AI's Influence on Employment and Economies

Incisive piece by the The New York Times Steve Lohr on first of its kind research by The Burning Glass Institute and SHRM on the likely impact of Generative AI on employment. Initial analyses, including our hear at Harvard Business School Project on Managing the Future of Work have identified important a number of likely outcomes. This report drills down deep, confirming many of those hypotheses. The core of the report is The Burning Glass Institute identifying the 200 occupations that are most likely to be affected by Generative AI (GAI). It isn't going to wipe out jobs wholesale. GAI will displace some tasks altogether and speedup others. It will make people more productive-- a huge boon to the U.S. economy, given lackluster productivity growth in recent years. That productivity growth will lead to companies reducing their staff or hiring needs. The biggest impact will be on classic, white collar jobs-- marketers, business and financial analysts, supply chain managers and purchasing agents, auditors, attorneys, etc. Industries will be affected asymmetrically with professional services, banking and tech. In some industries that will be less affected, specific competitors may be more vulnerable. A retailer like Tiffany's might only restructure marginally; a retailer like Williams-Sonoma with a significant web presence much more so. So, what should executives do? One, develop a strategy. Huge value is on the table and, if your competitors get out in front of you, the consequences will be significant. Companies that slide down the learning curve faster have the prospect of gaining a significant, even insurmountable data-drive advantage. Two, start demystifying GAI for your workforce. Too many companies are holding their cards close to their vests. Left to their own imaginations, workers are increasingly likely anxious and skeptical. That will undermine future reskilling initiatives. Three, start thinking about future job design. If GAI is going to unburden many white collar workers of 40%, 50%, even 60% of their current tasks, what should they be directed to do. What upskilling or reskilling should we be undertaking? How should job descriptions change? What about incentives and metrics? Start probing these questions now, don't wait and find yourself trying to change the engines on the plane while you're flying at 30,000 ft. Four, use tools like this to evaluate your organization's current design. How much disruption is coming your way? How can you start preparing for it now, such as reining in hiring for positions that are likely to be substantially transformed in the next year or two. Five, revisit your talent pipeline strategies. Where will the talent you need in the GAI world come from? Seems implausible that your talent suppliers from the pre-GAI world will all be perfect fits for the what's coming. #artificialintelligence #workforcetransformation #generativeai

Impressive new paper out led by A/Professor Jo-An Occhipinti (née Atkinson) I was glad to contribute. "Work is fundamental to societal prosperity and mental health, providing financial security, a sense of identity and purpose, and social integration. Job insecurity, underemployment and unemployment are well-documented risk factors for mental health issues and suicide. The emergence of generative artificial intelligence (AI) has catalysed debate on job displacement and its corollary impacts on individual and social wellbeing. Some argue that many new jobs and industries will emerge to offset the displacement, while others foresee a widespread decoupling of economic productivity from human input threatening jobs on an unprecedented scale. This study explores the conditions under which both may be true and examines the potential for a self-reinforcing cycle of recessionary pressures that would necessitate sustained government intervention to maintain job security and economic stability. A system dynamics model was developed to undertake ex ante analysis of the effect of AI-capital deepening on labour underutilisation and demand in the economy using Australian data as a case study. Results indicate that even a moderate increase in the AI-capital-to-labour ratio could increase labour underutilisation to double its current level, decrease per capita disposable income by 26% (95% interval, 20.6–31.8%), and decrease the consumption index by 21% (95% interval, 13.6–28.3%) by mid-2050. To prevent a reduction in per capita disposable income due to the estimated increase in underutilization, at least a 10.8-fold increase in the new job creation rate would be necessary. Results demonstrate the feasibility of an AI-capital-to-labour ratio threshold beyond which even high rates of new job creation cannot prevent declines in consumption. The precise threshold will vary across economies, emphasizing the urgent need for empirical research tailored to specific contexts. This study underscores the need for cross-sectoral government measures to ensure a smooth transition to an AI-dominated economy to safeguard the Mental Wealth of nations." https://lnkd.in/gq_ZjWDs

The PwC 2024 Global AI Jobs Barometer report provides a comprehensive analysis of the future of work, where Artificial Intelligence (AI) is poised to play a significant role. By examining a vast dataset of job postings, the report identifies trends in job creation and displacement across various sectors. The findings suggest a surge in productivity, postulating a potential labor productivity increase by 8-10% within three years (2027). However, this may be accompanied by evolution of job roles and re-imagined functions that underpins those roles pretty comprehensively. On the other hand, the report also forecasts new job creation at a rate of 5-7% within the same timeframe. These new positions will likely be in areas requiring collaboration with AI and human-machine interaction. The report highlights the imperative need for reskilling and upskilling initiatives, as approximately 20-25% of workers may require new skills within three years to adapt to the transforming job market demands of the AI-driven economy. This underscores the critical need for educational systems and training programs to evolve rapidly, equipping workers with the necessary skills to thrive in this new environment. The report suggests a continued trend of automation, with a growing demand for skills complementary to AI capabilities. The future of work will not be a competition between humans and AI, but rather a collaborative effort between the two to achieve greater efficiency and innovation. By understanding and leveraging AI's capabilities, workers can position themselves for success in the coming years. Extrapolating the trend lines beyond the report's three-year scope, we can anticipate a significant growth trajectory, potentially yielding labor productivity increases of 19.4% and 43.1% in five and ten years, respectively, as modeled by the exponential growth equation. In conclusion, AI is poised to drive a substantial increase in labor productivity. The key takeaway is that the future of work requires embracing change and preparing for a world where humans and AI collaborate. By equipping the workforce with the necessary skills to thrive in this AI-driven economy, fostering a culture of lifelong learning, and implementing robust reskilling programs, we can navigate the challenges and create a future that benefits all. #pwc #jobs #ai

Generative AI Leads to Decline in Hiring for Exposed Jobs The introduction of ChatGPT in late 2022 sparked extensive research into the potential impact of generative AI on the labor market. With the increasing adoption of AI, there's an anticipation of significant workforce reductions in jobs highly susceptible to AI automation. Various researchers have attempted to identify which occupations are more vulnerable to AI: https://lnkd.in/gbmKT_Cz. It's important to note that workforce reductions could entail not just layoffs but also a decrease in hiring rates. Now, more than a year after ChatGPT's launch, we have sufficient data to begin examining whether there has been a reduction in hiring from 2022 to 2023 for jobs with high AI exposure compared to others. This is not a prediction, but an analysis of recent data. The main finding is that occupations with higher exposure to AI indeed experienced a greater decrease in online job postings between 2022 and 2023. However, the relationship between AI exposure and job posting declines is not straightforward. A notable reduction in job postings was only observed in the 40 percent of occupations most exposed to AI. In collaboration with Kimberly Kreiss, we conducted the following analysis: We performed a regression analysis across detailed occupations, with the percentage change in online job postings from 2022 to 2023 serving as the dependent variable. We controlled for industry variations to account for shifts in worker demand. The primary explanatory variable was the level of AI exposure. We used nine decile dummy variables to represent the levels of AI exposure, comparing their coefficients relative to the first decile. The outcomes of the decile coefficients are depicted in the chart below. #ai #generativeai #tech #recruitment #futureofwork

AI is stealing jobs - or is it? The World Economic Forum analyzed over 19,000 tasks across 867 jobs to assess their exposure to automation or augmentation by AI language models. The findings show that rather than simply replacing humans, these models will likely transform many existing roles. Roles with the highest potential for automation: ↳ clerks, ↳ analysts, ↳ telemarketers and ↳ tellers. Meanwhile, healthcare and personal service professions have lower exposure overall. Importantly, roles with augmentation potential largely align with anticipated growth areas like AI specialists, data analysts and technologists. This suggests workforce transformation, not just job loss. The rapid AI advancement will create new roles as well (which is already happening), such as AI prompt engineers, ethics monitors and data curators. With 23% of jobs predicted to change in 5 years ... By understanding the nuanced impact on specific jobs and tasks, we can re-skill and up-skill to complement rather than be replaced by these powerful technologies. What's your take on this? If you've enjoyed this post, you'll love my newsletter! ✨ Subscribe: https://lnkd.in/gpzZHYYf ✨ Infographic Credit: Visual Capitalist

In an era marked by breakneck technological advancement, the emergence of generative AI represents a watershed moment, particularly in how we perceive labor and human-based problem-solving. This change is more than technological; it signifies a fundamental shift in how we’ll need to think about our economic and societal structures. I’ll explain… Knowledge workers have long been the kings of our information-based economy, engaging in the assimilation of information, idea evaluation, and decision implementation. However, the current trajectory of AI is painting a different future. We're transitioning from singular AI models to integrated agentic systems capable of human-level complex problem-solving. Which is why AI skepticism is misguided. The prevalent skepticism towards today’s AI models focuses on their limitations as statistical tools, dependent on their training data. While this critique is apt for individual models, it overlooks a crucial aspect- the collective potential of these systems working in concert. Around the world, people are utilizing powerful AI to decompose human workflows and reimagine them with as little human involvement as possible- think AutoGen and mixture-of-experts paradigms. This approach isn't about creating AGI (a common strawman argument), but about orchestrating collections of AI models, which are already capable of outperforming humans in many tasks...to create products. And they're not just limited to automating manual tasks. This also extend to intellectual functions, possibly representing the last significant labor-saving device humanity will invent. This development is a major cause for concern and the discourse by AI skeptics centered on the weaknesses of individual models, is leading to a dangerous underestimation of the impact that AI will have. The implications of an AI-driven world are significant- a potential devaluation of human labor in knowledge-based professions, and a reshaping of our labor market and economy. As we witness AI systems performing tasks with greater efficiency and accuracy than humans, an important question emerges: what happens to human labor and intellect in a world where machines can perform complex tasks, previously the domain of skilled professionals? Make no mistake, the rise of AI as a multi-agent problem-solving system presents a huge challenge for society. It will force us to reconsider the monetary value of human intellect and labor in a world increasingly dominated by machine efficiency. That's why the focus shouldn't be solely on the limitations of individual AI models, but on the collective capabilities of these systems and their impact on our societal and economic structures. The fact of the matter is AI has been unleashed and we must be clear-eyed about an AI-driven future which is approaching faster than any of us are prepared for. Don't be swayed by AI skeptics; it's not hype. #ai #artificialintelliegence

🚀 The AI Revolution and Upskilling: Navigating the Future of Work A recent report by the International Monetary Fund (IMF) brings to light a pressing issue in today’s rapidly evolving job landscape. According to their analysis, a staggering 40% of jobs globally are at risk of being influenced by artificial intelligence (AI). This statistic rises to 60% in advanced economies. This seismic shift could exacerbate existing inequalities, benefiting some while leaving others facing job loss or reduced wages. 🔍 Understanding the Impact In advanced economies, the integration of AI is a double-edged sword. While it can enhance efficiency and create new opportunities, it also poses significant challenges for those whose jobs are susceptible to automation. The disparity in impact raises concerns about widening the gap in income and job security. 🌉 Bridging the Gap: Upskilling for the AI Era To navigate this transition, upskilling becomes not just beneficial, but essential. Here are key areas to focus on: 1. Tech Savvy Skills: Understanding the basics of AI and machine learning can make you an invaluable asset. This doesn’t mean you need to be a tech wizard, but having a grasp of how these technologies work in your field can give you an edge. 2. Emotional Intelligence: AI is far from replicating human empathy and emotional intelligence. Skills like communication, empathy, and leadership will become more valuable as they complement AI’s analytical capabilities. 3. Creative and Critical Thinking: AI excels in handling routine tasks, but creative problem-solving and innovation remain distinctly human traits. Developing these skills can make you indispensable in an AI-dominated job market. 4. Lifelong Learning: The only constant in the AI era is change. Adopting a mindset of continuous learning and adaptability is crucial. 5. Cross-disciplinary Knowledge: Combining knowledge from different fields can lead to innovative solutions that AI alone cannot achieve. Cultivating diverse knowledge and perspectives is key. 🌐 In Conclusion The rise of AI presents challenges but also opportunities. By focusing on upskilling and adapting, we can not only survive but thrive in this new era. Let’s embrace this change and turn it into an avenue for personal and professional growth! Link in comments. #AI #FutureOfWork #Upskilling #CareerDevelopment #Innovation

🚀 How past tech disruptions can help inform the economic impact of AI via EY 💻 In recent years, no technology has created more excitement than generative artificial intelligence (#GenAI), but that excitement has been tempered by uncertainty and concerns among executives, policymakers and other stakeholders. 🤖 GenAI systems are so complex and developing so rapidly that it is difficult to predict how they will impact organizations, economies, and societies. In this first article of the series, my EY-Parthenon colleague Lydia Boussour uses history as a guide to shed light on the potential future impact of GenAI and the economic opportunities and challenges that it may bring. 📈 Three key lessons from past episodes of rapid technological change can help inform how AI may affect the #economy: 1️⃣ Significant productivity boost: GenAI will likely lead to a significant acceleration in productivity growth and raise living standards like prior general-purpose technologies. By examining the 1990s IT-driven acceleration in productivity growth, we estimate that GenAI could lift productivity growth by 20% to 50% in the coming decade. However, it will likely fall short of the doubling or tripling of productivity growth resulting from the Industrial Revolution or adoption of electricity. 2️⃣ Potentially delayed impact: The productivity boost from GenAI will likely occur with a lag, but the faster speed of technological diffusion and adoption could mean that the boost to economic activity is felt in the next three to five years versus multiple decades for the steam engine and 10 years for the computer age. 3️⃣ Nuanced job reshuffling: AI technologies are poised to cause significant labor market disruptions by automating some tasks and displacing workers, but it will also create new types of jobs and functions within roles across many sectors of the economy that will help offset AI-related job losses. Read the full article here: https://lnkd.in/d9ae9HRi

What will be the impact of Large Language Models on employment? Speaker: Daniel Rock Summary ======== Daniel discusses the findings of their paper, Generative Pre-trained Transformers are General Purpose Technologies (GPTs are GPTs), and the broader implications of AI systems in the workforce. They address the question of whether AI systems will negatively impact employment and explore the idea that large language models, such as Generative Pre-trained Transformers (GPT), can significantly transform the economy. The speaker takes an optimistic stance, stating that they do not believe there will be massive job displacement due to these technologies. They observe a shift towards non-routine cognitive tasks and introduce a new approach to evaluating the exposure of tasks to large language models. Topics ===== ⃝ Impact of AI systems on employment * The speaker believes that there will not be massive job displacement due to AI systems. * There is a shift towards non-routine cognitive tasks. * A new approach to evaluating the exposure of tasks to large language models is introduced. ⃝ Evaluation of exposure to large language models * The speaker and their team used the O*NET database to evaluate the exposure of tasks. * Tasks were categorized into ‘No Exposure (E0)’, ‘Exposure with LLM (E1)’, and ‘Exposure with LLM + other software (E2)’. * Human annotators provided “opinions” about the exposure level of various tasks within Jobs. The results were compared about GPT4 predictions and used as the baseline of the evaluation. There is agreement between humans and GPT-4 in evaluating tasks at the occupation level. * Approximately 80% of workers may have around 10% of their tasks exposed to large language models. ⃝ Impact of automation on jobs * Certain types of workers are more exposed to automation assuming no significant change in the subset of tasks associated with their job and not enough resources for reskiling / upskilling. * Automation can potentially improve job satisfaction by removing mundane tasks and shifting cognitive energy to more creative and demanding ones. * Job descriptions, list of subtasks in a job, are dynamic and creating the right infrastructure is important for safe and responsible adoption of technology. * The current study focuses on task level assessment of exposure and future work could explore system level exposure by including more high level dependencies. * It is difficult to advice on the necessary policy solutions but the importance of evaluation and quality control is clear. RECORDING: https://lnkd.in/gU58tdmR

AI exposure and impact on Jobs: Good & Bad - We need better preparation and execution. Just watched a thought-provoking video by Gita Gopinath, the Deputy Managing Director of the IMF, speaking from Davos at the World Economic Forum on the impact of Artificial Intelligence on the global job market. The IMF's recent research indicates a staggering 40% of jobs worldwide are now exposed to AI, with this figure soaring to 60% in the US. However, for lower-income countries, it dips to 26%. This exposure, as Gita aptly points out, is a double-edged sword. On the bright side, AI promises to boost worker productivity, a leap forward in efficiency and capability. But, it also poses a significant risk of displacing workers. As an HR tech entrepreneur and an evangelist for AI Workforce Transformation, I see this as a crucial juncture. The development and application of AI aren't set in stone. It's a path we're carving out, day by day. Gita's emphasis on the need for global cooperation and policy-making in this domain resonates deeply with me. AI is borderless, and so should be our approach in harnessing its potential while safeguarding our workforce especially in developing countries. We need strategies that not only bring AI's capabilities but also ensure that this technological revolution benefits humanity as a whole. This calls for a transformation in how we view and prepare our workforce. Upskilling and reskilling should be at the forefront of our HR strategies. We must create an ecosystem where humans and AI collaborate, enhancing each other's strengths. At iMocha & Revature this is our core offering to find skill gap and guiding them for #upskilling & #reskilling to create Future Ready Workforce and elevate their career progress using #Skillsintelligence I take this as an opportunity to urge all Founders, CXOs, HR Leaders in shaping a future where AI is not just a disruptor but a powerful ally in driving human potential and prosperity. Amit D Mishra Sujit Karpe Dave Ghosh Maansi Sanghi Vishal Pradhan Vishal Madan Ashwin Bharath Vidya Shankaran Anurag Gupta Vicente Pava #AIWorkforceTransformation #FutureOfWork #HumanAIcollaboration #HRtech #Davos2024 #GitaGopinath