In this episode of Praxi Pod, host Andrew Turner speaks with Ako Sabir about his extensive career in business transformation, focusing on the role of data and technology, particularly in the insurance sector. They discuss the unique challenges and opportunities within insurance, the critical importance of data in risk assessment, and the impact of AI on underwriting and claims processes. The conversation also touches on the necessity of regulatory compliance, the evolving awareness of leadership regarding technology, and the balance between innovation and risk management.

Ako shares insights on the importance of educating leadership on AI and the cautious approach needed for proof of concepts in integrating new technologies. In this conversation, the speakers delve into the complexities of implementing AI and technology in business, emphasising the importance of understanding use cases, operationalisation, and governance. They discuss the challenges faced in regulated industries and the necessity of a structured approach to data and technology strategies. The conversation also touches on the future of AI, the need for responsible use, and the significance of engaging leadership in driving transformation.

Takeaways

- Ako emphasises the importance of change and transformation in his career.

- He has worked across various sectors, focusing on data and technology for business transformation.

- Insurance presents unique challenges and opportunities for innovation.

- Data is fundamental in understanding risk and pricing in the insurance industry.

- AI can significantly enhance underwriting and claims processes.

- Regulatory compliance is a major challenge for insurance companies.

- Leadership in organisations is increasingly aware of the need for data and AI.

- There is a balance to be struck between innovation and risk management.

- Organisations must educate their leadership on the implications of AI.

- Proof of concepts should be approached with caution, focusing on practical applications. Invest time in understanding use cases before proof of concept.

- Operationalising AI requires a clear governance framework.

- Engage stakeholders early in the process for successful implementation.

- Data quality and trust are critical for AI initiatives.

- Business transformation is essential for successful AI adoption.

- Leadership engagement amplifies the impact of AI projects.

- Avoid chasing trends; focus on practical applications of AI.

- Incremental scaling of AI solutions is more effective than large-scale rollouts.

- AI should augment human decision-making, not replace it.

- The future of AI involves navigating complexities and ensuring accountability.

Chapters

00:00 Introduction to Ako Sabir and The Praxi Pod

03:01 Career Journey and Transformation Focus

06:00 Insights on the Insurance Sector

09:06 Data's Role in Insurance

11:59 Challenges in Financial Processes

14:58 Adoption of AI in Underwriting and Claims

18:03 Navigating Regulatory Compliance

21:04 Leadership and Technology Awareness

24:09 Balancing Innovation and Risk

27:11 Proof of Concepts and AI Integration

36:11 Navigating Technology Implementation Challenges

43:12 Operationalising AI in Regulated Industries

50:55 Transforming Business Through Data and AI

59:29 The Future of AI and Business Transformation