Part 2: Why AI Takes Internal Disruption First

Part 2: Why AI Takes Internal Disruption First

AI at scale is impossible without system design in place complemented by a fundamental assessment of any associated business processes. Some call it digital transformation but that aged terminology establishes past practices and ties us to the way we’ve always done technology and doesn’t truly set the “enterprise” up for future success. Learn why AI takes internal disruption first and hear examples from the aviation industry. 

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Part 3: A Framework For AI in the Enterprise

Through 2021, 75% of AI projects will remain at the prototype level as AI experts and organizational functions cannot engage in a productive dialogue. With all the investment, interest and funding, are we overpromising and underdelivering? This panel explores the potential of entering another AI winter and offers a framework for AI in the enterprise. 

Part 4: AI Use Cases at Scale

AI promises to be one of the most disruptive and innovative classes of technologies during the next 10 years. Yet, to maximize value delivery you must dig into a rich goldmine of real-world AI experience to prioritize value cases and find sources of transformative business value.  

Part 5: Ethics in AI & Customer Experience

Artificial Intelligence has potential risks companies in some cases are not ready to manage. An Ethics framework can help companies develop a more trust-based relationship with their consumers and society-at-large.

Part 6: The Future of AI

The most powerful manifestations of Artificial Intelligence occurs when an organization is given the ability to see their world through the lens of an AI. Now spatial models enable organizations to remotely observe, analyze and learn from their physical environments in ways that have never been possible before.