Welcome back everyone. I'm proud to say we bring you a special episode today.

I interviewed Dr. Kelly Monaghan, a researcher (and former leader at Upwork and Meta) and advisor to Fortune 1000 companies, about AI’s impact on workplace culture and the future of work.

Keep an ear out for my 7 hidden gems in this podcast 1. The "Power Paradox" of AI Adoption2. The Risk of "AI Peer Pressure"3. "Digital Exhaust" as a Competitive Advantage4. The Threat to "Expertise Dignity"5. Playing "Checkers vs. Chess" with Headcount6. The "Pilot" vs. the "Checkout" Model7. The $1-for-$1 Investment Rule

These are packed full of leadership advice and positive steps!

The areas you will love:

Rethink Business: Kelly argues generative AI should prompt leaders to rethink business purpose beyond shareholder maximisation, warning of a crossroads between human flourishing and inequality-driven displacement.

AI Is Transformation: She emphasises AI adoption is primarily a prioritisation and change-management challenge, not just tooling, and uses her “elevator/skyscraper” analogy to push leaders toward workflow redesign rather than doing the same work faster with fewer people.

Human First Approach: We discuss preserving human decision-making (e.g., pilots, human checkout), risks of agentic AI increasing complexity and governance/legal exposure (e.g., healthcare claims), and research showing heavy AI users may trust AI over colleagues, potentially eroding workplace connection.

The AI Business Metrics: Kelly advises defining AI skills, measuring readiness, focusing on growth metrics like revenue per employee, clarifying company purpose and AI principles, and investing in upskilling alongside technology.

Kelly also has a forthcoming book coming out called “Reclaim the Plot” and it sounds like the perfect way to address work issues.

Please connect with Kelly below

• Personal site - https://drkellymonahan.com/
• Company site - https://www.beyondthedesk.com/
• LinkedIn - https://www.linkedin.com/in/kelly-monahan-ph-d-18879413/

As it is an AI Moment interview here are the chapters to go through if you are short on time:

00:00 Meet Dr Kelly

01:03 AI Purpose and Workforce

03:06 Adoption Guardrails and Priorities

05:41 Elevator Moment Workflow Redesign

07:11 Human in the Loop and Agentic Risks

17:05 Remote Work Politics and Power

27:04 Reclaim the Plot

29:30 HR Takes Back the Layoff Story

32:34 Metrics That Value People

38:47 Align on Purpose and Principles

41:34 Human And/Plus AI To Improve Work

43:30 Three Leadership Principles

In this episode, Jonathan and I dive into the practical applications of voice AI that go far beyond simple voice-to-text.

We start by looking at the "surprise moments" in our workshops, where leaders realise they can use their phones to simulate high-pressure business environments.

We discuss how a hotel group used ChatGPT to train receptionists by role-playing as a complaining customer, providing immediate coaching on how to improve the interaction.

We also explore the "unlock" of using voice for strategic documentation. I share a personal example of how Jonathan helped a sales leader turn a quick conversation into a full strategy document using Gamma, reducing a day’s work to mere minutes.

We look at the broader business impact, such as how IKEA used voice analysis to discover a massive demand for interior design services, turning a cost-saving exercise into a new revenue stream.

Finally, we address why voice is such a powerful tool for those who find writing a barrier, including individuals with dyslexia, and how tiny lapel mics are becoming a new norm in the London startup scene to facilitate constant AI collaboration.

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In this episode of The AI Moment, I sat down with Jonathan Wagstaffe to tackle one of the most pressing questions for modern business leaders: Is it time to build your own company LLM? We move past the hype of "building from scratch" to discuss the practical realities of the Rent, Buy, vs. Build framework.

We explore why context is the new currency in AI. It is no longer enough to simply use a public model; to gain a competitive edge, businesses need to integrate their own operating procedures and product ecosystem into the AI's workflow. However, this isn't without significant risk. We discuss the "dull, boring" but essential issue of data quality, noting that messy or fragmented data will undermine even the most sophisticated AI ambitions.

The conversation highlights Yahoo Scout as a leading example of the "hybrid model"—taking a powerful base like Claude and layering specific data on top to create a specialist tool. For leaders, the takeaway is clear: be mindful of the exploding costs of token usage and the scarcity of AI expertise. Instead of chasing a "naked LLM," focus on building the proprietary guardrails and intelligence layers that turn a generic tool into a powerful business asset. As the enterprise space evolves rapidly toward the summer of 2026, staying agile with a hybrid approach is your best bet to avoid being "cleaned out" by rapid platform shifts