13:30 Welcome and introduction
Ann Guinée, Communication Manager, Beltug (English)
13:40 Approaches for Machine Learning in Human Resources and Financial Management
Many common tasks in human resources and financial management may be improved by machine learning (ML), through increased accuracy and reduced completion time for example. However, the effort to build and maintain such ML solutions is high. In this presentation, you will learn approaches and considerations for using 'off-shelf' ML solutions provided by application vendors.
Eileen Smyth, Chief Trust Officer, Workday (English)
14:10 User story: Roadmap to Personalising 1-to-1 with Machine Learning
Roularta Media Group works on a platform that provides customers with personalised content: algorithms work on customer preferences and behaviour, to classify the customers. Then content of the different brands is scored on the potential to attract traffic, to engage the readers, and finally to convert them to a subscription. Let's discover Roularta's roadmap for Machine Learning, and the smart personalised apps and sites they develop, that will offer visitors tailor-made content.
Yves Wittouck, PO Data Analytics, Roularta (English)
14:40 Q&A: Your questions, your experience
14:55 Short break
15:10 User story: I search, therefore I find - A look at UZA’s smart internal search function, with machine learning as the driving force.
Online users know what they are looking for, and they want to find it as soon as possible. That’s where a smart internal search function comes into play. Research shows that visitors who use the internal search function view more pages, stay on the website longer and return more often. So how did UZA optimize its internal search function into an intelligent digital assistant? What role did machine learning play? And what do the data from the on-site search teach us? A retrospective and preview of the internal SEO strategy of the UZA.
Caitlin Stabel, Digital communications officer, UZA (Dutch)
15:40 The good, the bad and the ugly: What are the drivers for success in AI?
Despite increased interest in and adoption of artificial intelligence (AI) for the enterprise, research shows that 85% of AI projects ultimately fail to deliver on their intended promises to business. In this session, you will discover the good, the bad and the ugly when it comes to errors in current AI projects. You will see how people and processes, as well as data and technology, are successful drivers for AI implementations. And you will gain a transparent view on the future AI innovations.
Mieke De Ketelaere, Program Director AI, imec (English)
16:10 Q&A: Your questions, your experience
16:30 Wrap up & End
We will keep the session open after the end to enable those who wish to continue the discussions.