Deepak Paramanand

AI investment is accelerating but proving a tangible near-term business value remains a challenge. This panel brings together enterprise AI leaders to unpack how to garner continuous internal buying, collaborate across non-technical functions, and position AI as a core business enabler - not just a technical experiment.

• Defining and measuring the real impact of AI investments: cost, productivity, revenue, and beyond
• Securing executive support and funding for AI products in competitive prioritisation environments
• Communicating value to non-technical stakeholders and navigating organisational AI illiteracy
• Embedding AI thinking across product, operations, and business strategy
• Evolving your role from technical lead to enterprise AI change agent

As AI models grow more powerful and compute-intensive, blockchain technologies are emerging as tools to help manage trust, transparency, and decentralised access to compute resources. This session explores how the convergence of AI, blockchain, and compute is set to reshape infrastructure strategies.

• Using blockchain to verify AI model provenance, usage, and audit trails
• Decentralised compute networks: unlocking distributed, low-cost GPU resources
• Tokenized incentives for data sharing, model training, and resource contribution
• Challenges in integrating blockchain with AI pipelines: latency, scale, and governance
• Emerging architectures enabling secure, transparent, and decentralized AI execution