VR and AR to enter the workplace
Pete Hanlon, CTO at Moneypenny, says immersive technology in training will be at the forefront of many businesses’ agenda in 2020.
“While VR solutions like the Oculus Quest are still, for many, a novelty and AR solutions like Microsoft’s HoloLens 2 haven’t made it to the consumer market, we will see increased adoption of these technologies in a business setting to train employees. VR is already being used to help people get over the fear of presenting in front of large crowds by allowing people to present to a virtual audience. AR is being used in medicine and high-end engineering to train employees how to perform complex tasks by walking people through complex procedures. This level of expert system and training is a sweet spot for VR and AR, hopefully this will improve the technologies further as they become more mainstream over the coming years.”
APIs and partnerships
Will Hurst, head of commercial development at Monevo, says the explosion of partnerships across the financial sector in 2019 will continue unabated in 2020.
“Where the ever-growing and ever-popular challenger banks lead, the incumbents will soon follow. I fully expect the old guard to adopt this approach to give opportunity to provide more positive interactions through products they don’t provide… helping customers to access products that the banks can help oversee.”
Transparency and choosing your own salary
Charles Towers-Clark, chairman of international IoT provider Pod Group, says the trend of transparency in salaries will come to the fore.
“Over this past year, more and more companies have been becoming far more transparent in their operations, even when it comes to transparency in salaries. This trend will continue throughout 2020 and beyond, especially as employees look for the more human elements of businesses, with the most engaging companies attracting the best talent. I think we can even expect to see a small number of companies allowing employees to choose their own salaries.”
Innovation in schools
Michael Oakes, change strategy manager at RM Education, says the growing digital literacy of staff will put pressure on schools to innovate.
“As the next generation of teachers enter the workforce, schools are now encountering young professionals that are digital natives. From sufficient internet speeds to classroom technology and cloud management, these teachers are now putting pressure on schools to innovate more quickly and clearly. And the schools that are doing digital effectively are proving far more desirable places to work for younger teachers. In turn, this is helping make schools more educated consumers when it comes to technology solutions. Whether they want smarter ways of working, cloud technology or the ability for teachers and students to access resources remotely, these digital natives have a much better idea of the changes they’d like to see happen in school, and how to help make that happen.”
Public scrutiny of artificial intelligence
Teg Dosanjh, director of connected living for Samsung UK and Ireland, says we’re going to see increased public demand for the demystification and democratisation of AI.
“There is a growing level of interest and people are quite rightly not happy to sit back and accept that a robot or programme makes the decisions it does ‘because it does’ or that it’s simply too complicated. They want to understand how varying AI works in principle, they want to have more of a role in determining how AI should engage in their lives so that they don’t feel powerless in the face of this new technology. Companies need to be ready for this shift, and to welcome it. Increasing public understanding of AI, and actively seeking to hear people’s hopes and concerns is the only way forward to ensure that the role of AI is both seen as a force for good for everyone in our society and as a result able to realise the opportunity ahead – historically not something that tech industry as a whole have been good at, we need to change.”
The rise of ‘AI workers’
James Dening, VP Europe at Automation Anywhere, says robotic process automation will be adopted more widely in 2020.
“Until now, RPA and artificial intelligence have been perceived as two separate things: RPA being task oriented, without intelligence built in. However AI and machine learning will become an intrinsic part of RPA – infused throughout analytics, process mining and discovery. There will be greater adoption of RPA across industries to increase productivity and lower operating costs [and] across all job roles, from developers and business analysts, to programme and project managers, and across all verticals, including IT, BPO, HR, education, insurance and banking. Consequently, training in all business functions will need to evolve, so that employees know how to use automation processes and understand how to leverage RPA, to focus on the more creative aspects of their job.”
AI in medical imaging and diagnostics will explode
Asheesh Mehra, co-founder and CEO of AntWorks, says the healthcare system will increasingly turn to intelligent automation.
“Utilising AI and intelligent automation to process patient data could mean that patient only has to wait two days to see the doctor rather than two weeks, as intelligent automation that is built on fractal science can deal with unstructured data like paperwork, emails and patient forms, much more effectively than other forms of automation. This all means that doctors will no longer have to deal with admin work, which currently take up as much as half of doctors’ time. All this time can be reused by doctors in seeing more patients and focusing on care, and we will see the benefits that this tech will reap on medicine within the next decade. AI will enable better imaging for doctors too, which means faster and more effective diagnosis and decreasing mortality rates across the globe.”
More analysis of language and social media data
Tim Tully, CTO at Splunk, expects natural language processing to come to the fore next year.
“NLP is going beyond smart assistants. At the business level, NLP combined with AI will increasingly make decisions that may be inscrutable to human observers, whether by analysing stock data to make investment decisions, or translating mountains of unstructured social media for broad sentiment analysis around a brand, or specific intelligence on who to target for which product pitch. But, training is everything. A lot of these algorithms are being trained on existing human practices that are inherently biased and problematic. It’d be naive to assume we can eliminate that from NLP algorithms at the outset.”