RESEARCH REPORT

In brief

In brief

  • Intelligent technologies like AI challenge the skillsets of today's workforce, but can also support the "new skilling" needed for growth.
  • AI and Big Data can help create individually tailored learning paths for workers, keeping people agile and business-relevant.
  • Companies should use delivery platforms and content ecosystems to broaden the support and knowledge available to workers.


Today, the average company’s workforce is not able to continuously refresh the knowledge and skill levels needed to capitalize on new business opportunities. This situation threatens to worsen over time. Here’s a different approach: machine learning and artificial intelligence solutions can proactively offer the workforce an entirely new, future-oriented learning experience across devices and channels—one that is customized, personalized, dynamic and predictive.

Being bold with “new skilling” bets

Business leaders know that thriving in the digital age requires them to take on the disruptive forces changing their industry—with speed, confidence and bold new bets. Nothing less than a similarly bold approach to “new skilling” will prepare the workforce to support continuous innovation and growth. New skilling programs should be driven by innovation, aligned with dynamic business objectives and designed to improve business performance.

By adopting a zero-based mindset, leading companies can take a clean-sheet approach to redesigning the learning organization with clear objectives in mind—for example, reducing time to implementation and improving speed to competency. Resources can be shifted from initiatives that aren’t contributing to desired business outcomes, to ones that will.

Delivering personalized learning experiences

Companies should reinvent themselves to deliver more personalized employee learning experiences based on roles, job profiles and competency-based assessments. Artificial intelligence and predictive analytics technologies can offer guidance by understanding employee profiles and then matching a person’s situation to available learning.

One caveat: Using employee data for either current or future roles is complicated. Based on our research, about half of organizations’ workforces have concerns about data collection. Responsible leaders will develop their learning programs in a way that builds trust in how data is collected and used, and that focuses on outcomes that benefit employees as well as the business.

Sixty-one percent of workers would be willing to have technology collect data about them and their work in exchange for more customized learning and development opportunities.1

Increasingly, informal learning opportunities—often on mobile devices—will supplant formal, classroom training. According to the “70/20/10” rule for the learner experience, companies should emphasize on-the-go learning, followed by lower percentages of social and formal learning.

A key here is to leverage delivery platforms and content ecosystems to broaden the knowledge and support available to workers, and then machine learning such that your learning systems adapt to the changing needs of workers.

Accenture asked executives what percentage of their workforce will move into new roles requiring substantial reskilling due to the impact of technology.

17%

Of executives said that over 60 percent of their workforce requires substantial reskilling for new roles today.

43%

Of executives said that over 60 percent of their workforce will require substantial reskilling for new roles over the next three years.

Preparing for the future with new skilling

When considering your own new-skilling program, keep the following points in mind:

  • Create individually tailored learning paths using Big Data and analytics.
  • Develop preliminary prototypes and proofs of concept focused on AI-enabled learning.
  • Build trust with employees by using data in an ethical and responsible way.
  • Consider enterprise metrics for evaluating the effectiveness of learning and the workforce of the future.

1 “Putting trust to work: Decoding organizational DNA”, Accenture Strategy, 2019.

About the Authors

Christopher Chu

Managing Director – Accenture Strategy, Talent & Organiza​tion


Tim Good

Managing Director – Accenture Strategy, Talent & Organization


Francisco Puertas

Managing Director – Accenture Strategy, Talent & Organiza​tion


Jay Kerr

Senior Manager – Accenture Strategy, Talent & Organization

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