what are some things that people aren’t understanding yet about how it will evolve?

FEEDBACK?

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How will team collaboration evolve within Enterprise AI? May 31, 2026

Show notes

SUMMARY: The biggest enterprise AI question is which organization can most effectively operationalize, govern, and economically scale AI agents across the business.

SHOW: 1032

SHOW TRANSCRIPT: The Enterprise AI Show #1032 Transcript

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

SHOW SPONSORS:

ShareGate - ShareGate Protect. Microsoft 365 Governance. We got this.
Nasuni - Activate your data for AI and request a demo

SHOW NOTES:

Opening Thesis - How will team collaboration evolve within Enterprise AI?

Question: Any suggestions on how to introduce enterprise-level governance and standardisation for agentic coding? Like skills, rules, plugins, context etc

Key Topics

1. This isn’t a Coding-specific problem. Every team has this issue.

If your processes weren’t well defined and enforced before, they will be worse now
Not it’s not just process standardization, but “buy-in” standardization

2. Everything moves so fast, so managers don’t have the answers (yet)

AI value is being created bottom-up, but paid for (and mandated) top-down
The current measurements aren’t useful (tokenmaxxing, all-or-nothing, etc.)

3. The governance tools don’t exist yet.

And it’s not clear that anyone wants them. They didn’t want them before.
How do you even define governance? What’s the baby step before that, reuse and basic sharing?

4. Are we ready to invest in “Centers of Excellence” again?

5. We under-estimate the “creativity” element in human buy-in.

Is success measured in improvement or replacement?
How much of that did “you” do? We don’t know how to measure that.
We haven’t lived through an AI-centric promotion cycle yet

6. Bottom-up and Top-down need to find some common language and middle ground.

Have they walked a mile in each other’s shoes yet (or lately)?
How to bring a reality to the hype vs. demands vs. learning curve?
How long is an AI-centric cycle vs. a pre-AI-centric cycle?

FEEDBACK?

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AI News of the Month - May 2026 May 27, 2026

Show notes

SUMMARY: Brian Gracely (@bgracely) and Brandon Whichard (@bwhichard, Software Defined Talk and Failover Media) discuss the biggest AI news stories from the month of May, 2026.

SHOW: 1031

SHOW TRANSCRIPT: The Reasoning Show #1031 Transcript

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

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?

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Why Enterprise AI Economics Are Changing May 24, 2026

Show notes

SUMMARY: The biggest enterprise AI question may no longer be
Which model is smartest? Instead, which organization can most effectively operationalize, govern, and economically scale AI agents across the business?’

SHOW: 1030

SHOW TRANSCRIPT: The Enterprise AI Show #1030 Transcript

SHOW VIDEO: https://youtu.be/acOBfRI0P3U

SHOW SPONSORS:

ShareGate - ShareGate Protect. Microsoft 365 Governance. We got this.
Nasuni - Activate your data for AI and request a demo

SHOW NOTES:

Opening Thesis - Was the first wave of AI adoption artificially cheap? - The industry may be transitioning from subsidized growth to usage-based economics.

Key Topics

1. Evidence AI Was Subsidized

Massive CAPEX vs low end-user pricing
Generous enterprise bundles
Frontier model access for $20/month

2. The Hidden Economics of AI Agents -

Agents consume exponentially more inference
Tool orchestration, retries, memory, verification

3. Why Frontier Labs Are Shifting Focus

From benchmark supremacy to orchestration
Governance, memory, connectors, MCP, workflows

4. Forecasting AI Pricing

12 Months:
- Commodity inference gets cheaper -
- Frontier reasoning remains premium
24 Months:
- AI billing resembles AWS-style infrastructure billing
- Runtime, memory, latency and orchestration become billable
36 Months:
- Outcome-based pricing emerges
- AI spending shifts from IT budgets to labor budgets Final Takeaways
- Commodity AI becomes utility-priced
- Frontier reasoning becomes premium
- Agents reshape enterprise economics

Key Conclusions

1. AI probably was subsidized
The economics strongly suggest adoption-first pricing.

2. The subsidy era may be ending
Premium tiers and metered pricing are emerging.

3. AI agents fundamentally alter economics
Usage scales exponentially with autonomy.

4. Commodity AI and frontier reasoning are separating
One becomes cheap.
One becomes premium.

5. The real battle is moving upward in the stack
The future moat may be:

orchestration
governance
workflows
enterprise context
operational tooling

Final Closing Thought
“The biggest enterprise AI question may no longer be:
‘Which model is smartest?’

Instead:
‘Which organization can most effectively operationalize, govern, and economically scale AI agents across the business?’”

FEEDBACK?

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Can AI Agents be held Accountable? May 20, 2026

Show notes

SUMMARY: As AI Agents are being brought into complex, regulated workflows, we explore the importance of accountability and accuracy, and how platforms and harnesses accomplish that goal. Can the CFO really fall in love with AI?

GUEST: Ram Venkatesh, Co-Founder/CTO of Sema4.ai

SHOW: 1029

SHOW TRANSCRIPT: The Enterprise AI Show #1029 Transcript

SHOW VIDEO: https://youtu.be/Lc3XS44Ixg4

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 about your background, and what led you to create Sema4.ai?.

Topic 2 - AI Agents vs. Automation 2.0. What Actually Changed. Tell us about the Sema4.ai platform and capabilities. What challenges does it solve today?

Topic 3 - You’re initially focused on solving challenges for the CFO, which means there is a ROI-focus all the time. Why did you target that segment of the business first?

Topic 3a - What are the biggest hidden costs in enterprise AI deployments today?

Topic 4 - Sema4.ai emphasizes “your LLM, your VPC, your data.” What are the biggest considerations for companies looking to create these private/sovereign AI solutions? What typically gets overlooked?

Topic 5 - How do you tend to frame the conversation about AI trustworthiness, and the role of humans vs. agents for enterprise work?

Topic 6 - It feels like so much has changed or evolved with AI in the last 2-3 years. How does an Enterprise think about this much change for something that will be core to many critical applications? What will the Enterprise Architecture look like in 2 years?

Topic 7 - Sema4.ai emerged partly from the acquisition of Robocorp and has roots in open-source automation. Do you have a perspective on the role open-source will play in AI going forward?

FEEDBACK?

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