A recent Gartner survey of Chief Information Officers finds that while just four percent have already implemented AI in some form in their businesses, 46 percent have plans in place to do so. Although there are many obstacles to implementing this groundbreaking technology, soon companies that fail to take advantage will lag behind. To help ease the potential pains of diving into adoption, our colleagues who conduct IT management research at Gartner have four recommendations to ensure success in the early stages of AI implementation: start small; focus on helping, not replacing, people; plan for knowledge transfer; and choose transparent solutions.
“Don’t fall into the trap of primarily seeking hard outcomes, such as direct financial gains, with AI projects,” Gartner analyst Whit Andrews explains. “In general, it’s best to start AI projects with a small scope and aim for ‘soft’ outcomes, such as process improvements, customer satisfaction or financial benchmarking.”
Early forays into AI should be learning experiences rather than attempts at large-scale change that dramatically reshape a department or function. It’s important to set modest goals for AI initiatives, given that the most important outcome will be gaining the knowledge and expertise to successfully apply the technology to a work stream. Additionally, while many employees fear AI could replace them, the easiest way to assuage those concerns is to deploy AI solutions that make employees’ lives easier. As Gartner EVP Peter Sondergaard remarked in his observations from the recent World Economic Forum in Davos, Switzerland, AI is expected to create many more jobs than it destroys, while generating massive value and saving billions of hours of worker productivity.
That means there’s an opportunity to get employees engaged with AI adoption as a technology that will make their jobs easier, rather than obsolete.
Salesforce will invest $2 billion in its Canadian business over the next five years, the company announced on Thursday, growing its office space, data center capacity, and Canadian workforce. The announcement came during a visit by Canadian Prime Minister Justin Trudeau to San Francisco, where he is meeting with tech company executives to encourage them to grow their businesses in Canada, Reuters reports. In particular, Trudeau hopes to woo these tech companies with Canada’s more business-friendly immigration policies at a time when President Donald Trump is cracking down on legal immigration to the United States:
Salesforce CEO Marc Benioff did not specify why the company chose Canada but he said, “Like you, we’re a city that values diversity, we value equality and we also value innovation. …We know we’ll be able to have a great business environment in Canada.” The company did not respond to a question about whether the immigration policies in the two countries influenced the decision.
Other American tech companies have bitten at Trudeau’s offer in the past year, Reuters adds, bolstering his efforts to make Canada (particularly Toronto) a hub for artificial intelligence and other cutting-edge technologies. Since last May, Uber, Alphabet’s DeepMind unit, Facebook, and Microsoft announced plans to establish or expand AI research labs in Canadian cities, including Toronto, Edmonton, and Montreal. Toronto is also on Amazon’s short list of contenders for its second headquarters in North America.
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The 2018 World Economic Forum, recently concluded in Davos, Switzerland, brought together political, business, and cultural leaders from around the globe to discuss the future of the global economy and its foremost institutions. Gartner EVP Peter Sondergaard was on hand to take in the events and speak with influencers at the forum, where he observed a few key themes in discussions of the future of the workplace: The increasingly digital nature of business, the rise of artificial intelligence, and the impact technology can have on improving diversity and inclusion.
“It became abundantly clear that organizations have reached the point at which the digital workplace must be driven by both CIOs and heads of HR,” Sondergaard explained. This doesn’t mean technology will eliminate the need for people, just that employees will need to work in different ways and companies will need to offer guidance on how to do that. “Such changes will require new models of learning and development,” he continued, “as well as the creation of hybrid workplaces that combine technology and information to accommodate a mix of employees.”
Certainly, we have seen a wide range of technologies promise to reshape how the people and processes of the workplace operate, but artificial intelligence is the driving force behind the most groundbreaking offerings. It’s powering Google Jobs, wearable tech, analytical tools, and voice-activated tech such as Amazon’s Alexa, as well as the automation of processes from candidate sourcing to performance management. As a result, demand for AI talent has skyrocketed as technology providers are scrambling to keep up with the rapid rate of change.
While the rise of AI has fueled fears of the potential for a massive loss of jobs, Sondergaard is confident that AI should ultimately create jobs if deployed properly. “As was true of the Industrial Revolution,” he also pointed out, “technological advances as a result of AI will spur job creation. In 2020, AI will create 2.3 million jobs, while eliminating 1.8 million — a net growth of half a million new positions. Organizations will realize an added benefit as in 2021 AI augmentation will generate $2.9 trillion of business value and save 6.2 billion hours of worker productivity.”
Last year, the Montreal-based startup Element AI estimated that there were fewer than 10,000 people worldwide with the necessary skills to design artificial intelligence/machine learning systems, but the Chinese internet conglomerate Tencent Holdings later estimated the total number of AI researchers and practitioners at between 200,000 and 300,000 people.
Element AI came out with a new estimate on Wednesday, Jeremy Kahn reports at Bloomberg, putting the number of AI specialists with recently-earned PhDs at 22,000, of whom 3,000 are looking for work. With less restrictive parameters, however, the total number of AI experts could be four times greater:
Element AI said it scoured LinkedIn for people who earned PhDs since 2015 and whose profiles also mentioned technical terms such as deep learning, artificial neural networks, computer vision, natural language processing or robotics. In addition, to make the cut, people needed coding skills in programming languages such as Python, TensorFlow or Theano.
Glassdoor has released its annual list of the best jobs in America for 2018, ranked based on earning potential, job satisfaction, and availability. For the third year running, data scientist took the top spot, while other data and technology roles dominated the list, such as DevOps engineer (#2), electrical engineer (#6), mobile developer (#8), and manufacturing engineer (#10). All in all, technical roles make up 20 out of the 50 best jobs. The rest of the list comprises a variety of management roles, as well as several jobs in the health care sector.
“But there are at least four new titles on the list that help crunch that data and make decisions based on what they suggest,” Washington Post columnist Jena McGregor points out:
These include strategy managers (No. 7), business development managers (No. 14), business intelligence developers (No. 42) and business analysts (No. 43), each of which make the list for the first time, said Scott Dobroski, a career trends analyst at Glassdoor.
“There’s always a lot of tech jobs and health-care jobs — that’s not new and not going away anytime soon,” Dobroski said. “But the biggest trend this year was this emerging theme of business operations,” he said, or people “who make sense of all that data and recommend business decisions.” Many of the people hired for these jobs, he said, are former consultants who companies are bringing in-house to help with strategic and market decision-making.
“Maybe the occupational therapist and the HR manager jobs are in there because those folks are needed to deal with anyone who is not already a data scientist?” GeekWire’s Kurt Schlosser quips.
Gartner is projecting worldwide IT spending to reach $3.7 trillion this year, a 4.5 percent increase from 2017, with enterprise software expected to be the fastest-growing component of IT spend, growing by 9.5 percent from $355 billion last year to $389 billion in 2018. HR technologies are among the leading drivers of innovation in this space, with significant spending forecast on software-as-a-service solutions in financial management systems (FMS), human capital management (HCM), and analytic applications. Big data, algorithms, machine learning, and AI are among the technologies expected to drive growth in IT investments in the coming years.
(For readers who want to hear more about our IT spending forecast, Gartner analysts discuss these findings in detail in a complimentary webinar, available on demand here.)
For talent management leaders, this information carries significant implications. In the coming years, technology will inevitably be more embedded into the HR function: The only choice for leaders is whether they want to be on the front or back end of the adoption curve. Technology in the HR realm is advancing at a rapid rate, but the function seems consistently hesitant to take advantage of the opportunities and efficiencies it offers. A wide range of tools are newly available or in development that can help solve perennial HR challenges such as candidate vetting, employee wellness, space management, analytics strategy, recruiting and retaining diverse employees, understanding drivers of high performance, making learning more accessible, or offering digital assistants for all employees.
Diversity, new interviewing tools, data, and artificial intelligence are the four trends set to have the biggest impact on recruiting in the coming year, according to LinkedIn’s latest Global Recruiting Trends report. Based on a survey of over 9,000 talent leaders and hiring managers worldwide, along with a series of expert interviews, the report underscores the growing role of technology in shaping how companies meet their hiring goals, of which diversity is increasingly paramount. Nonetheless, while many HR leaders see these trends as important, the number of organizations fully acting on them lags far behind.
Diversity was the top trend by far, with 78 percent of respondents saying it was very or extremely important, though only 53 percent said their organizations had mostly or completely adopted diversity-oriented recruiting. In recent years, diversity has evolved from a compliance issue to a major driver of culture and performance, as more and more organizations recognize its bottom-line value. This shift was reflected in the LinkedIn report, with 62 percent of the companies surveyed saying they believed boosting diversity would have a positive impact on financial performance and 78 percent saying they were pursuing it to improve their culture. Additionally, 49 percent are looking to ensure that their workforce better reflects the diversity of their customer base.
Diversity was the only top trend identified in LinkedIn’s survey that wasn’t directly related to technology, but technology is definitely influencing how organizations are pursuing it. In the past year, we have seen the emergence of new software and tools to support diversity and inclusion. The aim of these tools is to remove the human error of unconscious bias from the recruiting process, but it’s important to be aware that automated processes can also develop built-in biases and end up replicating the very problem they are meant to solve. This is an issue we’ve been following in our research at CEB, now Gartner; CEB Diversity and Inclusion Leadership Council members can read more of our insights on algorithmic bias here.
The development of new interview tools and techniques was identified as the second most important trend, with 56 percent saying it was important. The LinkedIn survey found that the most common areas where traditional interviews fail are assessing candidates’ soft skills (63 percent), understanding candidates’ weaknesses (57 percent), the biases of interviewers (42 percent), and the process taking too long (36 percent). The report highlights five new interviewing techniques, all enabled by technology, that aim to address these problems: