Enterprise AI

Chairpersons welcome and opening remarks. 

To follow soon …

Edge AI is the front runner for manufacturing and process driven industries, but why? This session will cover how Edge AI: 

• Enables processing algorithms locally for a quick response time.  
• Allows for ROI to be easily tracked due to the solution being located at the central shop floor phase.   
• Examples of Edge AI being used across industries for automated decisions and optimised response rates.  

As the adoption and implementation of AI continues to grow rapidly, so does the importance of ensuring responsible practices are in place to limit potential problems. This session will look at the steps we can take to help with emphasis on fairness, privacy and security of information.

• Sophisticated decision making through AI, how to eliminate the bias. 
• Learning from past mistakes – discussing the different approaches and concerns industries need to consider when tackling issues like privacy, surveillance and discrimination.  
• The role of responsible AI in aiding the ethical AI journey. 
• The need for governance and regulation as industry standards – where we are vs where we need to be and the laws around AI. 

• Protecting data from cyber hacks through AI-based security solutions. 
• The potential to scan malware in real-time. 
• The ability to react autonomously to everchanging threats.

A look at how AI is being used within the fraud prevention and identity theft spaces.   

• Using AI and ML to gain real-time intelligence, in turn creating a strong competitive advantage.  
• Creating a holistic technology approach to your digital transformation strategy.  
• What new services are expected to appear in this space?  

• AI and data analytics powering the digital bank revolution. 
• Personalization and other new services available to digitally enabled banks through AI. 
• Utilising conversational AI for remote interactions.  

• Creating a holistic strategy that includes AI, BI, ML and other disruptive technology processes and capabilities.  
• A shift towards simplifying the vendor landscape to limit the overlap here – focusing on gaps in the market and MVP (minimum value products).  
• Building partnerships across solutions and sectors as the key to an optimised eco-system.  

• Harnessing multi-sensor ML – where to start in building this data rich infrastructure.  
• Solving big problems with operational AI. 
• Working with unbiased ML and transparent AI for true insights. 

• An overview of multimodal learning.  
• The advantages of multi-sensory input.  
• Will this type of machine learning help to reduce bias within decision making? 

• Human-centred AI for the optimum patient experience. 
• AI enhancing the human expertise, not replacing it.  
• Private and sensitive data – how it is handled and processed is more important than ever.  
• Adopting AI quickly into existing processes, think automating routine tasks. 

View day 2 content here:

• Optimised Data & Analytics
• Transformational AI
• Human-centred Approaches to DTX