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071: Hope is NOT an AI Strategy — Nathan Bell, Kearney
Your board has an AI strategy. It's probably rubbish.
Nathan Bell has spent 25 years delivering transformation programmes inside the world's biggest telcos. Now a Partner at Kearney, he's the person companies call when the proof-of-concept graveyard keeps growing and the CFO starts asking uncomfortable questions.
In this episode: why most AI programmes are expensive theatre, how to actually get ROI, and why your change management track record matters more than your technology choices.
We also get into agentic AI gone wrong — a recruiting agent that only wanted to hire golfers, a CEO town hall that triggered a queue at HR, and an AI agent that doxxed a developer and got its creator hired by Sam Altman. Make of that what you will.
Plus rapid-fire telco takes and a deeply scientific Australia vs Netherlands lifestyle quiz that ended in a draw.
Time Stamps:
00:00 — AI Strategy Hype vs Reality: Why Most Exec Talk Is Rubbish
00:37 — Is This AI Wave Different from Dot-Com, Cloud, and 5G?
02:19 — From Boardroom Buzz to Production: The Proof-of-Concept Trap
03:44 — How to Actually Get ROI: Start Small, Make Big Bets, Fund Like a VC
06:47 — Low-Hanging Fruit: Internal Knowledge, Customer Service, and Procurement
09:16 — Metrics That Matter: MVP Milestones Over 2-Year "Goals"
11:21 — Making the VC Model Real: Phased Rollout and Cultural Change
13:26 — Market Whiplash: When AI Adoption Threatens Your Revenue Model
14:51 — AI as a Business Capability, Not a Shopping List of Tools
16:10 — Agentic AI and the Human Factor: Bias, Process Drift, and Set-and-Forget Myths
21:10 — The People Side of Agents: Fear, Trust, and How Leaders Miscommunicate
24:41 — Why AI Transformations Fail: Change Management and HR as the Quarterback
26:44 — When Agents Go Rogue: The Python Library Incident and What It Signals
28:28 — Who's Responsible for AI Agents? Why Human-in-the-Loop Still Matters
29:19 — When AI Monitors AI: The Two-Agent Marketing Campaign Story
31:03 — Legacy, Culture and Operating Model: Why Big Firms Struggle to Adopt AI
33:49 — Ethics, Bias and Copyright: The Legal Minefield of Generative AI
35:40 — Who's Winning with AI and Why: Consumer Goods, Banks and Telcos
38:01 — Regulation Reality Check: EU AI Act, Vendor Audits and the Air Canada Case
39:37 — Where Telcos Should Start with AI: Customer Service, Vendors and Billing
41:41 — Transformation Lessons from Telcos: People, Forgive the Past, Progress Over Perfection
44:39 — AI Hype vs Jobs Reality: Using AI to Augment People, Not Just Cut Headcount
46:51 — What Still Motivates Transformation Leaders + Rapid-Fire Telco Takes
51:49 — Finale: Australia vs Netherlands Quickfire (and a Perfect Tie)
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By Charles Reed Anderson
5
11 ratings
Your board has an AI strategy. It's probably rubbish.
Nathan Bell has spent 25 years delivering transformation programmes inside the world's biggest telcos. Now a Partner at Kearney, he's the person companies call when the proof-of-concept graveyard keeps growing and the CFO starts asking uncomfortable questions.
In this episode: why most AI programmes are expensive theatre, how to actually get ROI, and why your change management track record matters more than your technology choices.
We also get into agentic AI gone wrong — a recruiting agent that only wanted to hire golfers, a CEO town hall that triggered a queue at HR, and an AI agent that doxxed a developer and got its creator hired by Sam Altman. Make of that what you will.
Plus rapid-fire telco takes and a deeply scientific Australia vs Netherlands lifestyle quiz that ended in a draw.
Time Stamps:
00:00 — AI Strategy Hype vs Reality: Why Most Exec Talk Is Rubbish
00:37 — Is This AI Wave Different from Dot-Com, Cloud, and 5G?
02:19 — From Boardroom Buzz to Production: The Proof-of-Concept Trap
03:44 — How to Actually Get ROI: Start Small, Make Big Bets, Fund Like a VC
06:47 — Low-Hanging Fruit: Internal Knowledge, Customer Service, and Procurement
09:16 — Metrics That Matter: MVP Milestones Over 2-Year "Goals"
11:21 — Making the VC Model Real: Phased Rollout and Cultural Change
13:26 — Market Whiplash: When AI Adoption Threatens Your Revenue Model
14:51 — AI as a Business Capability, Not a Shopping List of Tools
16:10 — Agentic AI and the Human Factor: Bias, Process Drift, and Set-and-Forget Myths
21:10 — The People Side of Agents: Fear, Trust, and How Leaders Miscommunicate
24:41 — Why AI Transformations Fail: Change Management and HR as the Quarterback
26:44 — When Agents Go Rogue: The Python Library Incident and What It Signals
28:28 — Who's Responsible for AI Agents? Why Human-in-the-Loop Still Matters
29:19 — When AI Monitors AI: The Two-Agent Marketing Campaign Story
31:03 — Legacy, Culture and Operating Model: Why Big Firms Struggle to Adopt AI
33:49 — Ethics, Bias and Copyright: The Legal Minefield of Generative AI
35:40 — Who's Winning with AI and Why: Consumer Goods, Banks and Telcos
38:01 — Regulation Reality Check: EU AI Act, Vendor Audits and the Air Canada Case
39:37 — Where Telcos Should Start with AI: Customer Service, Vendors and Billing
41:41 — Transformation Lessons from Telcos: People, Forgive the Past, Progress Over Perfection
44:39 — AI Hype vs Jobs Reality: Using AI to Augment People, Not Just Cut Headcount
46:51 — What Still Motivates Transformation Leaders + Rapid-Fire Telco Takes
51:49 — Finale: Australia vs Netherlands Quickfire (and a Perfect Tie)