Yesterday, we were honoured to host this event with our brilliant guest speaker Pilar Santamaria. This was a seriously high-level presentation and discussion of the implications of not adopting AI technology swiftly and correctly, and the critical importance of employing an entrepreneurial mindset with ownership at board level.

It was noted with interest, that the UK is slightly behind the curve, exemplified by the role of Chief AI officer being mostly prevalent in the US but this appears likely to change very soon.

Some of the key take aways were:

Key Challenges in Monetising AI

1. Market Analysis: Traditional market analysis often lacks actionable insights.
2. Competitiveness: Standard ideation and development cycles may not align well with AI’s needs due to:
3. Lack of clear objectives.
4. Misalignment with business strategy.
5. Need for robust data strategies for effective AI integration.
6. Requirement for iterative improvement and regular updates.
7. Necessity for cross-functional collaboration.

New Target and Serviceable Markets

1. Budget-Centric Use Cases: Focus on cost-effective AI applications that provide a clear ROI.
2. Establish specific benchmarks for success, such as cost savings, efficiency improvements, customer satisfaction, or revenue growth.
3. Understanding Market Dynamics:
4. Use AI to analyse customer needs, preferences, and trends.
5. Evaluate the competitive landscape to identify market gaps where AI can offer unique advantages.

Creating New AI Solutions and Products

• Engage in rapid 3-month prototyping cycles to accelerate development.
• Utilise highly skilled experts (“Black Belt” project experts) to lead AI projects.
• Collaborate with customers to address real-world needs.
• Ensure compliance with regulations and standards.
• Innovate through quick iterations and specialised teams.

Roadmap Development

• Regular updates are essential to maintain relevance.
• Early adoption and regular assessments are key to meeting user expectations.
• A clear roadmap is critical; a “set it and forget it” mindset is no longer viable.

Transitioning to Generative AI

• Focus on collaborative efforts and a solid roadmap for successful transition.
• Leverage existing strengths and identify low-hanging fruit.
• Enhance customer experience through targeted strategies.

Talent Management – Skills and Roles

• Define the responsibilities and skills necessary for a Chief AI Officer (CAIO).
• Address hiring challenges by understanding how AI fits into the organizational structure.
• Ensure accountability in AI roles, with talent experts playing a significant role.
• Align the CAIO with the C-suite, reporting to the CEO and aligning with business objectives.
• AI advisory roles are becoming more common, not necessarily full-time at the executive committee level.