Day 2 - 19 April 2018
AI and the consumer: Chair’s Welcome
Keynote Panel: ChatBots – the next generation of messaging apps
- Understanding the messaging platform of the future
- Creating personalized interaction between the consumer and a brand
- Measuring the success of your chatbot though engagement levels, sentiment analysis, response rates, bot mentions and click through rates
Keynote: The future of AI for customer experience
- Explore how AI is being used to accelerate customer-centric experience design
- Practical applications to leverage AI
- How big data and contextual computing is influencing the consumer
- A look at the next generation of consumer analytics
- Using computer vision and natural language processing to enhance customer experience
- How does GDPR effect things?
Dr. Frauke Neuser
Associate Director Scientific Communications
10:45AM - Day 1
Skin Care gets smart with AI
- Skin care is one of the most confusing and difficult categories to shop. At the same time, women are increasingly looking for personalized experiences and solutions – but department & specialty store beauty advisors can be intimidating.
- Olay Skin Advisor was designed to help women better understand their skin & skin needs, and to find the right products for them – whenever and wherever they want.
- Olay Skin Advisor is rooted in 25+ years of imaging expertise, and powered by Olay’s VizIDTM Technology. Its Deep Learning algorithm turns an uploaded selfie into a personalized skin analysis. With the help of a short questionnaire and a synaptic intelligence algorithm Olay Skin Advisor also provides personalized product recommendation.
- To date, over 3.5MM people globally have visited the platform.
Panel: Examining AI uses in Banking & Financial Services
- Explore current AI applications within the financial & banking sectors
- The advancement of Robo advisers into Robo trading
- Discussing the role of partnerships in the advancement of traditional banking into the future
- The future value of machine learning within the finance & banking sectors enabling fraud reduction
How AI can transform the discovery of drugs
- The major challenges in drug innovation
- The promise of big data
- How Sanofi is using AI to enhance innovation
Digital Health and AI Clinical Lead
Panel: AI transforming Healthcare
- How is AI changing the way that healthcare is delivered?
- Machine learning and big data – how to leverage new data sets to deliver personalised medicine
- Innovative ways machine learning and deep learning are being used to develop new drugs
- Challenges for the future
Global Chief Innovation Officer, FAST
AI and the Consumer
Mindshare have created an AI tool and way of working that lets users create code to programme their advertising systems, configuring millions of media-buying strategies and creative rules automatically. This will free up the human element to spend more time ‘upstream’ with the data, uncovering insights, turning these into strategic actions and providing the rules that can be re-coded through ANNA directly back into media and creative technology at the same time. Empowering advertising with AI methodology’s to communicate with consumers like never before.
AI sucks…no it rocks!
An exploration of the pros and cons of AI from a consumer perspective, drawing on exposure to future trends at SXSW, and experience in working with AI for clients, including AFC Bournemouth.
Panel: The Revolutionising of Customer Experiences through AI
- The impact of AI and understanding when AI is most effective as a tool for customer service
- Why smart tech are key to creating contextual experiences
- Using AI to predict consumers intentions
- Effective personalisation of communications to create positive impacts
- What’s the most effective way of engaging staff and help them work along-side AI?
- What are the cost implications both short and long-term?
Case study: Deliveroo
How Deliveroo are applying AI to their delivery networks to get food to your front door in less than 30 minutes.
The Clinical Impact of AI on Therapeutic Relationship in Healthcare
- Examination of the applications of narrow artificial intelligence and machine learning strategies in musculoskeletal medicine (radiology, clinical decision support systems, pattern recognition of causative trends of diagnosis).
- The natural transition to a virtual point of care for patients and the removal of necessary therapeutic context which may have risks for patient-clinician relationship.
- A clinician’s perspective on how healthcare leaders must facilitate staff engagement with digital transformation to optimise the wider application of AI technologies.