Erik Brynjolfsson is in great demand. The US professor whose research focuses on the relationship between digital tech and human productivity is nearing the end of a European speaking tour that's lasted nearly a month. Speaking via Zoom as he prepares for his imminent lecture in Oxford, the director of the Digital Economy Lab at the Stanford Institute for Human-Centered AI is enthused by recent "seminal breakthroughs" in the field. Brynjolfsson's tour – which has included appearances at the World Economic Forum in Davos and the Institute for the Future of Work in London – is neatly timed, because the recent arrival of ChatGPT on the scene has been capturing human minds, if not yet hearts. The large-scale language model, fed 300 billion words by developer OpenAI, caused a sensation with its powerful capabilities, attracting 1 million users within five days of its release in late November 2022.

From 2001: A Space Odyssey and Ex Machina to Wall-E and Her, artificial intelligence has reliably been a subject of fascination in modern culture. But AI is no longer a thing of imagination, books or film scripts – it is already playing a pivotal role in both our professional and personal lives. And when it comes to the capability of this next-generation technology, we are now on the precipice of an exponential leap. The potential impact of AI on our lives cannot be understated, so the growing AI skills gap must be addressed if we are to ensure that businesses are prepared to take this jump. AI has already transformed the way we interact with banks, how we shop and how we manufacture.

There is a worrying shortfall in skills required for a career in AI. Although technical capabilities are vital for a career in the sector, problem solving is considered the most critical soft skill needed for tech roles among all survey participants (up to 37%). However, around a quarter of tech recruiters (23%) have difficulty finding applicants with this aptitude along with shortfalls in critical and strategic thinking, according to IMB's report'Addressing the AI Skills Gap in Europe'. Also, nearly seven in 10 tech job seekers and tech employees believe that potential recruits lack the skills necessary for a career in AI. As AI moves into the mainstream, specialist tech staff are working more closely than ever with business managers.

There are few technologies in recent years more prolific than Artificial Intelligence (AI). From self-driving cars to robotic surgery to the applications we use every day, AI is all around us in both our personal and professional lives. Worldwide revenues for AI, including software, hardware, and services, are forecasted to grow 16.4 percent year over year in 2021 to $327.5 billion, according to IDC. With all major technological breakthroughs comes new challenges, and these need to be addressed before AI can deliver on its full potential. To better understand the barriers to AI adoption, a new O'Reilly survey seeks to explore what those challenges are and how organizations can overcome them.

We need to keep the essence of human-centric AI. This is at least how we see things in the EU. We don't want a form of AI that will replace everything - we want AI that will complement what we do, and to leave more space for us to be creative and have a better quality of life. One individual who is already seeing that creativity first-hand is Frank Salzgeber, head of innovation at the European Space Agency's (ESA) venture office. His organisation supports 220 new start-ups a year.

Organizations with an interdisciplinary team have a "far higher ratio of success" when deploying AI projects, said Arun Chandrasekaran, distinguished VP analyst at Gartner, speaking at a Gartner IT Symposium/Xpo Americas session last week. Interdisciplinary teams that blend roles across business and data science have a higher ratio of success with AI projects, as well as a faster time to production. This trend "clearly tells us that AI needs to be a team sport, said Chandrasekaran. "However, in reality what we see in most organizations is data scientists wearing too many hats, because there's a dearth of skills across other areas," he said. Organizations with an interdisciplinary team have a "far higher ratio of success" when deploying AI projects, said Arun Chandrasekaran, distinguished VP analyst at Gartner, speaking at a Gartner IT Symposium/Xpo Americas session last week. Interdisciplinary teams that blend roles across business and data science have a higher ratio of success with AI projects, as well as a faster time to production. This trend "clearly tells us that AI needs to be a team sport, said Chandrasekaran.

The robots are coming – for jobs. This is the plain, cold, hard fact we now face as we head towards the third decade of the 21st Century. The technology-driven world in which we now live is one filled with promise – cars that drive themselves, algorithms that respond to customer service inquiries, automated business intelligence on tap. Yet, this brave new world is also filled with challenges. For even as AI and automation increase productivity and improve our lives, their widespread adoption means that many work activities humans currently perform will soon be displaced – if they haven't been already. What this doesn't mean, however, is that there will be a shortage of jobs in the future.

Every business looking to introduce artificial intelligence (AI) into their operations will, at some stage, have debated whether to'build or buy' their AI capabilities. It's a common cause of headaches for those companies that are excited and aware of the value that AI and machine learning (ML) could offer, but don't know the best way of making this success a reality. The AI skills gap has been increasingly documented in recent months as awareness and expectations of the technology continue to grow. In fact, 93% of US and UK organizations consider AI to be a business priority, but more than half of them do not have the required in-house talent to execute their strategy. As a relatively new discipline, attracting and retaining employees who are able to successfully drive business results via AI is undoubtedly something of a challenge.

Most early adopters face AI skill gaps and are looking for expertise to boost their capabilities. According to Deloitte's global study of AI early adopters, 68 percent report a moderate-to-extreme AI skills gap.1 What are the "most wanted" roles to fill these gaps? According to AI early adopters, the top four most-needed positions are "AI builders" who are involved in creating AI solutions: Beyond these AI builders, adopters are seeking "AI translators" who bridge the divide between the business and technical staff--both at the front and back end of building AI solutions: When we compare companies with relatively little AI experience (they've built five or fewer production systems) with those possessing extensive AI experience (they've built 20 or more production systems), we observe an interesting shift in "most wanted" roles (see chart). Early on, AI researchers are the most sought-after, with about a third of the less-experienced rating them a top-two needed role. Business leaders rank near the bottom.

There are other reminders that while AI may not necessarily put all of us out of our jobs, it will definitely change many jobs. Consider this new prediction from Gartner: 80 percent of project management tasks that would typically be handled by a person today will be eliminated by AI by 2030. This will span traditional PM functions such as data collection, tracking, and reporting, Gartner predicts. One irony of the concerns – included the well-placed concerns – about AI replacing work that once required humans: Companies need humans to get their AI initiatives going and ensure their long-term success. Nearly one in three (31 percent) of respondents in a Deloitte survey listed a "lack of AI/cognitive skills" as a top-three concern for deploying AI. That means, of course, the other two-thirds aren't listing a skills shortage as a top concern, which suggests IT leaders are more worried about the long-haul in this regard.