What learning trends are in store for 2023? The coming year will bear witness to some significant changes across the entire business world. Recession poses an ever-constant threat so it's important that businesses equip themselves for the future. On top of it all, businesses are having trouble finding new recruits due to a labor shortage. So 2023 will force businesses to strengthen their current ranks to protect against a shallow recruitment pool.

AI can improve or worsen job quality. What constitutes a quality job? If you were to ask family and friends, they would probably say good pay, benefits, and stable working conditions, but for many workers, workplace technologies, especially AI, are affecting job quality. That's important because the U.S. has a serious job quality problem. The number one ESG challenge companies are grappling with is the treatment of workers.

Artificial Intelligence (AI) and Machine Learning (ML), Cloud Computing, and 5G will be the most important technologies in 2022, according to a new study conducted by IEEE called'The Impact of Technology in 2022 and Beyond.' The report includes a survey of 350 CTOs, CIOs, and IT Directors, and other technology leaders at organizations with over 1,000 employees across multiple industry sectors, including banking and financial services, consumer goods, education, electronics, engineering, energy, government, healthcare, insurance, retail, technology, and telecommunications. Findings reveal the key technologies that will not only impact industries in 2022 but will dominate the next decade's digital transformation strategies. According to the IEEE study, technology leaders agree that Artificial Intelligence (AI) and Machine Learning (ML) will drive the majority of innovation across nearly every sector in the next 1 to 5 years. Other technologies driving innovation from 2022 onwards include Cloud Computing, 5G, Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (XR).

"Pop culture does a great job of scaring us that AI will take over the world," said Professor Daniela Rus, speaking at a virtual MIT event on Wednesday. But realistically, said Rus, who directs the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), robots aren't going to steal everyone's jobs overnight -- they're not yet good enough at tasks requiring high dexterity or generalized processing of different kinds of information. Still, automation has crept into some workplaces in recent years, a trend that's likely to continue. Throughout the daylong conference, the "AI and the Work of the Future Congress," which convened speakers from academia, industry, and government, one key theme consistently emerged: Task automation shouldn't be viewed as a replacement for human work, but a partner for it. With the exception of some middle-skilled manufacturing jobs, automation has generally improved human productivity, not eliminated the need for it.

The COVID-19 pandemic has elevated the role of technology in the workplace, and more employers are relying on artificial intelligence, machine learning and virtual reality to save money and limit in-person contact. These technologies can be effective tools for hiring, training and assessing employee performance, as well as creating meaningful interactions during a time of isolation. However, employers must ensure that their use of technology doesn't run afoul of employment and labor laws. "It's incredibly important for HR organizations and hiring managers to understand the nuances of the technology that they're using if it is making decisions on their behalf," said Marc Goldberg, chief technology officer at the Society for Human Resource Management (SHRM) in Alexandria, Va. He was speaking during a panel discussion at the American Bar Association's 14th Annual Labor and Employment Law Conference, which was held virtually.

Over the last several months, I've been focusing on the planning, execution and post-event activities for the recently concluded HR Technology Conference, which, by all accounts, was our largest and most successful event ever. It's only in the last week or two that I've had a chance to reflect on the conference--and on the year overall--thinking about the technologies and trends that have mattered the most in 2019 and speculating on what might dominate the conversations in 2020. Here's my semi-scientific look at what was important to the HR-tech community this year, and what we will probably spend more time on in 2020. AI in HR tech was probably the No. 1 tech topic and trend in 2019. There were about 500 exhibitors at HR Tech, and I bet easily over 100 of them are developing, deploying, or at least discussing, how AI is driving their technology offerings.

Today's Smart Connected Workplace is more about experiences and less about devices. Technology is acting as our digital concierge or a helpful assistant, providing information to us when we need it. According to Brandon Buckingham, Smart Connected director for Steelcase, this is a new workplace where technology enables better experiences that allow us to navigate place, time, resources and commitments seamlessly. At the same time, it offers the influencers of how space is used, planned for and acquired detailed information to inform their choices. And, as data is aggregated over time, it provides insights into key workplace issues like culture, innovation and engagement.

Artificial intelligence (AI) and analytics are helping to speed up the pace of digital workplace transformation in industries such as energy and utilities, financial services, manufacturing, and pharmaceuticals, according to a new report from Dimension Data. Reimagining business for the digital age is the number-one priority for many of today's top executives. We offer practical advice and examples of how to do it right. Gaining competitive advantage and improving business processes are among the top goals of digital transformation strategies, according to the report, "The Digital Workplace Report: Transforming Your Business," which is based on a survey of 850 organizations in 15 countries. While AI technology is still in its "infancy," it is sufficiently advanced to be working its way into companies in the form of virtual assistants, Dimension said.

Business adoption of artificial intelligence is accelerating, fueled by an explosion of data, the rapid growth in cloud computing and the emergence of advanced algorithms. In a survey of IT decision-makers that my company, CCS Insight, conducted in July 2017, 58 percent of respondents said they are using, testing or researching the use of artificial intelligence (AI) in their organizations. Respondents also estimated that as much as 30 percent of their business applications would be enhanced with machine learning within the next 24 months -- a bullish view, considering the technology's well-documented problems with trust, cost and the lack of skills needed to train machine learning systems. Speech-based and image-based cognitive applications are emerging at an accelerating rate for use in specific markets, such as fraud detection in finance, low-level contract analysis in the legal sector and personalization in retail. AI is also beginning to appear in systems designed for corporate functions such as customer service, HR, sales and IT.

In previous Neva blogs (Shift left: empowerment as-a-service and Shift left: empowerment as-a-service part 2 AI-driven automation), I discussed how AI-based automation accelerates the adoption and success of shift-left strategies. This post outlines the specific tasks associated with each level of IT support and discusses how AI-driven automation improves efficiencies for IT, enabling adoption of modern workplace technologies and delivery of superior service. A level 1 support agent's primary responsibility is triaging service desk tickets and providing basic support and troubleshooting. Level 1 typically relies on knowledge articles and standard fixes for common issues, such as password resets and application access. Level 1 agents must also collect information regarding the requester's location, issue type and other supporting documentation and manually enter it into incident records as part of ticket escalation processes.