27 June 2018
AI in the Enterprise: Chair’s Welcome
Executive Director – Head of Quantitative Research and Advanced Analytics
09:15AM - Day 1
Keynote: AI powering digital transformation
- Is your organisation ready for AI and digital transformation?
- Why should you embrace AI?
- Challenges faced by Enterprises using new deep learning and ML technologies
- Humans and AI working together – creating an AI culture and developing trust within the organisation
Frameworks for data driven business decisions
- How will machine intelligence impact business?
- Challenges and opportunities for investing in AI
- The benefits of adopting Business Intelligence analysis to support both strategic and tactical decision-making processes
Keynote Panel: Building an AI Strategy for Enterprise
Director Product, Search and Machine Learning
10:30AM - Day 1
- How are large companies deploying AI and machine learning?
- How will AI redefine management strategies & make your business smarter
- The latest updates and use cases in enterprise workflows
- Selection & appointment of your tech platform
- Measuring ROI and scaling AI projects
How to build a team and get business value out of AI
Chief Data Officer
10:10AM - Day 1
11:45AM - Day 1
From real experience as the CDO at Southern Water and previously Head of Data at The Pensions Regulator Peter will explore the essential elements in building the right team to deliver business value from AI.
Case Study: The role of AI in the workplace
- Discussing the role of AI in the present and future workplace for tasks such as recruitment, talent development and HR operations
- What will the impact of a AI based workforce be on the future of the human workforce?
- Examples of using chatbots and other AI technologies within the modern workplace to improve processes from across Enterprise
Panel : The Cognitive Enterprise
Director Retail Credits Service Center
12:45PM - Day 1
- Is your business ready to be transformed by cognitive automation (CA) and robotic process automation (RPA)?
- Which processes are most suitable for CA / RPA?
- What business benefits are being delivered? What are the challenges?
- Timescales for adoption, investment, scaling automation projects
- Examples and best practices from Insurance, banking, healthcare and manufacturing
Afternoon Keynote: AI for Everyone
- What are the barriers to entry for companies wanting to use AI within their businesses
- How important is transparency of data and ML scoring for enterprises wanting to start using AI?
- Discussing the current lack of people/expertise available to create AI systems and the impact this will have on creating AI for everyone
Data Products in the Newsroom
Director of Data
03:00PM - Day 1
Today’s newspaper publishers face challenges that would never even have occurred to their predecessors. In today’s world of online publishing, editors must constantly monitor the traffic on their newspaper sites and make quick decisions about the content of these publications.
Growing awareness of machine learning means that there is an increasing curiosity within newsrooms about what it can offer, and advances in technology mean there is an increasing ability for data and technology teams to create novel solutions to the challenges facing journalists and editors. However, despite an increasing abundance of available tools, and data about audiences and content, building data products that can genuinely improve the workflows in a newsroom is challenging.
The Data Technology team in News UK develops data platforms, machine learning systems and products. We work within our newsrooms to empower journalists and editors with access to data products that are carefully tuned to their needs. Dan will be discussing where we are on the journey, from the algorithms being developed to help aide decision making through the lifecycle of an article, to the modern APIs and front end frameworks being developed to provide access to the results of these algorithms.
The Curious Case of Deep Learning: Unlocking the insights from theory to practice
Dr. Utku Pamuksuz
Sr. Data Scientist and Clinical Professor/Lecturer of Data Analytics
W.W. Grainger and University of Illinois Urbana-Champaign.
03:30PM - Day 1
Necessity of wide spectrum of skills to deploy the complete deep learning solutions for four different business problems ( finance, marketing, insurance and Strategy )
Machine Learning – Privacy, security threats and the implications
- Identify the potential implications of AI cyber threats
- Infrastructure and processes for successfully defending again cyber threats
- How to adopt data science to combat fraud
Panel: AI for Social Good
- How is AI being successfully applied to challenge problems
- What are the potential uses of AI across various sectors that are essential for social good
- AI’s impact across Urban Computing, Health, Environmental Sustainability and Public Welfare