Autonomous AI applications are no longer speculative technologies nor are they just about self-driving cars. Autonomous AI embedded in vehicles, drones and a variety of other vehicles are creating a fundamental shift in how industries operate, move goods, respond to crises, and maintain infrastructure.
In this episode of the AI Adoption Podcast, I am joined by Dr Madeline Cheah, a leading voice in cybersecurity and AI assurance with Cambridge Consulting, Capgemini’s deep tech arm, to explore the landscape of autonomous AI applications and their implications.
We discuss what makes a system “autonomous,” how autonomous applications are deployed across industries, and what organisations must do to adopt them responsibly.
Key Highlights:
• Autonomous vehicles in action across agriculture, logistics, rail, and emergency services
• Safety and efficiency gains from reducing human involvement in high-risk tasks
• The risk landscape: cybersecurity, AI decision-making, and emergent behaviour
• AV supply chains that include open-source code, third-party datasets, and AI models
• Strategic guidance for business leaders: feasibility, safety, and system assurance
Chapters
00:00 Introduction to Autonomous Vehicles
04:35 Importance of Autonomous Systems
06:06 Autonomous AI Applications
10:57 Risks and Challenges of Autonomous Vehicles
15:48 Mitigating Risks in Autonomous Systems Development
18:34 Creating and Managing AI Supply Chains
20:50 Regulatory Considerations for Autonomous Systems
22:03 Priorities for Companies Implementing Autonomous Vehicles
24:15 Impact of Autonomous Vehicles on Employment
26:28 Societal Factors Driving Adoption of Autonomous Vehicles
𝐖𝐚𝐧𝐭 𝐭𝐨 𝐬𝐭𝐚𝐲 𝐮𝐩𝐝𝐚𝐭𝐞𝐝?
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