The AI optimism gap highlights that while we may be optimistic for AI’s potential, there is still a long way to go before we can be truly confident in its implementation; we know it exists, but we should be asking ourselves “what can it do for me now?” instead of wondering what it might be able to do for us in the future. AI shouldn’t have a ‘one size fits all’ approach. Whether you’re implementing it for automation, personalization or efficiency, you should be considering your organization’s core values, objectives and priorities. As we move from proof- of-concept through to production, it’s important to adopt a pragmatic approach to create a sustainable AI roadmap. This session will consider: 

• Assessing whether your data infrastructure is mature enough to handle AI implementation 
• A comparison of the value between implementing AI on an operational, customer-facing or enterprise level 
• Determining whether AI implementation is the right move for your organization 
• Demonstrating ROI of AI through Data & Analytics