Gallagher’s 2026 US Workforce Trends Report – Talent Benchmarks shows employers balancing growth ambitions against persistent turnover, constrained headcount and the accelerating adoption of AI. The findings point to a workforce strategy challenge for HR leaders: technology investment is increasing, but managers, employees and organizational trust remain critical to whether those investments deliver results.
U.S. employers are entering a period in which business growth and workforce expansion are increasingly moving in different directions.
Gallagher’s 2026 US Workforce Trends Report – Talent Benchmarks, based on responses from more than 3,700 U.S. employers, highlights the tension. While 61% of organizations expect revenue growth by 2027, only half anticipate increasing workforce headcount.
That gap is putting greater pressure on HR leaders to improve productivity, retain existing employees and determine where technology can expand workforce capacity without simply adding more people.
The report identifies retention as one of the most immediate challenges. Nearly two-thirds, or 63% of employers, reported annual turnover of at least 10% in 2025. Retention is now considered a top HR priority by 57% of respondents and a top operational priority by 39%.
That shift matters because employee turnover increasingly affects business performance rather than remaining an isolated HR metric.
When teams are already operating with constrained staffing, replacing employees creates additional recruiting costs while placing more workload on remaining employees. It can also slow execution at a time when organizations are attempting to introduce new technologies and redesign work.
Gallagher’s findings suggest employers are therefore looking at workforce effectiveness from multiple directions: manager performance, employee engagement, retention, workload and technology adoption.
Employee feedback is becoming one component of that strategy. More than half of employers, 57%, conducted an employee engagement survey in 2024 or later. But collecting feedback is proving easier than translating it into organizational change.
That distinction is increasingly important for HR technology platforms.
Employee listening systems, engagement surveys and people analytics can generate large quantities of workforce data. The challenge is turning those signals into decisions that managers and employees can see reflected in workloads, goals, career opportunities and working practices.
Gallagher identifies manager effectiveness as one of the strongest drivers of employee engagement, with organizations emphasizing clearer goal-setting, transparent communication and more timely feedback.
The finding aligns with a broader challenge emerging around AI.
Gallagher reports that 71% of employers have either fully operationalized AI or implemented it in parts of their businesses, while 73% expect AI adoption within HR to increase by 2028.
Yet adoption does not automatically translate into workforce value.
Gartner reported in March 2026 that only 45% of managers said AI had improved their teams’ work as much as they expected. Gartner’s research also found that just 14% of managers surveyed said they faced no challenges in driving effective AI use across their teams.
That puts managers in a strategically important position.
HR departments can deploy AI-enabled recruiting, talent management, workforce analytics and employee-experience tools, but managers ultimately determine how much of that technology becomes part of day-to-day work.
Gallagher’s findings point toward the same conclusion from a different angle: technology needs to be accompanied by communication, practical support and effective management.
Trust may be the biggest obstacle.
Nearly 29% of Gallagher’s respondents cited eroding employee trust as a barrier to AI adoption. Data privacy and security were an even larger concern, cited by 72% of employers.
The trust problem is particularly significant for HR because employee data is among the most sensitive information organizations process. AI systems that analyze performance, recommend candidates, personalize learning or influence workforce decisions can create questions about how employee information is being used and whether automated recommendations are fair.
Gartner has similarly identified employee trust as a critical condition for successful AI adoption. Its 2026 research warns that unhealthy human-AI interactions can impede trust and AI adoption, while its guidance for HR emphasizes transparency around AI-driven role changes, fairness and responsible data use.
For HR technology vendors, that creates a market requirement that goes beyond adding generative AI to existing products.
Recruiting platforms need explainable recommendations. Employee listening systems need clear data-use policies. Talent management platforms need governance around AI-generated assessments. Learning platforms need to show employees how AI supports development rather than simply automating decisions about them.
The report’s AI return-on-investment findings reinforce the challenge. Nearly three-quarters of organizations that have implemented AI are measuring ROI, but employers expect an average of 28 months before AI returns outweigh implementation costs.
That timeframe puts pressure on HR and business leaders to define value more broadly than immediate cost reduction.
If AI saves employees time but managers do not know how that time should be redeployed, the organization may not capture much additional value. If automation reduces administrative work but increases employee uncertainty, adoption can suffer. And if AI improves individual productivity while weakening collaboration or trust, the overall workforce impact may be difficult to sustain.
Gartner’s recent research points to the same issue. Its 2026 analysis found that employees proficient with AI across multiple use cases were twice as likely to report high productivity and 2.3 times more likely to deliver high-quality work. At the same time, Gartner found that many organizations are still failing to provide sufficient guidance on how employees should use time saved by AI.
This is where workforce technology and workforce strategy increasingly converge.
HR leaders need systems that can connect engagement data with turnover risk, skills intelligence with workforce planning, and AI adoption with employee sentiment. A standalone engagement survey or AI productivity dashboard provides only part of the picture.
The longer-term opportunity is an integrated workforce intelligence layer that helps organizations understand where capacity is constrained, why employees leave, which skills are changing and where AI can augment work without undermining trust.
The pressure is especially acute for early-career workers. Gartner reported in July 2026 that 22% of CHROs said at least one business leader at their organization had stopped hiring for some entry-level roles because of AI automation. Gartner argued that organizations should instead redesign early-career roles around more complex, higher-value work and provide stronger development structures.
That reinforces a broader message from Gallagher’s report: workforce technology cannot be separated from workforce design.
Employers are trying to grow without proportionally expanding headcount. AI may help increase capacity, but its success will depend on whether organizations redesign jobs, equip managers, protect employee trust and create realistic workloads.
For HR teams, the emerging priority is therefore not simply adopting more technology.
It is building an operating model in which people, managers, data and AI work together.
Gallagher’s workforce benchmarks suggest that employers still have significant work to do on the fundamentals—retention, engagement and management effectiveness—while simultaneously preparing for a much more AI-intensive workplace.
The organizations best positioned for the next phase of workforce transformation may be those that treat these issues as interconnected rather than separate HR initiatives.
Market Landscape
Gallagher’s findings reflect a broader transition in enterprise HR technology from automation toward workforce orchestration.
AI is increasingly embedded across recruiting, employee experience, learning, talent management and workforce analytics. But adoption alone is not proving sufficient. Gartner’s 2026 research says organizations need managers to help employees integrate AI effectively, while employee trust and workforce enablement remain major adoption factors.
This is creating demand for HR platforms that combine AI with:
- Workforce planning and capacity analytics
- Employee listening and engagement measurement
- Skills intelligence and talent marketplaces
- Manager enablement
- AI governance and risk controls
- Learning, reskilling and career mobility
- Predictive retention analytics
The competitive opportunity is increasingly shifting toward platforms that can connect these functions rather than optimize them independently.
For HR leaders, the question is also changing from “What AI tool should we deploy?” to “How should work, skills and management change because of AI?”
Top Insights
- Workforce capacity is becoming a strategic constraint, with 61% of employers expecting revenue growth but only 50% anticipating higher headcount.
- Retention is now a business issue, as 63% of employers reported annual turnover of at least 10% in 2025.
- AI adoption is accelerating in HR, with 73% of employers expecting increased HR AI adoption through 2028.
- Employee trust remains critical, particularly as AI systems increasingly influence workforce decisions and analyze sensitive employee data.
- Managers are becoming the AI adoption layer, translating enterprise technology investments into practical changes in everyday work.
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