Generative AI will potentially disrupt up to 90% of existing jobs and 11% of displaced employees almost 1% of the total Workforce !

?? 13% of companies could be leveraging GenAI in three to four years, nearly half could embrace it in a decade’s time

? In the next 10 years, most jobs (90%) could be disrupted in some way by generative AI.

?? Generative AI could inject anywhere from $477 billion to $1 trillion into the US economy by 2032, depending on the level of business adoption.

?? The more disruption workers face, the more difficult it will be to adapt to new ways of working.

?? CEOs could see an exposure score of more than 25% by 2032, as they begin using gen AI for everything from reviewing reports and analyzing operations to conducting competitive assessments and making strategic decisions, according to a new interesting research published by 高知特 Cognizant and Oxford Economics researchers using data ?? from US Department of Labor database that contains 18,000 tasks that drive the US economy, and carefully examining the impact generative AI could have on the 1,000 jobs composed of these tasks.

?The three scenarios for GenAI impact on US GDP

Researchers develop three adoption scenarios:

1?? If business adoption of gen AI is low, the annual productivity boost in the US could grow to 1.7% by 2032.

2??if adoption is moderate, then this productivity figure could reach 2.5% by 2032.

3?? if adoption comes in at the high end, that figure could soar to 3.5% by 2032.

? From the perspective of total economic output, researchers found that US GDP would see a boost between $477 billion and $1 trillion in 10 years’ time

?Impact of Job Disruption

?? To better understand what that disruption will look like, researchers analyzed almost 1,000 professions and their associated tasks and calculated a “theoretical maximum exposure score” for each one (referred to in this report as the “exposure score”).

Researchers found that most jobs will see some change from gen AI, and over half could be greatly impacted. They predict that from 2023 to 2032, the percent of jobs with high exposure scores (25% and above) could increase from 8% to 52%, a 550% uptick !

Researchers believed that Generative AI will change what’s generally called knowledge work, everyone from entry level number crunchers to seasoned heads of business units to C-suite executives will see their job evolve over the next decade.

?Job and worker impact in five years (2027)

Researchers plotted an array of job categories by their exposure scores and friction scores and they mapped jobs that will be most impacted, and those with the most difficulty or ease of finding a new job.

Key findings:

• Office and administrative roles -such as clerical assistants and receptionists - have a predicted exposure score of 4% but are saddled with a friction score of 80, indicating they will face an uphill battle.
• Software developers and database administrators (with relatively high predicted exposure scores of 8%) have relatively low friction scores of about 40, meaning their journey to new employment is less complicated, likely due to their in-demand skill set
• In healthcare, ongoing staffing challenges are driving up service costs while dragging down service quality.
• Emergency physicians, for example, will see up to one-third of their tasks automated over the next decade—a process that will enable organizations to deliver more healthcare services without the need to ramp up hiring.

?? Researchers conclude that combining the friction scores and the predicted exposure scores provides us with a clear lens into the disruption ahead. They also foresee an upside to generative AI workforce disruption, such as its positive impact on ongoing labor shortages that exist in key areas of the economy.

?Gen AI-driven change will follow a S-curve

Researchers believed that Gen AI-driven change will follow a similar s-curve as other tech advances, such as enterprise-grade software:

?? a gradual rise, to a dramatic spike, to a plateau in which the technology becomes refined and pervasive.

Researchers believed that after the 15-year mark, the steep climb slows, but adoption continues to grow for at least 20 more years. They predict that there are three stages to this growth story over the next 10 years, each with its own drivers, challenges and opportunities.

?? Researchers recommend following tenets that organizations can take the crucial first steps to bolster confidence, build trust and open the door to a new age of productivity and prosperity:

??Take care of your people

The fear of layoffs should neither be downplayed nor ignored. Addressing this concern is crucial for fostering trust between employer and employee, and requires proactive and robust measures. No business can guarantee layoffs will not occur. However, all organizations have it in their power to roll out a new generation of reskilling programs at a level never seen before

??Innovate or stagnate

To shore up employee trust, and fully participate in all generative AI has to offer, businesses need to think about how the technology will change how they do business and even the business they’re in. Rather than engaging in quarter-by-quarter thinking, they need to reimagine how they will operate and create value in 10 years’ time

??Build confidence with transparency

Building trust in generative AI requires a clear and demonstrable commitment to mitigating any detrimental effects of the technology on people, society and the business itself. Organizations must be transparent about how gen AI systems are developed and deployed, the values they’re designed to uphold, and the measures in place to ensure they do so.

??Put gains to good use

Employee-employer trust will only be forged when businesses give at least some consideration to how generative AI benefits will be distributed across society without hampering innovation and investment

?? Finally researchers emphasized that while they focused on the US workforce, the general themes that emerged from the findings can be applied globally and they noticed that today's stage is characterized by experimentation and cautious implementation. Organizations are tentatively deploying gen AI for tasks that are manageable in scope and low in risk. This is the critical time for organizations to explore and commit to major overhauls of their business and operating models, and to begin establishing a foundation of trust with their employees and the world at large.

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This remarkable research and projections not only underscore the power of gen AI to enhance, augment and automate many work tasks across all areas of the economy, but also set the stage for a profound shift in how we approach work, productivity and economic growth. It is now clear with this research that some workers will need to learn to work with Generation AI as it helps them with certain tasks, while others will have their role taken over by technology.

Thank you ?? 高知特 Cognizant Oxford Economics researchers team for these insightful findings:

Ollie O'Donoghue Duncan Roberts Lynne LaCascia Catrinel Bartolomeu Mike Turner Naveen Sharma Vasilis Douzenis Henry Worthington

Dave Ulrich George Kemish LLM MCMI MIC MIoL

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