What will workplaces of the future look like? It’s one of the top ten questions global businesses are asking themselves according to Deloitte’s 2013 Human Capital Global trends report, Resetting Horizons. And for good reason: dealing with the here and now is critical, but prediction and adaptation are key to sustained success. And there’s something more: predicting the future is a favourite pastime, and our history is littered with fabulous ideas. Some, like talking on handheld devices, have turned out to be inspired. Others, like us living a life of leisure while robots do all the work, have turned out to be disappointingly fanciful. The challenge has always been about separating the insightful from the noise.

The US manufacturing industry continues to gain momentum. Job openings have been growing at double-digit rates since mid-2017 and are nearing the historical peak recorded in 2001. In this dynamic manufacturing environment, Deloitte and The Manufacturing Institute launched their fourth skills gap study, to re-evaluate their prior projections and move the conversation forward on today’s hiring environment and the future of manufacturing work. The results appear to highlight a widening gap between the jobs that need to be filled and the skilled talent pool capable of filling them. The search for skilled talent—ranked as the No. 1 driver of manufacturing competitiveness by global manufacturing executives —appears to be at a critical level. In fact, Deloitte and The Manufacturing Institute research reveals an unprecedented majority (89 percent) of executives agree there is a talent shortage in the US manufacturing sector, 5 percent higher than 2015 results. The talent shortage seems to be exacerbated by two factors. First, the US economy is currently in the midst of the second-longest expansion in history, and the manufacturing industry is part of this expansion. To support continued growth, based on our analysis, Deloitte expects the number of new jobs in manufacturing to accelerate and grow by 1.96 million workers by 2028 (see figure 1). Second, the manufacturing industry could face a demographic challenge. Despite the trend of delaying retirement—according to the most recent Gallup poll, the average age of retirement is now 66 years—more than 2.6 million baby boomers are expected to retire from manufacturing jobs over the next decade. And, more than half of the open jobs in 2028 (2.4 million) could remain unfilled because of the following top reasons identified by executives: Shifting skill sets due to the introduction of advanced technologies; Misperceptions of manufacturing jobs; Retirement of baby boomers.

Career technical education (CTE) programs at community colleges are increasingly seen as an attractive alternative to four-year colleges, yet little systematic evidence exists on the returns to specific certificates and degrees. We estimate returns to CTE programs using administrative data from the California Community College system linked to earnings records. We employ estimation approaches including individual fixed effects and individual-specific trends and find average returns to CTE certificate and degrees that range from 14 to 45 percent. The largest returns are for programs in the healthcare sector; estimated returns in non-health related programs range from 15 to 23 percent.

Buoyed by high commodity prices, low unemployment and relative stability in a turbulent global economy, Canada is at an inflection point. Whether by design or accident of history, Canadians today are for the most part prosperous and confident in their futures. Ipsos’ latest Global Economic Pulse survey found that 68% of Canadians view their economic situation in a positive light, the highest among G8 countries.1 The challenge is how to take full advantage of our current economic and political capital. What should decision makers do today to best position Canadian workplaces for success in 2025? Deloitte and the Human Resources Professionals Association (HRPA) have partnered to address this question by developing detailed scenarios depicting what Canadian society might look like in 2025. The goal of this exercise was not to lay out the definitive future of the Canadian workplace. Rather, it recognizes that despite our relatively enviable position, we must identify strategies that address the very real problems that continue to exist: the sustainability of our industries, the competitiveness of our firms, the quality of our employment, the inclusivity of our workplaces and our level of innovation.

If 2017 is anything like 2016, “disruption” is set to become the word of the year. In politics, business and society, recent events have highlighted the shortcomings of predictability and the urgency of expecting the unexpected. The same applies to the labour market. Warp speed developments in technology – automation, artificial intelligence and the arrival of the sharing economy – are transforming how we work. Beyond technology, traditional working patterns are also being disrupted by changes in society, organizations and workforce management, leading to the rise of a more independent and dispersed workforce. Flexibility is, indeed, the key to this new age, with around 30% of the US and European working population already free agents. The “job for life” no longer exists, while the “multi-career” is the norm.

Technological developments are changing the world and the way we work. Self-driving vehicles, 3D printers, and artificial intelligence are providing new business opportunities, raising concerns that jobs will be replaced with automated processes. However, mass-unemployment has not been realised in the medium to long-term. On the contrary, economic output and employment have risen substantially in developed countries, but is everything different this time? Will advances in technology create a jobless future? To estimate the effect of automation on jobs more accurately, economists from the University of Oxford calculated which and how many jobs in the US are at high risk of being replaced due to automation. Based on these calculations, Deloitte in Switzerland carried out a similar analysis for Switzerland. The results of this analysis is presented in more detail in this report.

Rapid urbanization is exerting growing pressure on cities’ traditional infrastructures, and information and communication technologies (ICTs) present very viable means of updating these infrastructures to reflect the demands of 21st century societies. This ITU-T Technology Watch Report analyses Seoul’s implementation of its “Smart Seoul 2015” project, providing a best-practice guide to the construction and operation of a smart city. The report investigates the conceptual underpinnings of Smart Seoul, the use of smart technologies and mobile-web applications to provide citizen-centric services, and the role of technical standards as the precondition for smart city functionality.

This year’s report accomplishes two objectives. First, it refreshes last year’s metrics. Second, it provides global context whenever possible. The former is critical to the Index’s mission — grounding the AI conversation means tracking volumetric and technical progress on an ongoing basis. But the latter is also essential. There is no AI story without global perspective. The 2017 report was heavily skewed towards North American activities. This reflected a limited number of global partnerships established by the project, not an intrinsic bias. This year, we begin to close the global gap. We recognize that there is a long journey ahead — one that involves further collaboration and outside participation — to make this report truly comprehensive.

Advancements in AI were recently spotlighted by AlphaGo, a computer program developed by Google’s DeepMind team. The program — which relies on decision-making algorithms and neural networks — defeated a human European champion at the board game Go in a feat previously believed to be years away. On the investor side, Jim Breyer of Breyer Capital has said AI will deliver massive returns for investors betting on applications for industries including healthcare and entertainment. With this in mind, we used CB Insights’ database to look at funding to artificial intelligence startups since 2010. Our artificial intelligence category covers startups primarily focused on developing AI, across areas including image processing, natural language processing, machine learning, deep learning, and predictive APIs, among other core applications. We found that AI startups have raised an aggregate $967M in funding since 2010, with investments going to companies in 13 separate countries and 10 industry categories, including business intelligence, e-commerce, and healthcare.