Is traditional hierarchy slowing organizations down in the AI era?

In this CIO Talk Network conversation, Sanjog Aul is joined by Alexandre Kozlov of ABB, Andrea Heekelaar of Renault Dacia Brand, and Mahendra Beharie of DHL to explore how leadership models are evolving in response to AI, innovation, distributed teams, and changing workforce expectations.

The panel discusses balancing agility with governance, enabling innovation without chaos, scaling AI initiatives responsibly, and redefining leadership for a hybrid human-AI future.

Key themes include:

• Leadership beyond command-and-control structures
• Product-based and agile operating models
• Human-centered leadership in AI-driven organizations
• Controlled experimentation and governance
• Scaling AI across global enterprises
• Building cultures that embrace change and innovation

• AI and leadership evolution
• Organizational flexibility
• Product operating models
• Agile and SAFE frameworks
• AI governance and ownership
• Innovation enablement
• Human leadership qualities
• Future-ready organizations

00:00 Introduction
02:17 Leadership structures under pressure
08:37 Controlled chaos and innovation
12:05 Experimenting with organizational design
24:08 AI disruption and urgency
30:15 Risks of rushing AI adoption
41:12 Scaling AI in global enterprises
49:42 Leadership self-reflection
57:19 Closing thoughts

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CIO Talk Network features global conversations with technology and business leaders focused on leadership, innovation, AI, cybersecurity, transformation, and the future of enterprise.

As AI agents move from experimentation to execution, enterprises are realizing that speed and efficiency are no longer the hardest problems to solve. Accountability is.
In this CIO Talk Network conversation, host Sanjog Aul speaks with Aarti Singh, Enterprise CIO at Mahindra Group, to examine how leaders should think about responsibility, governance, and trust in an increasingly agentic AI environment.

The discussion explores:
Where leaders draw boundaries for autonomous AI agents
Why explainability matters in real enterprise decision-making
The risks introduced by third-party and black-box AI agents
How organizations should respond when autonomous systems fail
Why culture, not just controls, determines AI accountability
This episode reframes agentic AI as more than a technology choice. It is an operating model and leadership challenge that demands alignment across business, IT, risk, and governance teams.
For CIOs and enterprise leaders navigating AI adoption today, this conversation offers grounded insight into balancing innovation with responsibility.

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https://www.youtube.com/@ciotalknetwork

▶️ Watch on Vimeo
https://vimeo.com/ciotalknetwork

🔗 Explore more CIO Talk Network conversations
https://www.ciotalknetwork.com

About CIO Talk Network (CTN)
CIO Talk Network brings senior technology and business leaders together to discuss real decisions, real risks, and real leadership responsibilities in a digital-first world.

Organizations want the speed that AI promises, but they also need judgment.
In this episode, Earl Newsome, CIO at Cummins, and Viren Shah, Chief Digital and Information Officer at AGCO, join Sanjog Aul to discuss why the CIO should help guide ethical and responsible AI adoption.

They share lessons on trust, safety, value creation, team readiness, and what leaders must do to make AI work for everyone.

Topics Covered

00:00 – Introduction
02:45 – AI pressure vs leadership responsibility
06:30 – Balancing ambition with judgment
10:55 – What responsible AI really means
15:20 – The role of human guidance
19:40 – Empowering teams while protecting the enterprise
24:30 – Rethinking how AI value is measured
29:15 – Choosing when to say yes or no
33:40 – The evolving role of the CIO
38:10 – How organizations should structure AI ownership
42:00 – What leaders want to shape in the next few years

Full transcript: https://www.ciotalknetwork.com

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About CIO Talk Network

CIO Talk Network is a global community where business and technology leaders share experiences, challenge assumptions, and learn from each other. Every episode is designed to provide clarity, context, and real value without hype.