The big disconnect: AI, leaders and the workforce
AI promises to boost revenues and employment. But many businesses risk missing this opportunity unless they rethink how their people can work with intelligent machines.
Committing to human-machine collaboration will help AI create new growth, not just drive efficiencies.
Workers are eager to work with AI, but demand more support to reskill.
Artificial Intelligence (AI) has reached a tipping point in 2018. It's going mainstream. More than merely automating the work people do, it will usher in a new era of human-machine collaboration: Think advanced robots that can sense, predict and help their human co-workers complete tasks, or software that doesn't just interpret vast volumes of complex data, but learns to improve its ability to do so.
IDC estimates that spending on cognitive systems will jump 54 percent this year, which promises to drive growth for businesses and economies. In fact, Accenture analysis shows that if companies invest in AI at the same rate as today's leading businesses, they could boost revenues by 38 percent and lift employment by 10 percent within the next five years. Further, we estimate that by 2035, AI could add US$7.4 trillion in gross value to the U.S. economy.
But while this paints a promising picture, our research reveals three disconnects holding organizations back from unlocking trapped value at the intersection of humans and machines:
Investment in AI is not matched by investment in reskilling.
AI is a lever of growth, but it is mainly used to drive efficiencies.
Employers believe—incorrectly—that workers are unwilling to work with AI.
Disconnect 1: Investment in AI is not matched by investment in reskilling
A growing share of business leaders are making the case for AI. More than one-third (35 percent) of executives in our survey believe that intelligent technologies will improve productivity and customer experience and engagement, and 34 percent believe it will foster innovation. Almost two-thirds plan to invest in big data analytics in the next three years, and half will invest in data visualization and robotic process automation.
One Chief IT Security Officer at a US infrastructure and transportation company told us, "We're using intelligent technologies to a great extent and are investing around one-to-two percent of our revenues in AI every year."
increase in investment in AI, 2017 over 2016
of business leaders plan to invest significantly more in reskilling in the next three years
However, while companies are investing heavily in intelligent systems, they're not investing enough in reskilling people to work with these technologies and unlock the full value of human-machine collaboration:
61% of executives expect the share of roles requiring collaboration with AI to increase in the next three years. 58% plan to use AI to augment roles in their organization.
But only 3% of employers indicate they are planning to significantly increase investment in training and reskilling programs.
To address the disconnect in AI and skills investment, business leaders should:
Make the business case for reskilling within the organization: Companies should take the savings generated by automation and reinvest them in training and reskilling programs to facilitate human-machine collaboration—and unlock new sources of value.
Prioritize skills for development: Organizations should assess tasks needed to achieve business outcomes and identify skill gaps that can be closed with training investment.
Apply innovative learning technologies: Augmented and virtual reality can help train people at speed and scale by simulating tasks and stimulating workers.
Reworking the revolution
Disconnect 2: AI is a lever of growth, but it is mainly used to drive efficiencies
AI helps create new ideas: 42 percent of executives we surveyed believe intelligent technologies will be behind every innovation they implement in the next three years. Executives acknowledge the pressing need to invest in AI to remain relevant, and the competitive advantage to be gained by being an early adopter.
The CEO of a Japanese insurance firm told us, "Insurance leaders all over the world are aggressively implementing AI, and we are seeing a very strong effect of AI in their businesses. It would have been nearly impossible for us to stay in business if we continued doing things the traditional way."
Accenture analysis shows that the adoption of intelligent technologies is still at a nascent stage. Most AI applications today focus on efficiency gains rather than on amplifying human potential, and our research confirms this: When asked to identify the top three benefits of intelligent technologies, the highest proportion of executives—35 percent—cited improved productivity.
One IT director from an Indian energy firm told us that pushing down costs was the primary motivator behind investing in AI: "The key driving factor is cost reduction. These technologies offer a huge amount of cost reduction opportunities and processes for increasing efficiency."
This is further demonstrated by business leaders prioritizing automation over elevating the capabilities of their people: While three-quarters (76 percent) of executives said they have used AI to augment tasks over the last three years, 90 percent said they have used the technology to automate tasks.
To address the disconnect between today's efficiency play and AI's potential as a growth lever, business leaders should:
Shift their strategic focus: Test AI applications in growth projects that advance existing products and services, then scale the successful experiments.
Pivot the workforce: Redesign teams around the project-based work that characterizes new AI-driven business models. Empower them with more autonomy, and encourage a more experimental and risk-hungry culture.
Commit more AI investment to human-machine collaboration: Our analysis of industry sectors shows that if companies were to invest in AI and human-machine collaboration at the same level as the top-performing fifth of companies, they could boost revenues from as much as 28 percent in the automotive sector to as much as 51 percent in the consumer goods sector (see graph below).
Disconnect 3: Employers believe—incorrectly—that workers are unwilling to work with AI
Business leaders say they're held back from adopting and reaping the maximum benefits of AI because of a lack of readiness and willingness among workers.
In fact, nearly half (47 percent) of executives we surveyed ranked the growing skills gap as one of the top three trends influencing their workforce sourcing strategy, and executives believe that just 26 percent of their workforce, on average, is ready to work with intelligent machines.
But while the majority of executives expect an increase in the number of roles requiring human-machine collaboration, nearly one-quarter (23 percent) of them point to worker resistance to using intelligent technologies as one of the top three challenges of implementing them.
Privacy and income impacts are two big issues perceived by executives we surveyed: Nearly two-thirds (64 percent) believe their employees think that the use of AI in the workplace will compromise their privacy, and more than half (57 percent) believe their employees think that their incomes will decrease with the adoption of AI.
The CEO of a bank based in the UK told us, "One of the issues that we faced was that the technology was pretty new and there was a resistance in the workforce. The technology was initially associated with job cuts and people were reluctant to undergo training."
But this perception is likely to be incorrect: We interviewed more than 14,000 workers globally. More than six in 10 (62 percent) believe that AI will have a positive impact on their work. What's more, two-thirds (67 percent) of workers believe it will be important to learn new skills to work with AI in the next three to five years, and nearly one-third (31 percent) believe that they themselves are primarily responsible for keeping up their own skills.
To address the disconnect between employer perceptions and workers' actual willingness, business leaders should:
Listen and learn: Companies need to develop a better understanding of individual workers' expectations and aspirations and then tailor training to address differences in motivation and skill levels. Invest in awareness programs to prepare people to work with intelligent technologies.
Measure impact: Take a holistic approach to ensure that training is relevant—leveraging intelligent technologies to assess which training methods work for which segments and then measuring employee interest and engagement as well as the effectiveness of various training methods.
Foster a new leadership DNA: In an increasingly digital workplace, uniquely human attributes such as empathy, creativity, listening and inclusion are needed now more than ever, and leaders should be visible examples of these human attributes and role models of the culture. Companies should also develop leaders at all levels where the actual work occurs, empowering employees to exercise autonomy and make decisions.
Senior Managing Director – Talent and Organization
Mary Lyons
Global Managing Director – Talent and Organization, Accenture Strategy
Gaston Carrion
Managing Director – Talent and Organization, Accenture Consulting
Mamta Kapur
Research Manager – Accenture Research
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