Generative AI continues to reshape jobs and employment across industries and around the world.
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Generative AI is reshaping work and employment, according to recent research findings from three different sources: technology companies, consulting think tanks, and academic research teams. Although their perspectives differ, their conclusions are largely consistent and consistent with anecdotal comments we’ve heard recently from business leaders, with implications for governance and leadership at the board and C-suite level.
3 new studies
Microsoft’s 2026 Work Trend Index Annual Report surveyed 20,000 AI workers across 10 countries and analyzed trillions of anonymized Microsoft 365 productivity signals to identify characteristics of individuals and organizations that are effective at adopting AI.
In “AI Will Reshape More Jobs than It Replaces,” BCG’s Henderson Institute applied a structured microeconomic framework and used detailed occupational data to assess how AI will reshape employment outcomes.
What about Backfire AI? In “Deploying AI in the Workplace,” forthcoming in Management Science, academic researchers Di Yuan (Auburn University and University of Pittsburgh), Manmohan Aseri (University of Maryland), and Narayan Ramasubbu (University of Pittsburgh) develop policy recommendations to maximize the benefits of AI adoption by analyzing the impact of employee competition on AI adoption.
5 Implications of AI Deployment
The study provides a wide range of findings, including five common themes that influence companies’ approaches to AI adoption.
- AI will reimagine more jobs than it will replace. Although this is the title of the BCG study, two other studies make similar points. BCG predicts that 50% to 55% of U.S. jobs will be reshaped by AI in the next two to three years. Additionally, another 10% to 15% of U.S. jobs could be eliminated within five years or more. While significant, this projected level of job losses is lower than many of the highly publicized forecasts in recent months. Additionally, Microsoft’s research shows that some jobs will become obsolete, new jobs will be created, and others will change. The company cited LinkedIn’s 2026 Labor Report, which found that more than 1.3 million AI-related jobs were created in the past two years. This academic study discusses how roles are changing as AI becomes more integrated into daily work, and is consistent with BCG’s research on turnover.
- AI will change the way people add value. This is an important point common to all three studies. Microsoft found that the most important human skills in AI deployment are reviewing AI output and critical thinking, noting that “as the scalability of execution increases, the premium on judgment increases.” BCG reached a similar conclusion, saying that roles that rely on emotional and social cues, trust, persuasion, and nuanced interpretation of situational judgment are more likely to be enhanced by AI than by automation. The academic study found that jobs that require high levels of intangible skills and tacit knowledge outperform jobs that require technical skills when it comes to successful AI implementation. We also showed that the most successful roles combine technical and intangible skills. All three studies suggest that the jobs most likely to be replaced by AI are those that involve highly repeatable tasks. Those least likely to be replaced require a high degree of judgment and situational awareness.
- AI will change the roles of managers and leaders. Microsoft found that only 16% of organizations are considered “frontier organizations” where both AI capabilities and AI readiness are strong and mutually reinforcing. An additional 16% of organizations are “stuck” due to both low individual AI practices and low organizational AI conditions, and 10% are “agency blocked” with advanced AI practices but low organizational conditions. Misalignment often exists at the top and is reinforced by leaders. Only 26% of AI users say their leadership has clear and consistent alignment on AI. The study concludes that “every leader’s job at this point is to make change stick,” highlighting the need for managers to be able to manage not only people but also agents and agent workflows. It also highlights the importance of ensuring quality control of AI output and supporting effective judgment and critical thinking across the organization. BCG’s research highlights the importance of changing the mindset of organizations as work is reshaped, focusing on acquiring and training the necessary skills, and placing the right people in the right roles as work evolves. Leaders must also support redesigned roles that require greater expertise, oversight, and accountability, while reinforcing the importance of subject matter knowledge and sound judgment. This academic research suggests that managers need to rethink how work is structured and managed to optimize AI adoption.
- Culture is key to successful AI implementation. Microsoft found that organizational factors such as culture, manager support, and human resources practices account for more than twice the influence of individual mindsets and behaviors (67% vs. 32%). This includes treating AI as a competitive advantage, encouraging experimentation, and operating it as a self-reinforcing learning system where AI insights are shared and incorporated into operations. BCG research highlights the importance of aligning organizations on upskilling and reskilling, shaping new career paths, and accelerating innovation by fostering new levels of human-AI collaboration. It also emphasizes the importance of clear leadership communication that encourages employees to embrace change. This academic research suggests a structured approach to culture and workforce design, shifting recruitment toward judgment-based skills while preserving technical competency, supporting continuous AI learning, and tailoring the use of AI to each employee’s strengths.
- Recognition and rewards for the use of AI need to change. Microsoft reports that only 13% of AI users find reinvention rewarding, even if they don’t see immediate results. Conversely, leaders of “frontier” organizations claim to always encourage and reward reinvention. BCG emphasizes the need for leaders to rethink performance measurement as they redesign workflows and capture new sources of value. This suggests the relevance of new domain-specific KPIs that link productivity gains to tangible outcomes, such as increased revenue per full-time employee, more products shipped, and stronger customer impact. This academic research highlights the need to rethink incentives for AI users and enable the learning process without inadvertently creating counterproductive competition among users within an organization.
All three studies show that AI is changing the way work is done, automating routine tasks while increasing the need for human judgment and decision-making. Research shows that AI outcomes vary based on leadership alignment, culture, and incentives. Organizations that adjust the way they work and reward employees to create next-generation work experiences will derive more value from AI and discover greater competitive advantage.
