Standing on the shoulders of robots: Can AI-powered productivity solve the talent crisis?
Even in a volatile economic climate with stagnant productivity gains, the intensifying talent crisis is a predictable challenge to growth.
Artificial intelligence (AI) can help mitigate the effects of unfavorable demographics, skills mismatches, and changing workforce expectations on the global economy. But with some markets at greater risk than others, the impact of AI may vary throughout the world. The issue facing every leader today is how to mitigate the risks and turn the potential gains from AI into a sustainable advantage for their organizations.
Generative AI has emerged as an ally in modern workplaces — but many view it as a threat or simply do not know enough about it to plan effectively. From finance to healthcare, AI's ability to swiftly process vast amounts of data, learn from patterns, and execute repetitive tasks can significantly reduce the burden of routine responsibilities on workers. It promises to not only augment human effort and make work more efficient, but also to amplify human intelligence — expanding our capabilities to take on new jobs and unlock value.
In our latest Global Talent Trends report, 41% of executives think most of AI’s value will come through augmentation and efficiency gains in 2024 (30% expect greater returns from amplified intelligence). Employees, however, see things differently. Oliver Wyman Forum reports that over half of the workforce now uses generative AI, but 39% of employees (especially blue-collar workers) feel their productivity is the same or worse today because of it. Either way, AI will impact many jobs — directly or indirectly.
The good news is that various AI and automation capabilities are combining to increase productivity and innovation, with AI enabling new avenues of value creation. The issues before us now are how to accelerate the potential of generative AI and how to identify which industries and economies might benefit the most.
We have only just begun to gauge the full impact of generative AI in the workplace, but early studies tend to show a 10% to 20% leap in productivity. Call centers are heralding a boost of up to 14% and we expect similar gains in other functions, such as marketing, finance and HR, that are well-positioned to embrace this technology.
Knowledge workers will also benefit. Harvard Business School found that generative AI can help business consultants complete certain tasks 25% faster, while improving quality by 17% for above-average performers — and up to 43% for those below the average.
Ultimately, the promise of AI is not exclusive to certain functions or tools. As AI touches more business applications and work activities, its effects will be compounded and felt firm-wide — especially as this technology permeates into more senior roles.
AI versus demographic and talent headwinds
Mercer set out to explore the potential impact of generative AI on productivity and long-term economic conditions, with research and insights designed by Man Bites Dog and carried out by Oxford Analytica. We commissioned a high-level model based on GDP forecasts, demographic trends, labor statistics, and research into generative AI. Our thought experiment focused solely on the impact of AI on labor productivity, while keeping other variables such as migration and fiscal policy fixed.
First, we identified 10 key countries which are significant contributors to GDP today (and likely will be in the future). These countries cover developed markets like the UK and the US, and emerging markets such as China and India. Then we divided each market category into six industry sectors:
- Finance and insurance
- Information and technology
- Manufacturing
- Healthcare and social assistance
- Transportation and warehousing
- Hospitality and foodservice
Using historical data, we calculated the average productivity growth rates for each sector. We then divided the market categories into high-speed and low-speed performers (those in the 75th versus 25th percentiles, respectively, of compound annual growth rates ending from 2016 to 2018) to estimate year-2035 productivity growth rates.
The model predicts that as early as 2025, six out of 10 markets could already struggle to meet customer demand through labor supply alone. HR leaders cite this risk as a top concern for their firms this year, and only one in two executives globally believe their companies have the talent required to meet demand today. As demographic shifts lead to a decrease in skilled workers, all these markets may see constrained economic growth.
Based on this hypothetical scenario, we examined what role AI productivity gains could play in mitigating the impact of demographic shifts (see Figure 1). To explore this, we would need to determine the productivity gains that AI alone could deliver. If demand was truly unlimited (in other words, whatever we produced would find a buyer), then how much more productive could AI make us with a potentially limited labor supply?
AI-powered productivity potential
Figure 1: Potential impacts of generative AI on GDP forecast
Boost* to GDP forecast (with AI), via productivity gains
Category: Emerging markets
Category: Developed markets
Emerging markets = China and India
Developed markets = France, Germany, Italy, Japan, Singapore, Sweden, UK, and USA
Sources: Oxford Analytica, Mercer
Figure 2: Estimated generative AI-enabled productivity boost by sector
Finance and insurance
Information and technology
Manufacturing
Healthcare and social assistance
Transportation and warehousing
Hospitality and foodservice
Unlocking the power of AI with an enterprise experience strategy
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Strategy
- Targeting innovation hubs and trainings, globally and strategically
- Aligning digital transformation efforts across domains
- Leveraging AI-powered productivity to grow worker income and corporate profits
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Workforce
- Offering phased retirement for smoother transitions
- Upskilling workers to boost efficiency and employability
- Improving benefits programs for employee resilience
- Enhancing corporate policies to broaden talent pools
- Designing work to achieve the optimal blend of humans and AI
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Technology
- Investing more in technology research and development
- Leveraging large language models and domain-specific applications
- Protecting investments in AI during the lean times
- Upgrading to AI-compatible systems and tools
is Leader of Global HR Digital Transformation & AI, Mercer
Global Talent Advisory Leader, Mercer
Transformation Lead International