The event focused on the challenges and strategies for gaining adoption of AI within an organisation. Key points included:

• Team Structures and Cybersecurity: Current structures hinder AI initiatives; need hands-on, cost-effective approaches. Overcoming opposition by demonstrating security measures and presenting data protection plans.

• Data Quality and Championing AI: Emphasised the need for real, clean data to avoid skewed results and mistrust. Importance of senior-level support and achieving quick wins.

• Generalist vs. Specialist and Evaluation: Prefer larger language models over fine-tuning unless necessary. Discussed methods for testing and ongoing monitoring.

• Education and Consensus Tool: Need to educate the business on data differences and user awareness. AI models as consensus tools, not formulaic solutions.

• Security Threats and Operationalising AI: Addressing new threats like deepfakes and voice recognition fraud. Formalising AI use and focusing on reducing repetitive HR questions