Show Notes: The 2025 AI Year in Review

Jonathan and I are sitting down to wrap up what has been a truly transformative year for the AI landscape

If 2024 was the year of hype, 2025 was the year of the "Great Separation," where we finally saw which players could execute and which were just blowing smoke.

This episode is a longer pod so here are the chapters to jump to if you are pushed for time:

00:00 Introduction and Year-End Reflection

00:22 OpenAI's Mixed Year

04:35 AI Market Trends and Investments

06:47 Google Gemini's Progress

09:48 AI Skillset and Workforce Impact

12:05 Microsoft Copilot's Struggles

16:21 Power and Infrastructure Challenges

19:38 Apple and Meta's AI Journey

22:45 AI Application Success Stories

28:52 Conclusion and Future Outlook

The Big Shifts of 2025

We dive deep into why Google Gemini has arguably won the year. While they started weak, they’ve successfully re-engineered their entire organisation around an AI ecosystem, delivering incredible tools like NotebookLM and Nano Banana.

On the flip side, OpenAI has had a mixed scorecard.

Despite holding 70% market share, they’ve faced a "Code Red" at year-end, pivoting away from broad "empire mode" experiments to protect their core LLM.

We also tackle the "Microsoft Problem".

Despite its reach, Copilot is struggling with user delight due to heavy corporate guardrails, leading to a disappointing adoption rate compared to sleeker apps like Gamma.

Key Takeaways

• The Skillset Advantage: Only 10-12% of knowledge workers are truly using AI. If you are investing time to learn these tools now, you are already in the global elite.
  
• Infrastructure is the New Wall: The West is facing a massive power generation crisis
• OpenAI alone may soon require energy equivalent to one-fifth of the US's current output.
  
• Time to Value (TTV): Tools like Gamma are setting the standard for "Time to Edit," allowing you to move from a recorded conversation to a finished strategy deck in minutes.
  

1. Stop the Start-Stop: If your company is stalling AI rollouts for "legal sign-off," you are losing ground every day.
   
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In this episode of The AI Moment, Jonathan Wagstaffe and I dive into a common failure mode we are seeing across the business landscape: the ‘start-stop’ motion of AI adoption.

Too many businesses treat AI implementation like a pit stop—they pull in to perfect their strategy or policy, but then struggle to get back into the race.

We discuss the real danger of ‘over-perfecting’ governance. While some leaders pause to hit 100% policy perfection, competitors and internal outliers race ahead at 70% readiness.

This creates a massive internal disconnect; when the company hits the brakes, enthusiastic employees often just go underground, building their own ‘shadow AI’ toolkits while the rest of the business stagnates.

Key Takeaways:

Measure Twice, Cut Once: Jonathan emphasises the importance of the ‘thinking phase’ before experimentation begins. Spending time defining playbooks and guidelines upfront prevents the frustrating scenario where Legal steps in weeks later to ban work that has already started.

Adopt 90-Day Sprints: To cure the start-stop cycle, we recommend working in 90-day sprints. Set your scope, run the sprint, and evaluate at the end. This structure prevents the distraction of constantly debating tool switches: like the recent Gemini vs. ChatGPT discourse & keeps the team focused on execution.

Leadership Clarity: Leaders must define three core themes and stick to them. This stability allows your AI champions to guide the rest of the team to maturity without the agenda constantly shifting.

Your Call to Action!

Stop aiming for a perfect policy that doesn’t exist. Establish your 90-day goals, empower your champions, and keep the momentum going.

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Thanks for listening

Danny Denhard

2026 Predictions: The Big Hack, Agentic Shopping, and Multiplayer AI

As we close out 2025, Jonathan and I decided it was time to get the crystal ball out and predict where the world of AI and business is heading in 2026.

While 2025 was about experimentation, 2026 is going to be the year of ROI, integration, and some serious security challenges.

Key Takeaways:

• The Big AI Hack is Coming: My first prediction is a sombre one. We have already seen the Claude MCP hack, but I believe we will see a major, targeted attack on the big LLMs or agentic systems in 2026 . Hackers follow the money, and with agents now able to take action on our behalf, the "black hat" incentive is huge .

• The End of "Blue Links": Jonathan predicts a massive shift in e-commerce. We are moving away from searching Google for a list of links to asking an AI to "find the best lawnmower" and having it present a single buy button . This means brands must offer pricing consistency; if your prices jump around, AI agents simply won't recommend you .

• Multiplayer AI: I believe the days of "single player" AI are numbered. 2026 will be the era of "Multiplayer AI," where teams collaborate with LLMs inside shared workflows rather than isolated chat windows . This will finally drive better cross-functional connection .

• Democracy’s Acid Test: We also discussed the upcoming US midterms . With the cost of creating deepfakes and AI content dropping to near zero, we expect a flood of disinformation that will test the limits of voter trust .

Take Action:

1. Audit Your Security: If you are using AI to write emails or manage tasks, double-check every hyperlink . Security against AI-assisted hacking must be a priority for 2026 .

2. Prepare for Agents: If you work in e-commerce, start thinking about how your product data appears to a machine, not just a human .

   
   

   Join the Conversation: We’d love to hear your own predictions. Drop us a line at ai@dannydenhard.com and don't forget to subscribe to our supporting newsletter at aimoment.co.uk for deeper analysis .

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• We will see you next time!

In this week’s episode of The AI Moment, Jonathan (Wagstaffe) and I (Danny Denhard) dive into a topic that is bothering a lot of people right now: the growing disconnect between corporate AI hype and actual customer sentiment.

We discuss the reality that while businesses are rushing to tell everyone "we are AI everywhere" to satisfy investors and earnings calls, consumers are becoming increasingly irritated!

In fact, recent surveys suggest up to 80% of customers dislike or simply don’t care about AI features.

They just want their problems fixed quickly and without friction or want a better, cheaper product.

Jonathan and I also explore the "AI bubble" where companies market to their industry peers rather than their users.

I share a breakdown of the current App Store revenue leaders, highlighting how giants like TikTok and Google One are outperforming many pure-play AI tools by focusing on utility rather than just the technology itself and yes I know these tools have AI built in but the utility and entertainment value is the hook not AI!

Key Takeaways:

• Stop Marketing "AI": Your customers don’t care how you solve their problem, only that you solve it. If you removed the label "AI," they would likely be just as happy if not happier, just having a product that works.

  
  

• Ignore the Peer Pressure: Don’t force chatbots or features just because competitors are doing it. This often leads to "random activity" rather than disciplined strategy.

  
  

• Empower the Front Line: Real innovation shouldn't be mandated from the boardroom. It comes from the people on the ground who understand the daily friction points customers face, yes listen to the board and market to partners, colleagues and shareholders with AI, you don't need to over do it with AI in consumer ads.

  
  

Call to Action:

If you want to move beyond the hype, focus on a "Human + AI" hybrid model.

Ask yourself: if we didn't mention AI, is this update still valuable?

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In this festive episode of The AI Moment, Jonathan and I tackle the panic that often surrounds the holiday season.

We move beyond the hype to discuss how you can use AI right now to reduce the Christmas "faff", from managing the dreaded office Secret Santa to ensuring you don't burn the turkey.

We explore practical, hands-on use cases for Generative AI to make your holidays smoother.

Whether it is finding a unique gift for a colleague you barely know or reformatting a family recipe for a gluten-free guest, AI can be your ultimate holiday assistant.

We also look ahead to 2025, sharing our "Santa Wishlist" for the features we want to see next, including better voice analysis and seamless app integration.

• Secret Santa Sorted: Stop worrying about what to buy for £10. We discuss how to prompt AI to give you 3 distinct options, practical, playful, and unique tailored to your colleague's interests.

• The "Leftover Christmas Chef": Don't let food go to waste. We explain how to use AI on Boxing Day to turn your fridge contents into creative, 20-minute meals.

• Dietary Inclusive Hosting: Hosting vegans or gluten-free guests? Learn how to use LLMs to adapt your traditional recipes instantly without losing flavour or upsetting your guests.

• Budgeting Assistant: We discuss using AI to keep your spending on track, helping you allocate funds across gifts and food without the emotional stress.

If you want to stay ahead of the curve and make AI actionable in your daily life, make sure you are subscribed to our newsletter. We dive deeper into these topics every Monday and Friday.

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Ho ho ho Jonathan and Danny

The AI Moment: AI Is More Than Just The Web

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In this week's episode of The AI Moment, Jonathan and I step away from the keyboard to explore the "extended world of AI." Too often, the conversation is dominated by chatbots and browser-based tools, but the most disruptive shifts are happening in the physical world.

We discuss the imminent arrival of autonomous vehicles, specifically Waymo’s launch in London scheduled for 2026. This isn't just a transport update; it marks a pivotal shift in how we trust technology.

Jonathan highlights a crucial technical detail often overlooked: these vehicles aren't relying on the cloud.

They run on Small Language Models (SLMs)—highly efficient, on-device AI that functions offline. This is a massive signal for business leaders: you don't always need a giant, expensive model to solve complex problems.

We also dive into the next generation of wearables: moving from watches to smart jewellery and glasses.

This brings us to the core tension of the episode: Privacy vs. Utility. We seem willing to trade our data for convenience, like a watch predicting the flu before we feel it.

However, I introduce the concept of "For Me vs. Against We." Smart glasses might be useful for me, but do they work against society by recording others without consent?

As we approach 2026, which we identify as the "ROI Year" for AI, understanding these physical and ethical implications is no longer optional.

Key Takeaways:

• The Rise of SLMs: Waymo proves that Small Language Models are robust enough for life-critical tasks. Businesses should look to SLMs for efficient, offline, and specific solutions rather than defaulting to massive LLMs.

• The 2026 Timeline: We agree that 2026 is the year AI ROI "explodes." If you are still struggling with your data strategy today, you will be left behind when the hardware ecosystem matures in two years.

• The "For Me vs. Against We" Test: Before adopting new tech (like smart glasses in the workplace), leaders must audit the social cost. Does the convenience for the user erode the trust of the wider team?

Quote of the Episode:

"Small language models, designed properly, can actually deliver an awful lot of performance." — Jonathan Wagstaffe

Do you have any questions for us? Contact us on ai@dannydenhard.com

How To Build AI Workshops That Actually Work - AI Moment Longer Episode 1

In this week's episode of The AI Moment, Jonathan Wagstaffe and I tackle a critical question facing almost every business leader right now: how do you run an AI workshop that actually changes behaviour?

Recorded on a day when half the internet (including ChatGPT) went down thanks to Cloudflare, we discuss why reliance on tools isn't enough you need resilience and a proper strategy. We break down the reality of the "AI bell curve" in your teams.

In any room of ten people, you’ll have two power users and two sceptics who refuse to engage. The magic happens when you can move that middle majority from fear to fascination.

• The Pre-Work Requirement: Why I never start a workshop without surveying the team first. If you don't know the problem they are solving, you are just teaching them features, not workflows.

• Breaking Muscle Memory: How to use practical exercises like "True or Fake" or "Vibe Coding" to force marketeers and sales teams out of their old habits and into immediate prototyping.

• The EIE Framework: My "Educate, Inspire, Entertain" model. If you aren't entertaining your team, you aren't removing the fear barrier.

• Sales Team Resistance: Why sales teams are often the hardest to crack but the quickest to convert once they see AI as a coach rather than a replacement.

Stop treating AI enablement as a "one-and-done" training day. You need to identify internal "Captains" and "Champions" to keep the momentum going. If leadership doesn't drive this top-down, you will remain stuck in a cycle of "start-stop" innovation.

Don't outsource your brain to an agency. Your goal must be self-sufficiency. Start your first internal experiment today—even if it's just getting your sales team to roleplay a difficult customer with an LLM. If you need a framework to get started, look at our "Educate, Inspire, Entertain" model or reach out to us for a workshop that moves the needle.

Want to go deeper on our newsletter that supports each and every episode at ⁠⁠dannydenhard.com/aipod⁠⁠

Got questions contact us on ai@dannydenhard.com or via our site ⁠dannydenhard.com/aipod

Thanks for listening!

Danny Denhard & Jonathan Wagstaffe

-- Danny on LinkedIn - https://www.linkedin.com/in/dannydenhard/

-- Jonathan on LinkedIn - https://www.linkedin.com/in/wagstaffe/

Show Notes: What Is Vibe Coding & How Could We Use It?

In this episode of The AI Moment, Jonathan and I tackle a phrase that has been buzzing around the industry this year: Vibe Coding. It might sound like just another buzzword, but for non-technical leaders, marketers, and product teams, it represents a massive shift in how we work.

We demystify what vibe coding actually is—essentially, using AI tools like ChatGPT, Claude, or Replit to "code up" solutions without needing a computer science degree. Whether it is automating a tedious weekly report that pulls data from five different sources or building a rapid prototype for a new campaign landing page, vibe coding is bridging the gap between having an idea and executing it.

Key Takeaways for you:

• It is for everyone: You don't need to be a developer. Tools like Relay and Zapier allow you to script simple automations, while more advanced environments like Lovable or Cursor let you build actual web apps.

• Speed to market: I shared how product teams are using this to test ideas. You can spin up a personalised landing page, run paid traffic to it, and validate a concept before committing expensive engineering resources.

• The "Backend" Warning: We discussed a critical reality check. AI can build a beautiful interface, but you must ensure the plumbing (like email triggers or CRM updates) actually works.

• Security First: A major watch-out from the episode—AI doesn't always follow security best practices. Be careful not to leave sensitive API keys or user data exposed in your generated code.

Don't be intimidated. Our advice is to start small. Go and play with a tool like Relay today. Try to script one boring task you do every week. It is about building confidence in a safe environment so you can eventually speed up your entire workflow.

Tools Mentioned: Relay, Zapier, Replit, Figma, Lovable, Claude, Cursor.

Thanks for listening today Danny Denhard & Jonathan Wagstaffe

• Danny on LinkedIn - https://www.linkedin.com/in/dannydenhard/

• • Jonathan on LinkedIn - https://www.linkedin.com/in/wagstaffe/

Want to go deeper on our newsletter that supports each and every episode at ⁠⁠dannydenhard.com/aipod⁠⁠

Got questions contact us on ai@dannydenhard.com or via our site ⁠dannydenhard.com/aipod