To achieve the full potential of AI, organizations must reinvent work, reshape the workforce and prepare workers
A new report from Accenture reveals an urgent need for business leaders to look beyond how generative AI affects specific tasks and roles and, instead, start to scale gen AI by redesigning processes across their organizations, as well as how people experience work.
“When we look at scaling AI it needs to be through a holistic lens that reimagines how work is done, how to lead a workforce through that change, and how it can be a better experience for all.”
To do this, leaders must commit to learning and leading in new ways that deliver economic value, drive business growth and benefit their people. Yet two-thirds of executives say they do not have the technology and change leadership expertise to drive the reinvention needed to fully leverage the transformative power of gen AI.
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The report, “Work, workforce, workers: Reinvented in the age of generative AI,” highlights organizations’ conflicting views about how to achieve the promise of gen AI and reveals a critical gap in trust. While 95% of workers see value in working with gen AI, approximately 60% are also concerned about job loss, stress and burnout.
The findings show the gap between workers’ and business leaders’ perceptions of the impact of AI in the workplace. While almost 60% of workers worry about AI eliminating their jobs, less than one-third of C-suite leaders feel job displacement is a worry for their people. In addition, three-quarters of organizations do not have comprehensive strategies in place that will lead to positive worker outcomes and experiences.
Building on Accenture’s earlier research on unlocking human potential in the workplace, this latest report shows that leaving people “Net Better Off,” including supporting learning and well-being, is a clear pathway to building trust and a smoother adoption of gen AI. Among employees in the top quartile for feeling Net Better Off, people expressed greater comfort with the technology—particularly in terms of how they can apply it to their work.
“Success starts with leaders who are willing to learn and lead in new ways, to scale gen AI responsibly, to create value and ensure work improves for everyone,” said Ellyn Shook, chief leadership and human resources officer, Accenture. “It starts with asking a simple question: are people ‘net better off’ working here? This not only unlocks people’s potential and drives bottom-line growth, but also paves the way for workers feeling comfortable, trusting and ready to work with gen AI. What we’ve learned from the past as leaders is that what happens next is up to us. The best outcomes are ours to shape.”
‘Reinventors’ leading critical changes
Just 9% of organizations are “leading” when it comes to their capabilities for reinvention and how they maximize the potential for generative AI to boost the bottom line, while increasing people’s proficiency, and level of comfort, with the technology. Over half of these Reinventors are taking action to reshape the workforce by redesigning jobs and roles around gen AI, and three-quarters are actively involving their people to help shape enterprise change efforts. In addition, nearly half (47%) of Reinventors are already thinking bigger—recognizing that their processes will require significant change to fully leverage gen AI.
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“Generative AI has a more profound impact than any technology that has come before it. Our research underscores the need for organizations to have a gen AI reinvention strategy that addresses the full value chain, not just roles and tasks where AI can augment or automate how we already operate,” said Paul Daugherty, chief innovation and technology officer, Accenture. “When we look at scaling AI it needs to be through a holistic lens that reimagines how work is done, how to lead a workforce through that change, and how it can be a better experience for all.”
As part of their reinvention strategy, leading organizations are working to build an agile workforce by investing in skills mapping and data integration, so they have the predictive insights to ensure the right mix of skills to grow their people’s capabilities and their business. They are twice as likely to invest in growing people’s soft skills, along with tech skills, and twice as likely to anticipate workforce productivity gains of 20% or more in the next three years. By adopting these approaches, organizations can create $10.3 trillion in additional global economic value by 2038.
This agility must start at the top. For leaders to successfully bring a change of this magnitude into their organization, they must ensure that work—not only what they do, but how they do it—works for everyone. Nearly all workers surveyed (94%) reported being ready to learn gen AI skills, though just 5% of organizations are providing training at scale. With AI learning from both data and interactions with humans, who are responsible for ‘teaching’ the machines, building that capability and fostering a ‘teach to learn’ culture is paramount.
As the future of work continues to evolve, people-centric approaches, including actively engaging employees to understand and act on concerns and build trust, will set leading organizations apart in both performance and culture.
This report’s insights are anchored in two complementary research approaches: economic modeling, data science and global surveys to understand the broader macro, labor and industry trends surrounding gen AI and work; and experimental and ethnographic techniques to analyze the work experiences, mindsets and approaches happening at the individual employee and organization levels.
Collectively, these survey, interview and other ethnographic approaches yielded data points from over 7,000 C-suite leaders (CXOs) and 5,000 workers of large organizations (>1 billion USD in annual revenue) headquartered in 19 countries (Australia, Brazil, Canada, China, France, Germany, India, Ireland, Italy, Japan, Mexico, Netherlands, Singapore, South Africa, Spain, Sweden, Switzerland, United Kingdom, and United States) and representing 24 industries: Aerospace & Defense, Airline, Travel & Transport, Automotive, Banking, Capital Markets, Chemicals, Communications & Media, Consumer Goods & Services, Energy, Financial Services, Food Distribution, Health, High Tech, Hospitality, Industrial Goods & Equipment, Insurance, Life Sciences, Natural Resources, Professional Services, Public Service, Retail, Software & Platforms, and Utilities.
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