- First-of-its-kind Workforce Intelligence Index spanning a decade shows 75 percent of Fortune 500 tech companies face untapped upskilling opportunity
- Index features 1,500 companies across technology, healthcare, retail, consumer goods and more
- Engineering roles hold highest potential for AI and human collaboration, with leading firms averaging 70 percent plus reskilling capacity
As enterprises race to harness artificial intelligence, layoffs have become a common response to uncertainty about the future of work. New research shows that this approach is shortsighted and needs nuance. TechWolf, a workforce intelligence company that helps enterprises navigate the AI transformation and build resilient, future-ready workforces for the AI era, today released its Workforce Intelligence Index, based on public vacancy data from more than two billion global job postings collected between 2015 and 2025.* The Index shows that only 18 percent of tasks are fully automatable by AI. According to the data, the majority (62 percent) of tasks will remain fully human, while about 38 percent will have significant disruption by AI (combined automatable and augmentable tasks). Within the Fortune 500 technology sector, 75 percent of the workforce has untapped potential to upskill or reskill.
The Economic Case for Reskilling Over Layoffs
Research has shown that widespread layoffs at major firms can erode innovation, morale, and long-term performance. In contrast, the Society for Human Resource Management notes that upskilling is not a perk but a strategic investment that improves retention and strengthens productivity. “Layoffs may please investors for a quarter, but they weaken companies for years,” said Mikaël Wornoo, Founder and President of TechWolf. “The smarter move is reskilling. It keeps knowledge inside the business, strengthens culture, and delivers sustainable growth in the AI era.”
AI’s Impact on the Workforce: Opportunity, Not Just Risk
While headlines focus on job losses, TechWolf’s Index provides a more balanced picture. Layoffs can yield short-term savings but often weaken companies over time through the loss of expertise, higher rehiring costs, and lower morale. According to SHRM’s Q1 2025 Civility Index, employees at companies undergoing layoffs reported committing more acts of incivility (67 percent) compared to those companies not undergoing such changes. Companies actually have real economic interests in retaining their talent. However, in the past, they did not have the proper tools or reliable data to dynamically shape their workforces for the transformation taking place at the time, often resulting in layoffs. Today, advanced technology provides valuable insights into where and how businesses can invest in reskilling, upskilling, and strategic workforce planning, ultimately avoiding expensive layoffs. This creates an opportunity for businesses to be better positioned to capture productivity gains, retain critical knowledge, and strengthen their competitiveness.
Engineering Roles at the Center of AI Transformation
Engineering jobs are often cited as being most vulnerable to automation, with AI-assisted “vibe coding” and large language model tooling raising concerns that software engineers may be replaced. TechWolf’s Index shows a different, more nuanced reality. These roles hold some of the highest potential for augmentation rather than elimination, as AI changes how engineering work is performed rather than making it redundant.
Leading Fortune 500 tech companies, including Microsoft at 86 percent, IBM at 85 percent, Dell at 79 percent, Apple at 75 percent, Cisco at 70 percent, and Qualcomm at 71 percent, all have more than 70 percent upskilling potential within their workforces. This signals that engineers are not disappearing. Instead, they are shifting into AI-augmented roles that accelerate product velocity, improve code quality, and free capacity for higher-value architecture and innovation. The reality of how engineering professionals use AI may be more nuanced than is often described.
Wornoo continued, “It’s clear that AI causes a significant workforce transformation at high speed. However, a thorough assessment of AI readiness opportunities and insights provides C-level leaders with a proactive, strategic way to prepare for the next wave of jobs and get ahead of reshaping their workforces in a way that propels employees to lean into their creativity, judgment, and expertise.”
For business leaders, cutting engineers in the name of automation is shortsighted. The smarter strategy is reskilling engineers to master AI-driven development tools, ensuring companies keep their most valuable technical talent at the center of transformation.
Intra-Sector and Cross-Sector Views of AI Readiness
The Workforce Intelligence Index encompasses 1,500 public companies across technology, healthcare, consumer goods, and retail, revealing that every sector, as well as companies within the same sector, is facing workforce transformation — but with varying opportunities.
- Healthcare: AI can enhance diagnostics, streamline clinical workflows, and reduce administrative burden. The greater opportunity lies in upskilling frontline staff to work alongside AI-driven tools, improving care delivery while addressing talent shortages. TechWolf’s data shows that 62 percent of healthcare companies require upskilling, 67 percent benefit from the combination of human skills and AI, and 33 percent face significant AI disruption. TechWolf’s Index notes that, for example, Pfizer’s Supply Chain Management shows a greater AI opportunity compared to its peers. In contrast, Johnson & Johnson’s Sales show a less favorable AI opportunity compared to industry peer averages.
- Retail and Consumer Goods: Automation can manage inventory, logistics, and repetitive operational tasks, freeing employees to focus on customer engagement and experience. Companies that reskill staff for data-driven decision-making are best positioned to capture market share. TechWolf’s data shows that 68 percent of retail and consumer goods companies require upskilling, 69 percent benefit from the combination of human skills and AI, and 31 percent face significant AI disruption. TechWolf’s Index highlights that, for example, Burberry’s Production department offers a greater AI opportunity compared to its industry peers, whereas Adidas has more AI opportunities in the Software Development department.
- Technology: Engineers and developers are shifting into AI-augmented roles that demand new skills in orchestration, oversight, and integration — making reskilling the difference between falling behind and leading. TechWolf’s data shows that 75 percent of technology companies require upskilling, 55 percent benefit from human skills and AI in partnership, and 45 percent have significant AI disruption. For example, TechWolf’s Index indicates that Cisco’s Marketing function shows a greater AI opportunity compared to industry peers and IBM’s Data Science and Analytics department shows greater room for AI-driven efficiency compared to the average of industry peers.
These findings illustrate how AI’s impact on work is not one-size-fits-all. Instead, it is reshaping jobs in ways that reflect the realities of each industry, from the pressures facing frontline healthcare staff to the transformation of retail operations and the evolution of software engineering.
To explore the Workforce Intelligence Index in detail and to learn how TechWolf can help your company future-proof its workforce, visit the Index here.
Workforce Intelligence Index Methodology*
The Workforce Intelligence Index is based on public vacancy data from more than two billion global job postings collected between 2015 and 2025. TechWolf’s AI models break down jobs into measurable tasks and predict automation potential using the Human Agency Scale, developed at Stanford (Shao et al., 2025). By aggregating and normalizing this data, the Index benchmarks roles across industries and highlights where upskilling and reskilling can have the greatest impact.
TechWolf’s AI team has published widely on the application of language model inference to specific workforce intelligence questions, with over 100 citations of their research in peer-reviewed journal articles. The team’s open source model for job title matching (JobBERT) is one of the most popular models on Hugging Face, with over 250,000 monthly downloads.
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