Turning AI Aspirations into Real Business Value

Speakers:
- Tim Baker, Managing Director, Financial Services Practice Lead, Expero
- Chris Lacava, Chief Product Officer, Expero
- Adam Wheat, Enterprise Group CTO, Morningstar
- Graham Ganssle, Head of Machine Learning: Customer Service, Wayfair
- Michael Young, Chief Technology Officer, Reuters at Thomson Reuters

While we’ll have a bias towards financial services, this webinar aims to delve into the challenges and opportunities presented by the generative ai revolution.  Overcome the fear of missing out - either by getting comfortable with waiting for the dust to settle, or jumping in with a well timed and designed project that delivers results fast.  

In this webinar our experienced panel will recount where they saw the opportunity, how they overcame the shortcomings in the technology, addressed concerns around compliance, and delivered solutions that saved money, created new products, and transformed customer service. The panel includes speakers from Reuters, Wayfair, Morningstar and Expero. 

The focus of this webinar is to provide tangible tools for safely and confidently adopting AI and LLM technology.  Some of the key topics to be covered are: What is the impact of waiting to get into the AI game? What industries and use cases are best for AI and LLM? How could LLM 'Hallucinations’ impact your revenue? What is data ‘leakage’ and how can I avoid it? Can’t my current technology vendors do these functions today? How to integrate existing technology like Graph DB and Graph Machine Learning, Geospatial, TimeSeries, & Visualization into the equation and other topics.  

This event is designed in a 'Speed Dating' format with usual tips and usable strategies for business and technical roles.

What You'll Learn:

Exploring Today’s AI Landscape

• A comprehensive walkthrough of existing AI capabilities and tools tailored for financial institutions.
• A discussion of the real-world applications and use cases illustrating the transformative impact of AI in financial services.
• Where do people fit into this new model and what ROI and type of value propositions can it offer.
  

The Rise of Large Language Models (LLMs)

• How LLMs are redefining human-data interaction, facilitating efficient, intuitive data exploration.
• What are the implications for how firms manage their enterprise data?
• The pros and cons of developing in-house LLMs versus leveraging third-party solutions.
  

Navigating the Pitfalls

• From hallucinations to data leakage, we will explore the inherent issues associated with AI integration.
• Learn mitigation tactics to address and preempt these challenges, ensuring robust, secure AI deployment.
  

Foundations for Success

• What are the key elements and dependencies that underpin a successful AI implementation.
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