Dr. Saskia Meier-Andrae, Stefan Bär, Daniel Gebler, Keno Dreßel
Rethinking Customer Experience in the Age of AI
#1about 1 minute
Why companies now compete on AI-driven customer experience
Companies are shifting their competitive focus from price and product to delivering superior customer experiences powered by AI.
#2about 2 minutes
How eBay uses AI to simplify the seller experience
eBay's AI-powered tool simplifies the product listing process by auto-populating details from a photo, saving sellers time and improving listing quality.
#3about 2 minutes
Addressing common client concerns about AI adoption
Many companies are eager to adopt AI for customer experience, but a primary technical concern is how to prevent hallucinations in chatbots.
#4about 2 minutes
Innovating logistics and returns with AI at Picnic
Picnic uses AI to innovate its business model by optimizing its supply chain and offering a reverse logistics service for returning items from other retailers.
#5about 4 minutes
Integrating AI expertise into product and business teams
Instead of creating siloed AI labs, companies are embedding AI specialists into cross-functional teams to ensure innovations solve real customer problems.
#6about 2 minutes
Hiring analytical generalists for the age of AI
Companies are now prioritizing hiring critical and analytical thinkers over deep domain experts, as these generalist skills are more effective for applying AI.
#7about 4 minutes
Navigating the practical impact of the EU AI Act
The EU AI Act has minimal direct impact on companies applying AI, leading to a call for collaborative and agile regulation that fosters trust and innovation.
#8about 3 minutes
Creating personalized customer journeys with AI
AI enables deep personalization, from suggesting weekly meal plans based on health goals to allowing natural language search for products with specific attributes.
#9about 2 minutes
The promise and pitfalls of implementing agentic AI
While agentic AI can automate entire processes like customer service and logistics, a key challenge is preventing performance from flattening without robust feedback mechanisms.
#10about 4 minutes
Learning from common failures in AI projects
Successful AI implementation requires overcoming challenges like poor data quality, building a culture that accepts failure, and understanding unexpected user behavior.
#11about 3 minutes
A rapid-fire look at AI tools and buzzwords
Panelists share their favorite AI tools and identify overhyped industry buzzwords like "omnichannel" and "hyper-personalization."
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