The organisation of tomorrow will be built around data, and it will require artificial intelligence to make sense of all that data. Artificial intelligence is a broad discipline with the objective to develop intelligent machines. AI consists of several subfields: Machine learning (ML), a subset of AI that enables machines to learn from data. Reinforcement learning, which is a subset of ML and focuses on artificial agents that use trial and error to improve itself. And deep learning, also a subset of ML that aims to mimic the human brain to detect patterns in large datasets and benefit from those patterns.

Data is being collected, analysed and utilised everywhere. Artificial intelligence algorithms process data to produce automated decisions, recommendations and services. New artificial intelligence applications are springing up at an accelerating pace. "Our positive expectations regarding the data economy won't come true if citizens and consumers do not trust that artificial intelligence is used to drive human wellbeing," Haataja says. In the future, the competitiveness of companies and countries will depend to a great extent on their ability to utilise data and artificial intelligence.

It's December and was there something else? Right: not Santa is in front of the house but the chapter of coding leipzig. This time we are guests at Saxonia Systems and we prepare a bunch of talks. As always, we'll prepare something. But this should not stop you from submitting your own ideas and talks. So if you have a topic you want to talk about, let us know. And best of all: you've got the chance to introduce yourself to the people and present your topic.

Is my organisation a member? The Whitehall & Industry Group's AI Collaboration Forum will bring together a wide audience from our 230 members, spanning the private, public and not-for-profit sectors, as well as academic institutions. Supported by the Office for Artificial Intelligence and kindly hosted by EY. The agenda will explore the vital role of cross-sector collaboration to ensure the endless possibilities of AI are harnessed and regulated effectively, generating maximum positive economic and societal impacts for the UK. Holding a BSc in Computer Science and an MBA from the Massachusetts Institute of Technology, Sana Khareghani has over 20 years' experience in technology and business across the private and public sectors.

IMAGE: Robert Gramling is the Holly and Bob Miller Chair in Palliative Medicine at the University of Vermont Larner College of Medicine. In a new paper, Gramling and his colleagues show... view more Some of the most important, and difficult, conversations in healthcare are the ones that happen amid serious and life-threatening illnesses. Discussions of the treatment options and prognoses in these settings are a delicate balance for doctors and nurses who are dealing with people at their most vulnerable point and may not fully understand what the future holds. Now researchers at the University of Vermont's Vermont Conversation Lab have used machine learning and natural language processing to better understand what those conversations look like, which could eventually help healthcare providers improve their end-of-life communication. "We want to understand this complex thing called a conversation," says Robert Gramling, director of the lab in UVM's Larner College of Medicine who led the study, published December 9 in the journal Patient Education and Counselling.

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Countless tech platforms are setting out to help call centers automate conversations with their customers. But U.S-Indian startup and Y Combinator alum Observe.ai is bucking that trend by using AI to help coach human call center workers, rather than replace them. Today the company announced it has raised $26 million in a series A round of funding to further this mission. It then automatically transcribes each call and carries out sentiment analysis to determine customer satisfaction while drawing correlations between the words and actions of the support agent and the happiness of the customer. Top-performing agents can be used as benchmarks to determine what works, which can then help train new or under-performing support staff.

Whether we like it or not, driverless cars seem to be on their way. It might still be many years until the technology is ubiquitous on our roads, but when automated vehicles (AVs) do arrive, they're going to shake things up in a huge way. One of the biggest benefits AVs are expected to bring is improvements to road safety. Human error is the biggest cause of road trauma -- remove human drivers from the equation and the number of those injured or killed on our roads should decrease significantly. As vulnerable road users, cyclists can rightly feel a sense of excitement at the prospect of driverless vehicles.

At a height of 100m up the amazing A'DAM Tower in central Amsterdam, the altitude wasn't a problem at Global Transformation Summit (GTS) but keeping up with the many shared experiences and fast exchange of ideas was! GTS Amsterdam brought together global brands, connecting international business leaders and senior marketing and localization professionals. What was the common ground? Many insights shared and new contacts made. As content types and volumes continue to increase – the growth of content on the internet doubles every 18 months – brands need to converge content, collaborate internally, and ensure the customer experience is consistent and personal, to stand out from online competition. This means re-imagining how we work – looking to define how multilingual content performs beyond traditional KPIs.

Having spent 20 years in the banking tech industry across 50 countries, Aditya Bhagat and Surya Prasad realised that there is a major gap in the customer expectations, and the offerings from financial institutions. They also realised that artificial intelligence (AI) has the potential to bridge this gap but, the implementation of the AI layer in banking requires deep domain and banking technology expertise. Therefore, the duo decided to leverage their experience to build functional AI products to ease AI deployment and enhance the customer experience in the shortest time. Founded in 2017, BankBuddy's platform combines bots, workflow automation, computer vision, big data, and natural language interactions to help financial institutions with customer experience management, hyper-personalisation, and operations automation. Aditya believes that with rapid disruption in the financial services space from fintechs and big tech companies, and expected changes in the business models from open banking, the survival of financial services companies will hinge on the low cost of customer acquisition, excellent proactive service, and continuous cross-sell, upsell, and retention. The company, though based in Dubai, provides service to about 11 countries including India.