Despite the widespread use of ChatGPT in the workplace, we are still in the proof-of-concept or pilot phase of generative AI !

?? ChatGPT has reached critical mass adoption faster than other modern innovations but that doesn't mean a massive productivity gain at all !

?? About a third of employees under 30 have now used ChatGPT for work!

The spread of generative AI is impressive not only in terms of geographic breadth but also speed of adoption across industries.

?? Generative AI’s potential is vast, yet years of scaling are needed for full productivity benefits.

?? While many employees notice an improvement in productivity, more than one-third of generative AI-using employees report no change or a decline in productivity after adopting generative AI, according to two new interesting research published by Oliver Wyman Pew Research Center using data ?? from a survey of 10,133 U.S. adults during February 7 to February 11, 2024.

?The three potential usage of ChatGPT

Researchers found three potential reasons people might use ChatGPT:

1?? For work

2?? To learn something new

3?? For entertainment

Researchers found that the share of employed Americans who have used ChatGPT on the job increased from 8% in March 2023 to 20% in February 2024.

Another research published recently by Oliver Wyman Forum found that From June to November 2023, Generative AI use exploded across all job types, with a 62% increase in use overall across white-, blue-, and pink-collar workers.

?Usage of ChatGPT has risen accross all age groups

Researchers found that about a third of employed Americans under 30 have now used ChatGPT for work.

?? The usage of ChatGPT for work, learning or entertainment has largely risen across age groups over the past year.

?? There are striking differences between these groups (those 18 to 29, 30 to 49, and 50 and older)

?Mass adoption ≠ mass productivity

Researchers believe that the dramatic uptake in generative AI has been useful for many but hasn’t yet resulted in significant productivity gains across the board.

Generative AI’s true rewards of large-scale productivity transformation will likely require work to be restructured at an organizational level.

Researchers found that employees are still in early experimentation mode with generative AI, testing how to optimize their individual ways of working. They provide three phased of Generative AI impact on productivity:

?? Individual Benefit - Projected productivity benefit: low Estimate: 0–1 years

In this phase, productivity gains mainly are seen at the micro level

? Employees are primarily learning generative AI on their own while employers are discovering its potential benefit to their organizations

? Few workplace measures are in place for overall use

?? Scaling Up - Projected productivity benefit: medium Estimate: 1–5 years

? A growing number of employees and teams are increasingly integrating generative AI into workflows

? Employers are beginning to restructure some jobs and practices to optimize generative AI use while upskilling employees

? As a result of early investment, leading companies in generative AI adoption will begin seeing productivity gains at scale

?? Workplace Maturity - Projected productivity benefit: high Estimate: 6–10 years

? Enterprise integration pays off as generative AI pushes global productivity to new heights

? Entire organizations have restructured around generative AI, including the creation of new jobs and reconstruction of established jobs

? Employees across industries are expected to have some level of experience with generative AI upon entry

? Widespread generative AI guidelines on data, privacy, and ethics are fully in place

Researchers noticed that while many employees notice an improvement in productivity, more than one-third of generative AI-using employees report no change or a decline in productivity after adopting generative AI.

?? Specifically, more than 10% of blue-collar workers perceive a decrease in productivity, with workers in some sectors, such as transportation, which is heavily reliant on efficiency and time management, reporting up to 19% productivity losses.

?The S-Curve of Gen AI for HR

According to Dave Ulrich , we are today in the “S-curve” of GenAI for HR. Moving up this S-curve will reduce variance in how to think about and use GenAI for HR.

?? Also The RBL Group researcher believe that HR will be able to create information asymmetry beyond optimizing and reporting legacy and shared best practices to offering guidance to personalize which practices deliver results that matter to stakeholders.

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As demonstrated by the analysis of these 3 wonderful pieces of research that I have just shared with you, we must carefully analyze the evolution of the adoption of Generative AI applications in the world of work and the impact on HR. Despite the articles on this subject, we are still at the proof-of-concept stage according to researchers and the productivity gains are not yet up to par. Just because there is mass adoption doesn't mean productivity is spectacular.

Thank you ?? Pew Research Center Oliver Wyman Forum The RBL Group researchers team for these insightful findings: Colleen A. McClain Dave Ulrich Ana Kreacic Lucia Uribe John Romeo Amy Lasater-Wille Ravin Jesuthasan, CFA, FRSA Simon Luong

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