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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