Lenno questions whether it's really just about fixing whatever's in front of you and calling it a plan. And Bren lays out his theory that 80% of businesses are successful enough to never really need to change, so they throw money at data and AI initiatives without ever fully believing in them.

The episode revolves around what really drives change, and what happens to the companies that keep buying the buzzwords instead of tackling problems?

Takeaways

• Problem-first approach
• Influence of mindset and collaboration
• Challenges of data ownership
• Impact of data and AI on businesses

Chapters

• 00:00 The Impact of Data and AI on Businesses
• 02:40 Challenges of Data Ownership
• 04:19 The Role of Data Professionals
• 06:33 Influence of Mindset and Collaboration
• 09:26 Freedom and Curiosity in Data Initiatives
• 18:36 Driving Change in Business
• 26:05 The Role of Data Professionals in Business Evolution
• 33:16 The Need for a Problem-First Approach

Peter shares what he's learned about building high-performing teams and creating genuinely inclusive environments for neurodivergent individuals.

The conversation also touches on the leadership challenges and opportunities in managing a neurodiverse team. One question stands out...how many teams have been quietly built in one leader's image, filtering out the very differences that would have solved their hardest problems?

This is a conversation about building teams that think differently on purpose, not by accident.

Takeaways

• Neurodiversity in the workplace
• Leadership and neurodiversity

Chapters

• 00:00 Introduction to Neurodiversity
• 08:27 Understanding Neurodivergent Individuals
• 21:09 Leadership and Neurodiversity

Lenno tells the story of the first SAP program, one that had to be pulled apart mid-flight. This painful lesson meant the next one, built on those battle scars, came in pain-free, on time and under budget.

That's the essence of the episode...real capability comes from getting it wrong first. So what happens when AI removes the junior roles where those mistakes used to be made before becoming a data leader?

Takeaways

• People are central to the success of transformation initiatives.
• Experience and learning from past mistakes are crucial for personal and professional growth. Transformation and experience are essential for growth.
• Behaviour change is hard, and people problems are a significant challenge in data leadership.

Chapters

• 00:00 The Importance of People in Transformation
• 01:16 Challenges of Transformation
• 03:07 The Value of Experience in Learning and Growth
• 15:13 Transformation and Experience
• 16:18 People Problems and Behavior Change
• 17:28 The Impact of Technology on the Workplace
• 18:15 Influence of Generational Differences
• 19:13 The Role of Data Leaders in Shaping the Future of Work
• 19:28 The Importance of Communication and Education
• 20:26 Individuality and the Human Component in Data Leadership

Alberto talks through the power of "why," the questions he uses to get people past surface answers like money, and the team assessment he built to measure purpose and psychological safety alongside trust and clarity.

The conversation also looks at courage and the relationship with purpose, and why staying in a role that doesn't fit your purpose is usually the bigger risk.

They discuss how understanding and aligning with your purpose can lead to greater fulfilment, better decision-making, and navigating technological changes like AI.

Guest

Alberto Gonzalez Otero - https://www.linkedin.com/in/albertogotero/

Chapters

00:00 Introduction to Alberto Gonzalo Otero and Purpose

00:59 What is Purpose and Why It Matters

03:04 Purpose During the COVID-19 Pandemic

05:03 AI, Technology, and the Future of Work

07:05 The Midlife Crisis and Purpose

08:07 Purpose Across Generations

09:01 The Impact of AI on Jobs and Society

10:57 Using Purpose to Make Better Decisions

13:12 The Role of Leadership and Team Dynamics

15:57 The Value of Purpose in Innovation and Technology

20:09 Balancing Technology and Human Values

24:05 Aligning Work with Personal Purpose

28:04 The Power of Asking 'Why' and Purpose

32:58 Team Dynamics and Purpose

37:08 The Courage to Follow Your Purpose

41:09 Overcoming Societal and Personal Barriers

43:57 Practical Steps to Discover Your Purpose

44:55 Closing Remarks and Final Thoughts

This episode digs into why data sovereignty and geopolitics get all the corporate attention, while the far bigger risk sits closer to home.

And ultimately they address the question that you can spend a billion dollars on security, but what's the point if it only takes one person to undo it?

This is a sharp reminder that everything we write on a work account, or hand over to an app, has become a monetizable asset, whether we intended it to or not.

So if our data is worth buying, shouldn't we be the ones getting paid for it?

From there, they ask if AI is making customer service better, or if people are quietly rejecting it in favour of a real human

They also unpack a LinkedIn story about connecting family calendars to ChatGPT instead of talking to their own kids.

Honest, a little ranty, and very human so exactly the conversation the call centre script never lets you have.

They discuss declining global birth rates and shrinking workforces, and what that means for healthcare, economic growth, and data privacy as health tracking gets more personal.

There's also a cheeky ChatGPT sign, and an AI-planned run that did not go as planned.

Warm, candid, and thinking out loud as always, this is the conversation still finding its shape in real time.

They start with why ChatGPT's real genius wasn't the model, but the humble Google-style search box that let everyone in from day one.

From there, Lenno shares his own hands-on testing of AI models on messy address data, and the pair compare Klarna's AI-first retreat with IKEA's decision to retrain its workforce instead of replacing it.

Warm, candid, and refreshingly honest, Brendan and Lenno keep circling back to the same conclusion: however far the technology goes, this is still a people problem.

Brendan and Lenno dig into why data governance gets written off as boring right up until someone rebrands it "AI enablement" — and why light, iterative guardrails tend to beat giant upfront frameworks that nobody ends up using.

From an Excel spreadsheet that quietly wrecks someone else's day to the Rubik's Cube problem of every data decision rippling sideways, they trace how the post-COVID shift to screens has cost us the "collision conversations" that used to build trust before things went wrong.

It all lands on the same place: data is the output, people are what bring it to life.

Starting with pricing (why token costs, like mortgage rates or SaaS subscriptions, are unlikely to stay this low), is a price hike inevitable? And what happens if you have AI in critical processes when costs skyrocket?!

A question that hits hard was if agentic AI can do the work of offshore teams, what happens to the people behind those jobs, and whose responsibility is it to plan for that?

Warm, unscripted, and more than a little uneasy by the end.

This episode tackles a question the data community has been circling for a decade without answering, "Who is actually accountable for data quality, and why does it never seem to stick with any one role?"

Lenno shares a story from the world of a highly regulated chemicals business, asking when the data is wrong, whose responsibility is it to fix it?

Both mull over data accountability and workplace safety culture, arguing that most people notice when something's broken and just expect someone else to deal with it. Finally, asking why the technical side of a data leader's job is often the easiest part.

Honest, unpolished, and packed with real examples from the front line of enterprise data.

In this debut episode, they dig into why the data world keeps repeating the same mistakes decade after decade, and why the arrival of AI hasn't changed that as much as people think.

From dashboards nobody uses to AI projects launched before anyone's asked the right questions, Brendan and Lenno make the case that technology isn't the problem...people are.

They explore the growing tension between Gen Z entering a workplace they don't fully understand, and leaders who've stopped asking why in favour of getting answers faster. Is AI making us more curious, or quietly making us lazier thinkers?

Warm, candid, and refreshingly honest, this is the conversation the conference stage never quite gets to.