The $40M AI Advantage: How Dell, ANZ & Mastercard Are Able To Execute 10x Faster

There’s a scene that lives rent-free in the minds of every 80s action junkie.

Jean-Claude Van Damme.

Two trucks.

One foot on each.

Engines rev and he holds the split 🤯

It’s also the perfect metaphor for what most companies are trying to do with AI adoption right now.

They’ve got one leg on “Old School Ops” and one foot dangling over “New AI-Powered Workflows”.

Don’t be that company.

If you want your team to actually use AI, this edition is for you!

First, figure out how they really think about it.

Then, steal the exact tactics below from the companies that are making AI adoption a no-brainer.

The 5 Types of AI Mindsets In Your Team

Your ability to get the team onboard is crucial.

AI isn’t a tool problem. It’s a people problem.

When it comes to getting your team to adopt AI, you’ll run into a mix of predictable mindsets according to Rogers’ diffusion theory and BJ Fogg’s behaviour model.

Here’s what you’re up against 👇

1. The Innovators (5%)

🧠 Behavioural Insight:

• Intrinsically motivated early adopters.

• High curiosity, low resistance.

🛠️ How to Manage:

• Give them a sandbox + spotlight.

• Let them experiment, then showcase their wins to the wider team.

Bonus tip: Microsoft launched a Frontier program - an experimental lab designed for early adopters like this to engage with cutting-edge AI tools and agents focused on productivity and work.

It can offer your team the opportunity to test and provide feedback on the latest AI innovations before they become widely available.

2. The Early Majority / Achievers (35%)

🧠 Behavioural Insight:

• Outcome-driven, logical adopters.

• Motivated by reward and reputation.

🛠️ How to Manage:

• Tie AI use directly to performance metrics.

• Make it a lever, not an experiment.

3. The Skeptics / Risk Managers (20%)

🧠 Behavioural Insight:

• Anchored in loss aversion and fear of error.

• Want control, not chaos.

🛠️ How to Manage:

• Show safety nets, not just features.

• Give them tools with audit trails, explainability, and guardrails.

4. The Bystanders (25%)

🧠 Behavioural Insight:

• Not anti-AI, just ambivalent.

• Lack of trigger or ability.

🛠️ How to Manage:

• Make AI the path of least resistance. 

• Bake it into their existing workflow.

• Don’t ask them to “learn,” just let them “use.”

5. The Resistors / Identity Defenders (15%)

🧠 Behavioural Insight:

• See AI as a threat to autonomy, competence, or status.

🛠️ How to Manage:

• Reframe AI as augmentation, not replacement.

• Highlight how it supports their expertise, not erodes it.

Bonus: The Social Influencers

• They exist in any persona group and are very influential.

• Make up about 10–15% of your workforce.

• Winning these people early is the unlock for faster org-wide adoption.

🧠 Behavioural Insight:

• Highly influential peers, often not in leadership roles.

🛠️ How to Manage:

• Enlist them early.

• If they adopt and endorse it, the rest follow faster.

Steal This Simple AI Adoption Strategy:

1. Target Innovators + Influencers first → let them spark momentum.

2. Then enable the Early Majority with structured use cases + rewards.

3. Slowly nudge Skeptics and Bystanders with education + ease.

4. For Resistors? Reframe. Protect their identity. Show them AI doesn’t replace, it enhances.

How The Best Companies In The World Are Approaching The Challenge

Most companies are playing with AI.

A few are winning with it.

Here’s exactly what the winners are doing, plus and the numbers to back it up 👇

1. Shoosmiths: Incentivising AI Usage with a £1M Bonus Pool

• UK-based law firm Shoosmiths introduced a £1 million bonus pool to encourage staff to collectively use Microsoft Copilot one million times within a fiscal year.

• AI is now integrated into their daily workflows, enhancing client service and operational efficiency.

2. San Antonio Spurs: Streamlining Operations with ChatGPT

• The San Antonio Spurs have adopted ChatGPT to enhance data analysis and community engagement.

• It is currently saving employees over 1,800 work hours each month.

3. Mastercard: Revolutionising Fraud Detection and Personalisation

• Mastercard employs AI to safeguard over 159 billion transactions annually, significantly enhancing fraud detection rates.

• They are using AI tools like Shopping Muse and Agent Pay to improve customer experiences through personalised product recommendations and secure transactions.

4. ANZ Bank: Boosting Developer Productivity with GitHub Copilot

• ANZ Bank conducted a six-week study involving approximately 1,000 software engineers to assess the impact of GitHub Copilot - check out the results 👇

  • Engineers using Copilot completed tasks 42% faster than those who did not.

  • Participants reported a notable boost in productivity and code quality.

  • The tool positively influenced their ability to perform specific functions, although improvements in code security were not statistically significant.

5. Dell Technologies: Launching the AI Factory with NVIDIA

• At Dell Technologies World 2025, Dell unveiled the AI Factory in collaboration with NVIDIA, aiming to simplify and accelerate AI adoption for enterprises.

• The AI Factory reduces setup time by up to 86% compared to traditional methods.

• It is offering a comprehensive suite of AI solutions, including agentic AI capabilities and streamlined deployment processes.

The best companies aren’t just dabbling AI, they’re embedding systems around it.

Don’t wait for the perfect AI strategy.

Steal what’s working, start small, and build the muscle.

Your Challenge This Week

If you want to avoid the Van Damme split and stay standing, here’s the exact framework I use to help high-performing exec teams with AI adoption:

1. Start with “Jobs To Be Done”

Don’t start with the tool. Start with the job.

• Ask: What’s one thing that takes too long, costs too much, or blocks growth?

• Then ask: Can AI make this 10x faster or cheaper?

👉 Example: Klarna saved $40M by replacing 700 copywriters with AI.

2. Create a Playground

People don’t learn AI by reading PDFs. They learn by playing.

• Give your team “AI Fridays” (1hr a week to explore).

• Incentivise wins. “First person to automate a task with AI this month gets dinner on the company.”

👉 Example: HubSpot gave teams a 30-day challenge: Use AI to automate one part of your job. No pressure, just play. Result? Internal AI usage shot up 200%.

3. Assign AI Champions (Not IT)

Every team needs an “AI Captain”. This is someone who’s 10% ahead of the curve and pulling others forward.

• Ops has one. Sales has one. CS has one.

• Make it a badge of honour, not a chore.

👉 Example: At Bain & Co, AI champions were embedded in departments. They weren’t from IT. They were peers with credibility which meant adoption skyrocketed.

4. Measure Behaviour, Not Just Output

Track:

• % of team using AI weekly

• % of AI-driven process changes

• Time saved per department

👉 Example: Microsoft measured Teams meetings after rolling out Copilot. The stat? 29% fewer meetings and 1.2hrs saved per person per week. That’s the metric that gets execs excited.

Good luck and let me know how you get on 🫡

MY TOP FINDS OF THE WEEK 🏆

For Your Performance

• DoorDash CBO’s “how to work with me” doc is a must for any senior leader (LinkedIn)

For Your Team

• Microsoft CPO on how your teams can become even more valuable by using these AI best practises (Podcast)

For Your Health

• Brain Expert Daniel Amen on what foods are linked to brain fog, memory loss nd long-term cognitive decline (DOAC clip)