The event discussed the need to demonstrate ROI for AI, testing datasets, and safeguarding AI chatbots with contextual guardrails. Key points included:

• Top Issues and AI Pilot: Identifying top issues to address with AI and running pilot projects to fix core system issues. Emphasised the importance of data privacy and the need for AI in cloud exit strategies.

• Decentralised AI and Microsoft GitHub: Highlighted the need for domain experts and the risks of centralising AI, which can lead to loss of context and verification challenges. Mentioned the use of AI in every product and the role of entry-level developers.

• AI's Impact on NZ Companies and AI as a Search Tool: Discussed whether AI can transform normal NZ companies or if it will only impact large enterprises. Debated the effectiveness of AI as a search tool for knowledge bases.

• Hype vs. Reality and Testing Datasets: Acknowledged the hype around AI, its interest, and the need to sell the hype to secure investment, despite some scepticism. The importance of testing datasets and implementing contextual guardrails for AI chatbots was discussed.

• Smart Intern Analogy and General Adoption Challenges: AI was compared to a smart intern who is not always right, highlighting the need for human oversight. The event also touched on general challenges in adopting AI, such as the need for critical thinking, security awareness training, and addressing social engineering threats.