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 News
7 February 2018 | ITSM
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Reworking The Revolution
Are you ready to compete as intelligent technology meets human ingenuity to create the future workforce?...

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

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. 72 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 (69% in the UK). 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 (56 percent in the UK), only 3 percent say their organization plans to significantly increase its investment in reskilling their workers in the next three years (7 percent in the UK).

“While many businesses are committing to AI, if they are to drive real growth then they also need to equip employees with the skills required to collaborate effectively with machines,” said Payal Vasudeva, managing director, Accenture Strategy. “The full promise of AI depends on humans and machines working together in innovative ways to enhance customer experiences and create entirely new products, services and markets.”

The research suggests that there is a strong foundation on which to boost AI skills investment. 63 percent of senior executives across markets surveyed think that their company will create net job gains in the next three years through AI (66 percent in the UK). 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 across markets agree that job descriptions are already obsolete (54 percent in the UK); 29 percent say they have redesigned jobs extensively (41 percent in the UK).
  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.

For additional information or to view the report “Reworking The Revolution” click on the link https://goo.gl/K9Z3Ay.


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.

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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