Forecast predicts generative AI to make many white-collar workers blue

If a recent forecast from McKinsey & Company is correct, climate change isn’t the only rough ride ahead over the next decade for regional and national economies.

“The next several years will take us on a roller-coaster ride featuring fast-paced innovation and technological breakthroughs that force us to recalibrate our understanding of [generative artificial intelligence’s] impact on our work and our lives,” the team of researchers from McKinsey writes in The economic potential of generative AI: the next productivity frontier.

Policymakers, higher education leaders, TBED practitioners, and urban planners would be wise to take notice: no aspect of regional innovation policy portfolios is likely to be untouched.

• In many sectors, positions requiring creative professionals and knowledge workers, the key labor components of technology-based economic development (TBED), are most at risk.
• Additionally, the McKinsey researchers note, “generative AI increases the potential for [disruption by] technical automation most in occupations requiring higher degrees of educational attainment.”
• The need for, and nature of, research parks, innovation districts, and downtown/suburban business clusters will see traditional uses changed (beyond that already induced by the pandemic and advanced work-from-home capabilities)
• The competitiveness of many small and midsized companies will be challenged if they are unable to keep up with the rapid technological advances seen in generative AI and the financing to implement the necessary changes in equipment and workforce training. This gap potentially increases the risk of further market concentration in many sectors, further squeezing profit margins for smaller operations.

Also like climate-induced economic and social upheaval, the pace for disruption from generative AI is also quickening. Comparing their new analysis to similar research McKinsey published in 2018, the researchers have accelerated the dates—by decades in some cases—for significant AI adoption and productivity milestones affecting 11 key technological capabilities currently dominated by knowledge workers.

Viewed through traditional economic measures—GDP growth, increased sales, and productivity gains—generative AI will be a tremendous boon for business and industry. In the new report, McKinsey has increased its 2018 estimated impact of AI on global economic activity from $13 trillion to as much as $17.7 trillion. Furthermore, increased productivity among knowledge workers is expected to add $6.1 trillion to $7.9 trillion in economic gains.

Through 63 use cases, McKinsey examined AI’s potential impact across 16 business functions and 21 industry sectors. They concluded that 75% of impact will be felt in marketing and sales, R&D, software engineering, and customer operations. Sectors with the largest anticipated impact, measured by productivity gains as a percentage of total industry revenue, are: high tech; finance; pharma and medical products; education; and telecommunications. The 68-page document includes several examples of how AI might be deployed to improve productivity in these areas.

Given that McKinsey predicts AI’s impact on global sales to be only 3 to 5%, policymakers and TBED practitioners should note underlying those anticipated productivity gains will be reductions in higher-wage knowledge-based jobs, positions replaced or made redundant by the improved efficiencies from the suite of AI technologies.

For example, the report discusses how much time generative AI could save workers in the functions the new technology will most likely affect. With the introduction of generative AI, and its ability to understand and generate natural language, the total percentage of work hours that could theoretically be automated using pre-generative AI has increased from about 50 to 60–70%. In other words, one person assisted by AI could do the work of two people without AI.

McKinsey & Company’s paper includes a few caveats. The authors warn that realizing the full potential of the technology will take time, and there will be challenges along the way. These challenges include managing the risks inherent in generative AI, determining what new skills and capabilities the workforce will need, and rethinking core business processes such as retraining and developing new skills.

And the authors caution, "Given the speed of generative AI’s deployment so far, the need to accelerate digital transformation and re-skill labor forces is great.”

The fourth and final section of McKinsey’s report exploring “considerations for business and society” raises more questions than it offers answers. The researchers completely punt on any labor and economic development policy recommendations.