In recent years, many in the business world have seen a rise in the use of artificial intelligence (AI), from chatbots to image recognition and financial fraud detection. Gartner has predicted that AI software will reach $62 billion in 2022 alone, an increase of 21.3% from 2021. And there are huge potentials for AI in the UK, with predictions that it could deliver a 22% boost to the UK economy by 2030. With such an increase in the use of AI, it was only a matter of time before the regulation was tightened (and rightly so) to ensure businesses and consumers remained protected. Recently, the UK Government shared a new rulebook for AI innovation to boost public trust in the technology.

From the adversity of almost two years of pedal-to-the-metal crisis-response, rose immense investment in business transformation and technologies across all industries. After such rapid transformation, enterprise leaders might be forgiven for wanting to take a pit stop. But this is no time to slow down. With soaring employee expectations, and competition to digitally innovate, transformation in 2022 will continue apace. Trend 1 – Enterprise technology will be forced to'level-up' and meet consumer tech standards Increasingly, workplace technology seems to be playing a losing game of catchup with the consumer devices and apps we use in our everyday lives.

However, it's only really in the last year that we have really seen digital ethics hit the mainstream, with organisations in the private and public sector focusing their attention and, increasingly, resources, on these matters. So, what's caused this shift? Many organisations underwent an overnight transformation during the pandemic to survive and at the heart of this was the accelerated adoption of more advanced technologies such as automation and artificial intelligence (AI). Organisations are now taking a more serious look at what being data-driven means for them, developing data strategies that could shift entire business models. Without integrating digital ethics into this acceleration, the ethical risks proliferate.

Gartner predicts that "by 2022, 70 percent of white-collar workers will interact with conversational platforms on a daily basis." As a result, the research group found that more organizations are investing in chatbot development and deployment. IBM Business Partners like Sopra Steria are making chatbot and virtual assistant technology available to businesses. Sopra Steria, a European leader in digital transformation, has developed an intelligent virtual assistant for organizations across several industries who want to use an AI conversational interface to answer recurrent customer service questions. In developing our solution, we at Sopra Steria were looking for AI technology that was easy to configure and could support multiple languages and complex dialogs.

At Sopra Steria, we believe Artificial Intelligence is a key discipline for the digital transformations our clients implement. To offer you smarter applications! To create more conversational interfaces. To be an innovation connector.

Over 1,000 attendees, 50 speakers and 30 exhibitors; this is a brief summary of what I was lucky enough to take part in during the first AI Europe 2016 conference held in London on the 5 and 6 December. The attendee list boasted the biggest names from the world of artificial intelligence such as Microsoft, Dell, Uber, Samsung and Nvidia, as well as several innovative start-ups, the likes of Blippar and DreamQuark whose innovations are based on machine or deep learning models. Even if we can say with a degree of certainty that further advances in artificial intelligence are yet to come, leading players are in agreement that most AI techniques and technologies are now well-advanced. Therefore, their major preoccupation today is more about the quality of the data sets being used to train and validate their machine and deep learning models. Whether it's Dell or Uber, Microsoft or Blippar, they all have one thing in common: they all agree on the fact that as of now, the quality of the data used in AI for machine learning is of the utmost importance.

Artificial Intelligence is a technology that uses human-like learning to perform tasks. The idea of Artificial Intelligence or AI is nothing new. As a concept it has been in our literature and art for centuries. But these ideas had no foundation other than as philosophies of nature and science fiction. Connectionist paradigms of Artificial Intelligence have a somewhat more flexible approach than their rule-based cousins, but both have applications in modern technologies. Machine learning is based on artificial neural networks, which are a much-simplified version of how our brains work.