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Ep 633: The 3 Big Obstacles Holding AI Adoption Back

Cisco's President gives us exclusive AI insights, Microsoft’s ‘Hey Copilot’ could be a real AI assistant, Claude launches AI skills, Canva teases AI agents release and more.

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Everyday AI
October 16, 2025

Outsmart The Future

Today in Everyday AI
8 minute read

🎙 Daily Podcast Episode: Learn the 3 major obstacles holding enterprises back—from infrastructure to data gaps—and how to overcome them for true business transformation. Give it a watch/read/listen.

🕵️‍♂️ Fresh Finds: Claude now connects to Microsoft 365, GPT-6 might have a release date, more Apple AI exits and more. Read on for Fresh Finds.

🗞 Byte Sized Daily AI News: Microsoft’s ‘Hey Copilot’ could be a real AI assistant, Claude launches AI skills, Canva teases AI agents release and more. Read on for Byte Sized News.

💪 Leverage AI: Most companies stall on AI because they lack secure compute, real-time algorithmic defenses, and machine-data infrastructure — the 10% that win built all three. Want the exact playbook Jeetu used to beat those bottlenecks? Keep reading for that!

↩️ Don’t miss out: Did you miss our last newsletter? How to use ChatGPT apps, Google Gemini 3.0 Pro leaks, Mark Cuban warns against ‘erotic’ ChatGPT mode, Google drops impressive AI video updates and more. Check it here!

EP 633: The 3 Big Obstacles Holding AI Adoption Back -- An Everyday AI Chat with Cisco President Jeetu Patel

Jeetu Patel knows a few AI secrets. 

As the President of one of the largest companies in the world, he's helped pave the AI adoption roadmap. 

At Cisco, they provide full-stack, enterprise AI solutions spanning infrastructure, security, observability, and operations to the world's largest companies. 

So naturally, Jeetu could write a legit playbook on what's slowing enterprises down in the AI fast lane and how they can overcome those bottlenecks. 

And naturally, Jeetu is gonna share it all with us. 

Also on the pod today:

• Is the AI bubble real? 💥
• AI infrastructure shortage explained ⚡️
• Agentic workflows: next gen automation 🤖

It’ll be worth your 33 minutes:

Listen on our site:

Click to listen

Subscribe and listen on your favorite podcast platform

Listen on:

Here’s our favorite AI finds from across the web:

New AI Tool Spotlight – Snap runs instant usability tests with AI personas and quick feedback, Outchat.ai allows readers to chat with blog content, Lazy is a one-shortcut capture tool that sends straight into Notion.

LLM updates — Anthropic’s Claude now hooks into Microsoft 365, letting you search emails, chats, and docs in one place

GPT-6 — If an OpenAI investor is to be believed, GPT-6 could be coming before the end of the year.

Big Tech - Apple’s AI lead for Siri’s next-gen search is leaving for Meta amid a string of senior exits — signaling talent flight as Apple races to catch OpenAI and Google. Curious who's reshaping the future of AI at Meta and what it means for Siri?

AI in the Workplace - Gen Z isn’t failing — it’s redefining work: they use AI to upskill, favor flexible gigs and side hustles, and quit jobs that don’t offer growth or balance. Want to see why employers calling it a “crisis” might be missing the point?

1. IBM and Oracle’s new AI agents just crashed the enterprise party — and brought reinforcements 🚀

IBM has launched three new AI agents built with Oracle’s AI Agent Studio and made them available through the Oracle Fusion Applications AI Agent Marketplace. These agents are designed to automate enterprise workflows like intercompany agreement review, sales-order entry, and converting purchase requisitions into contracts.

Going forward, IBM also plans to introduce additional agents—particularly for HR and supply chain functions—developed using its watsonx Orchestrate platform. These will further expand how organizations can embed AI-driven automation across business processes within Oracle environments.

2. Microsoft Turns “Hey Copilot” Into a Real Mic Drop 🎤

Microsoft rolled out new Windows features to bring the concept of an “AI PC” closer to reality. Among the updates: users can now say “Hey Copilot” to launch Microsoft’s assistant, allow Copilot to view their screen to help with apps or data, and use Copilot Actions (in preview) to operate on documents and photos directly from the desktop. axios.com

Importantly, these features are available on all Windows 11 PCs (not just the high-end “Copilot+” models) and are opt-in, giving users control over which actions Copilot can perform.

3. Google and Salesforce Just Upgraded Their AI Fling — Now With Gemini in the Mix 🔥

Salesforce and Google announced an expansion of their AI partnership, deepening integrations between Salesforce’s Agentforce 360 platform and Google’s Gemini models. The collaboration enables enterprise customers to build AI agents using Gemini’s multimodal capabilities (handling image, audio, and video) and deploy Salesforce infrastructure on Google Cloud, giving users more flexibility and choice in their AI stack.

They’re also tying together Google Workspace and Slack with Salesforce’s systems, so workflows, data, and AI reasoning become more tightly woven across tools people already use.

4. Canva Set to Unleash AI Agents for Design and Marketing �*

Canva is close to rolling out its first phase of agentic AI workflows within weeks, according to chief product officer Cameron Adams at NVIDIA’s AI Day Sydney 2025, as reported by Information Age.

These new agents will act as active teammates in design, marketing, and sales tasks, promising to streamline project work beyond just typing prompts. With Canva’s user base ballooning to 250 million monthly users and compute costs soaring, the company is betting big on AI-powered collaboration tools that could scale businesses and make creative teamwork more accessible.

5. Claude Unveils ‘Skills’ for Smarter AI Workflows 🛠️

Anthropic just rolled out “Skills,” a game-changing update that lets Claude load custom instructions, scripts, and resources for specialized tasks, according to an official company announcement. Users can now build their own skills or tap into pre-made options, making Claude smarter at everything from accounting to brand content.

This move means AI can finally work with tools like Excel, PowerPoint, and Notion in ways that actually follow company standards, slashing manual work and boosting productivity.

🦾How You Can Leverage:

Why's the AI math not mathing? 

More than 90% of enterprise leaders say AI adoption is a top priority but less than 10% have actually deployed it company-wide.

Huh?

That gap ain't an accident, y'all. There's three specific bottlenecks killing implementation while your competitors figure out the workaround.

Jeetu Patel, President and Chief Product Officer of Cisco, showed up to Everyday AI with the dang playbook.

As the executive running AI infrastructure, security, and operations for some of the world's largest enterprises, Jeetu's seen every failure pattern and knows exactly what separates the 10% winning from the 90% stuck.

His insights?

On point, like a decimal.

Jeetu broke down the three big bottlenecks blocking AI adoption, revealed why data centers are being built where power exists instead of where companies need them, and explained how smart executives are securing competitive advantages right now.

Wanna know the future of enterprise AI? Learn from someone literally building it.

Let's get it.

1 – Infrastructure Wars: Secure Capacity or Watch From Sidelines 🔥

$20 monthly? Lost money. $200 monthly? Still bleeding cash. Next up? $2,000 plans, then $20,000.

That's not broken pricing, fam. That's infrastructure scarcity showing you what real enterprise demand looks like when supply can't keep up.

Jeetu's take on this is wild: Data centers are being built where power EXISTS, not where companies actually need them. Token generation is becoming national security infrastructure because countries figured out the economic prosperity connection.

The $5 trillion question? Who secures capacity first.

Here's Jeetu's warning: Companies that started experimenting early are finding what works. The ones waiting for "perfect technology" are falling further behind every quarter.

His move? Start now with whatever infrastructure you can get, because everyone's competing for the same limited GPUs and power grids

Try This

Call your data center provider Monday and ask about power availability and GPU access for Q3 2025—actual timelines, not sales talk.

Map three workflows that could run autonomously if compute wasn't the constraint. That's your real roadmap.

Project your AI spend 18 months forward at 3x growth. Show your CFO before budget season locks you out.

Pick the business unit with highest ROI per compute hour and give them capacity first. Stop spreading infrastructure thin across departments hoping something sticks.

2 – Trust Deficit: Your Models Are More Vulnerable Than You Think 🚀

Large language models are nondeterministic. Same question, different answers every time.

Yet you're building mission-critical business systems on this.

Jeetu's team at Cisco jailbroke DeepSeek 100% of the time within 48 hours using Harm Bench benchmarks. Every vulnerability exposed before companies deployed it.

Ask a model to build a bomb and it refuses. Ask it to write a movie script where Brad Pitt builds a bomb? Suddenly you've got detailed instructions.

That's a jailbreak, and hackers are way better at this than your security team.

Jeetu's play for developers: Stop building security stacks from scratch. Use guardrail APIs and innovate without paranoia breaking your timeline.

The companies winning on trust? They're validating continuously every time they retrain models, not running annual audits and hoping for the best.

Try This

Spend 30 minutes Thursday trying to break your customer-facing AI. Ask it to generate content your brand would never publish. Document what slips through.

Assign someone to roleplay a malicious user for two hours manipulating outputs through creative prompts.

Six months into AI deployment without algorithmic security testing? You're already vulnerable. Schedule that pressure test this week.

Compare guardrail API costs against building in-house security. Most teams are shocked at the difference.

3 – The Machine Data Blindspot: 55% of Growth You're Ignoring ⚡

Most companies think their proprietary customer data is their competitive moat.

Jeetu's reality check: 55% of global data growth is machine-generated now. Not human content. Machine logs from autonomous agents working 24/7.

We've exhausted publicly available internet data for training models. Models now run on synthetic data and machine logs showing what agents did, when, and what happened next.

That's completely different from human documents and emails your data team knows how to handle.

Jeetu's insight? Correlate machine data with human context for actual differentiation. But most companies organize information like it's 2020, optimized for document search instead of time-series analysis.

His team built infrastructure specifically for machine data streams. The pattern he's seeing? Autonomous execution jumped from 20-minute tasks to 30-hour coding sessions generating massive data streams.

Most companies ain't equipped to capture that value.

Try This

Audit what percentage of your data growth is automated systems versus humans. Most executives don't know this number.

Pick your highest-volume automated workflow. Connect those machine logs to an LLM in a pilot by month-end.

Ask your data team about time-series machine data retrieval Tuesday. If they look confused, you found your gap.

Prioritize AI integration for workflows already generating machine data instead of manual processes needing complete overhauls.

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