Businesses
risk missing major growth opportunities unless CEOs take immediate steps to
pivot their workforces and equip their people to work with intelligent
technologies, according
to new research by Accenture.
The Accenture Strategy report, Reworking the Revolution: Are you ready to compete as intelligent technology
meets human ingenuity to create the future workforce?, estimates that if businesses invest in Artificial
Intelligence (AI) and human-machine collaboration at the same rate as top
performing companies, they could boost revenues by 38 percent by 2022 and raise
employment levels by 10 percent. Collectively, this would lift profits by
US$4.8 trillion globally over the same period. For the average S&P500
company, this equates to US$7.5 billion of revenues and a US$880 million lift
to profitability.
Impact of greater AI
spending on revenue and employment growth, 2018-2022
Both leaders and workers
are optimistic about the potential of AI on business results and on work
experiences, according to the study. Seventy-two percent of the 1,200 senior
executives surveyed said that intelligent technology will be critical to their
organization’s market differentiation and 61 percent think the share of roles
requiring collaboration with AI will rise in the next three years. More
than two thirds (69 percent) of the 14,000 workers surveyed said that it is
important to develop skills to work with intelligent machines.
Yet, a disconnect between
workers’ embrace of AI and their employers’ efforts to prepare workers puts
potential growth at risk. While a majority (54 percent) of business
leaders say that human-machine collaboration is important to their strategic
priorities, only three percent say their organization plans to significantly
increase its investment in reskilling their workers in the next three
years.
“To achieve higher rates
of growth in the age of AI, companies need to invest more in equipping their
people to work with machines in new ways,” said Mark Knickrehm, group chief
executive, Accenture Strategy. “Increasingly,
businesses will be judged on their commitment to what we call Applied
Intelligence - the ability to rapidly implementintelligent
technology and human ingenuity across all parts of their core business to
secure this growth.”
The research suggests
that there is a strong foundation on which to boost AI skills investment.
Sixty-three percent of senior executives think that their company will create
net job gains in the next three years through AI. Meanwhile, the majority of
workers (62 percent) believe AI will have a positive impact on their work.
The report shows how
pioneers are using human-machine collaboration not just to improve
efficiencies, but to drive growth through new customer experiences. An online
clothing retailer’s AI helps its stylists learn more about customers’
preferences so that they can offer a unique and highly personalized service.
And a sports shoe brand set a new bar in customization and speed-to-market by
aligning highly skilled tailors and process engineers with intelligent robots
to design and manufacture in local markets.
“Business leaders must
take immediate steps to pivot their workforce to enter an entirely new world
where human ingenuity meets intelligent technology to unlock new forms of
growth,” said Ellyn Shook, Chief
Leadership and Human Resources Officer, Accenture. “Workers are impatient to
collaborate with AI, giving leaders the opportunity to demonstrate true Applied
Intelligence within their organization.”
To help leaders shape the
future workforce in the age of AI, Accenture makes the following
recommendations:
1. Reimagine
Work by reconfiguring work from the bottom up. Assess tasks, not
jobs; then allocate tasks to machines and people, balancing the need to
automate work and to elevate people’s capabilities. Nearly half (46 percent) of
business leaders agree that job descriptions are already obsolete; 29 percent
say they have redesigned jobs extensively.
2. Pivot
the Workforce to areas that unlock new forms of value. Go beyond process
efficiencies and prepare the workforce to create new customer experiences. Fuel
new growth models by reinvesting the savings derived from automation into the
future workforce. Foster a new leadership DNA that underpins the mindset,
acumen and agility required to seize longer-term, transformational
opportunities.
3. Scale
up ‘New Skilling.’ Measure the workforce’s level of skills and willingness to
learn to work with AI. Using digital platforms, target programs at these
different segments of the workforce and personalize them to improve new skills
adoption. Accenture has developed a ‘new skilling’ framework based on a
progression of skill level and using a suite of innovative digital learning methods
that maximizes training investment at speed and scale.
Methodology
Accenture combined quantitative and qualitative research techniques in order to analyze the attitudes and readiness of workers and business leaders with regards to collaborating with intelligent technologies. The research program included a survey of 14,078 workers across skill levels and generations and a survey of 1,201 senior executives. These were carried out between September and November 2017 in 11 countries and (Australia, Brazil, China, France, Germany, India, Italy, Japan, Spain, UK and the USA) and the following industry sectors: Automotive, Consumer Goods & Services; Health & Life Sciences; Infrastructure & Transportation; Energy; Media & Entertainment; Software & Platforms; Banking (Retail & Investment); Insurance; Retail; Telecommunications; Utilities.
Accenture combined quantitative and qualitative research techniques in order to analyze the attitudes and readiness of workers and business leaders with regards to collaborating with intelligent technologies. The research program included a survey of 14,078 workers across skill levels and generations and a survey of 1,201 senior executives. These were carried out between September and November 2017 in 11 countries and (Australia, Brazil, China, France, Germany, India, Italy, Japan, Spain, UK and the USA) and the following industry sectors: Automotive, Consumer Goods & Services; Health & Life Sciences; Infrastructure & Transportation; Energy; Media & Entertainment; Software & Platforms; Banking (Retail & Investment); Insurance; Retail; Telecommunications; Utilities.
The
research also included economic modelling to determine the correlation between
AI investment and financial performance, in depth interviews with 30 C-suite
executives and ethnographic interviews with 30 individuals who have been
working with AI.
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