The Four scenarios for the near future of GenAI hinge on factors such as Trust, Skill acquisition, Cultural shifts, and unclear Business value!
Nicolas BEHBAHANI
Global People Analytics & HR Data Leader - People & Culture | Strategical People Analytics Design
?? Currently, the future of GenAI in the workforce is uncertain and undefined.
?? By mid-2024, only 12% of workers report using GenAI daily in their jobs.
?? Barriers to GenAI adoption include issues of trust, skill acquisition, cultural shifts, and unclear business value.
?? Researchers have proposed four scenarios to help stakeholders explore the potential evolution of GenAI in the workforce, according to a new interesting research ?? published by World Economic Forum and 普华永道 using data ?? from from interviews with more than 20 early adopters from a wide range of industries and regions across the world.
?The future of GenAI in the workforce remains uncertain and undefined.
Despite rapid developments, the technology is still in its infancy, making it impossible to extrapolate the extent to which productivity gains and job augmentation may be achieved in the near future. Acknowledging the unpredictable nature of the future,
Researchers considers four scenarios to enable various stakeholders to think through the multiple ways in which GenAI in the workforce could evolve:
1?? Scenario 1: High trust, current applicability & quality
In this scenario, enthusiasm for GenAI workforce adoption is high. Leadership hopes GenAI will contribute to the solving of labour shortages and anticipates it will improve the quality of work. There is a fear of missing out on opportunities as well.
Over time, however, in this scenario it turns out that GenAI does not live up to the sky-high expectations. Because confidence is so high, employees also use tools that are not validated or without proper knowledge.
2?? Scenario 2: Low trust, current applicability & quality
The major difference between scenario 1 and 2 is the lack of enthusiasm and willingness among employees to deploy GenAI in scenario 2. Workers are inclined not to emphasize its potential and what it can do but rather the biases and the sometimes unreliable outcomes.
3?? Scenario 3: Low trust, expanding applicability & quality
At first glance, this scenario resembles Scenario 2: organizations want to deploy GenAI, but a large part of the workforce is resisting or hesitant. However, in this scenario, low trust is due to concern about job displacement as opposed to fear of incorrect GenAI tool outcomes.
4?? Scenario 4: High trust, expanding applicability & quality
with trust being high and quality and applicability rapidly expanding, enabling organizations to scale up use cases faster
?What is job augmentation?
Researchers describe “job augmentation” as a process where GenAI not only partially automates certain tasks within a job role but also enhances human workers’ capabilities in performing other tasks.
Job augmentation may go beyond technical productivity increase to also enhance job quality and worker well-being.
In the other hand, Job automation refers to the use of GenAI to fully perform tasks that were previously performed by humans in a given occupation.
?The emerging impact of GenAI on productivity gains and job augmentation
Like other recent advances in automation and AI technologies, the rise of GenAI has led to concerns about possible job displacement.
Research examining the potential impact of GenAI on jobs commonly operates on the premise that job roles and occupations are composed of various tasks, some of which may be susceptible to varying degrees of automation by GenAI. For instance, tasks that are repetitive or routine are more exposed to automation than those requiring significant human interaction. While a wide range of tasks may be fully automated by GenAI, research to date has found very few examples of jobs that could be displaced in this way in their entirety.
?Current barriers to scaling GenAI adoption
Researchers identified several barriers to GenAI adoption, including concerns about trust, skill acquisition, cultural changes, and unclear business value:
?? Trust
Trust is a crucial factor that must be considered when embracing new technologies. GenAI models are sometimes referred to as “black box” systems due to the complexity of their algorithms, raising concerns about the outcomes they generate and transparency
?? Skills
At a workforce level, two out of five employers report that a lack of adequate AI-related skills is an obstacle to the integration of GenAI at work.
?? Culture
The culture of an organization is a crucial factor in the adoption of new technologies such as GenAI. Organizations interviewed for this report stress the importance of change management: successful introduction of GenAI depends on experiments and finding use cases. This requires a stimulating and supportive culture.
?? Business value
Companies often cite costs as a significant barrier to GenAI adoption, with a number of them unsure of the technology’s potential benefits. The uncertainty is amplified by the limited evidence available on the impact of GenAI on firm performance.
?An actionable framework enhance productivity through GenAI adoption.
Combining insights from the scenarios and lessons learned from early adopters outlined previously, researchers proposes an actionable framework for promoting job augmentation and workforce productivity growth with GenAI.
The proposed framework is based on two iterative stages: Starting and Scaling. In the Starting phase, organizations pilot and test various GenAI workforce applications and tools to gather important insights on what works well and what does not, while minimizing initial investment. Based on these early results and lessons learned, organizations may then make informed decisions on broader measures, which leads to the Scaling phase
The different elements that organizations should address during the Starting and Scaling phases revolve around two core themes: Enable and Engage.
?? ???? ???????????????? ????????:
This insightful research highlights intriguing patterns regarding the future of GenAI adoption and its inherent uncertainties. With the right enabling conditions, GenAI has the potential to augment jobs and boost productivity. However, organizations must first understand the technology’s value for their specific needs, identify suitable use cases, and rigorously test the solutions. Researchers propose a flexible framework focusing on key elements that could help organizations achieve widespread GenAI adoption within their workforce and beyond.
??Thank you 普华永道 and World Economic Forum researchers team for sharing these insightful findings: Peter Brown MBE and Till Alexander Leopold
?? Follow me as a LinkedIn Top Voice on LinkedIn (+40 000), and click the ?? at the top of my profile page to stay on top of the latest on new best?HR, People Analytics, Human Capital and Future of Work research, become more effective in your HR function and support your business, and join the conversation on my posts.
???Join?more than 20,000+ people and subscribe to receive my Weekly People Research
Everyday, I share a new research article about?People Analytics, Human Capital, HR analytics, Human Resources, Talent,…
Building Future-Ready Organizations with Innovative People & Culture Solutions | Empowering Talent, Driving Growth, Leading Transformational Change
3 个月Super amazing ?? Nicolas. Spot on , as with most changes AI adoption will mature with time. However, the speed of AI adoption is a big challenge.
Human Resource Professional | MBA | Coporate Recruiting Professional- ASA | Ex-Wirtgen Group,A John Deere Company
3 个月Another excellent piece of research on GenAI! Insights from the World Economic Forum and PwC provide a compelling roadmap for understanding its future in the workplace. Successful GenAI adoption requires more than just technology; it hinges on strong leadership and actionable experimentation. Organizations can start by embedding GenAI pilots within smaller teams to tackle real-world challenges, ensuring measurable outcomes and creating a feedback loop that fosters trust and scalability. Prioritizing transparency in AI outputs, along with robust upskilling initiatives, will further demystify GenAI and minimize resistance. Thank you for sharing!
Head of Talent Development
3 个月The future of GenAI hinges on trust, skills, cultural shifts, and clear business value. Exploring these through four scenarios offers a structured way for stakeholders to navigate its uncertain workforce evolution.
Is Your Team Feeling Discouraged? ?? Let’s Turn That Around! ?? Boosting Productivity, Driving Motivation & Engagement ?? Founder @AlbiCoins | 15+ Projects for Global Enterprises | Workplace Innovation Expert ?? DM
3 个月Great post! Personally, I think we’re likely to see a progression from Scenario 2 (low trust, current quality) toward Scenario 4 (high trust, expanding quality) as organizations invest in building understanding and demonstrating clear ROI.
Industry Veteran | Exploring Future of Work | Great Manager’s Coach & Mentor
3 个月Trust, Skills, Culture, & Business Value - GenAI's four horsemen ?? of the uncertain future! ??? The race to GenAI adoption is a marathon run than a sprint. ?? Nicolas BEHBAHANI for sharing. ??♂? "Generative AI is not just a tool for automation; it's a catalyst for innovation, unlocking new possibilities & transforming how we approach problem-solving across industries." - Satya Nadella, CEO of Microsoft. ? Scenario 4: High trust, expanding applicability & quality seems the most likely to happen. PS: Business Value is paramount - VALUE: V - Vison (is AI is integrated part of the Business) A - Applicability (Current & Future) L - Learning on AI with Culture shifts. U - Understanding - Building trust in GenAI's - Quality & Reliability. E - Execution (Effective implementation of AI) for Value creation.