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AI Field Manual for Employers: 138 Use Cases for AI at Work

Learn all the ways HR departments are using AI — and which use cases make the easiest starting points.

  • AI Learning Curve
  • Explore AI Use Cases
  • Types of AI Use Cases
  • Methodology
  • More

Artificial intelligence is a growing priority and challenge for HR departments. More than a third of CHROs (35%) said adapting to technological advancements such as AI is a challenge for their organizations, according to the SHRM report 2026 CHRO Priorities and Perspectives, up from 29% the year before.

Smart AI adoption will set leading HR departments apart from the pack. The key is understanding which AI use cases provide the greatest value and pose the fewest risks.

How SHRM Created This List
SHRM researchers analyzed over 250 reported HR use cases for AI, condensed them into 138 archetypes, and categorized them under the 16 practice areas that characterize mature HR departments. SHRM surveyed HR professionals to determine each use case’s prevalence, as well as its perceived risks and costs.

Why Tackle the AI Learning Curve?

Many HR professionals and leaders are experimenting with AI, but skills gaps persist in HR and the broader workforce. Organizations that support AI skill-building and responsible use can maximize the utility of this technology while freeing up workers to do more creative and strategic work that aligns with business goals.

0%


Share of U.S.-based workers who rely on AI for tasks they previously completed independently.

0%


Share of senior leaders who expect AI to positively affect productivity.

0%


Share of U.S.-based workers who reported improved quality in their work as a result of AI use.

0%


Share of small organizations that will use AI in their HR function in 2026, compared to 60% of extra-large organizations.

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Many workers today are using AI as part of their work, rather than fully automating tasks, a signal that points to augmentation, not just replacement. This credential helps you pair artificial intelligence with human intelligence to shape how work gets done.

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138 Use Cases Across 4 Dimensions

This list of AI use cases is divided into four sections, aligned with the dimensions of SHRM’s HR-X Framework. These traits indicate a mature HR function and can be used to demonstrate HR’s business impact. Each section provides an overview of how HR departments are using AI right now, as well as the challenges those use cases present, organized alphabetically by HR practice area.

Functional Acceleration

An organization’s ability to maximize people and technology resources through effective strategies and efficient operations

HR Practice Areas:

  • HR Function Strategy &  Management
  • HR Technology 
Explore Use Cases
Market Discernment

An organization’s ability to understand business and labor market conditions, making it possible to both find and reward top talent

HR Practice Areas:

  • Recruiting
  • Total Rewards
Explore Use Cases
Organizational Impact

An organization’s ability to drive organizational outcomes by shaping the future of work, engaging the C-suite, ensuring compliance, and managing change

HR Practice Areas:

  • Compliance
  • C-Suite & Board Relations
  • Future of Work
  • Organizational Design & Change Management
Explore Use Cases
Talent Optimization

An organization’s ability to drive performance, engagement, and retention through innovative talent management approaches

HR Practice Areas:

  • Employee Experience
  • Inclusion & Diversity
  • Labor & Employee Relations  
  • Leadership & Manager Development
  • Learning & Development
  • Performance Management
  • Talent Analytics
  • Talent Management 
Explore Use Cases

Understanding the 4 Kinds of AI Use Cases in HR

The 138 use cases break down into four broad categories, based on HR professionals’ subjective assessment of their relative risks and costs.


icon for Low Hanging Fruit
Low-Hanging Fruit

(Low Risk/Low Cost)

These use cases are seen as relatively easy to execute with existing technology, often via mainstream general-purpose AI tools. The consequences of making a mistake in these areas are comparatively minor and more easily remedied. These are great starting points for organizations looking to make their first investment in using AI within HR.

icon for Experimental
Experimental

(High Risk/Low Cost)

These use cases are seen as easier to implement but carry significant risks if they aren’t executed properly. AI use in these areas could lead to compliance headaches, strategic blunders, or other mistakes that are harder to redress. Consider confining AI use in these areas to controlled test environments, which allows the organization to study potential future applications without creating undue risk.

icon for Strategic Bets
Strategic Bets

(Low Risk/High Cost)

These use cases are seen as harder to adopt because they rely on more specialized AI tools, require more substantial human involvement, or need a lengthy and complex training and adoption process. The risks of using these tools are relatively low, however, so some organizations may want to begin investing in these areas now to position themselves to take advantage of future advancements.

icon for Monitor
Monitor

(High Risk/High Cost)

These use cases are technically possible, but they’re seen as logistically challenging with the currently available tools and seen as presenting significant risks to the organization. Some organizations may be able to successfully perform these tasks using AI today, but most will be better off waiting for specialized tools to mature and for reliable best practices to emerge.

How Vulnerable Is Your HR Job to AI Displacement?

Assess how exposed your current HR role is to job displacement risk. Use your results to inform your professional development strategy.

Get Started

Methodology

The survey was fielded to a sample of HR professionals via SHRM’s Voice of Work Research Panel between Dec. 5 and Dec. 23, 2025. For the purposes of this study, participants had to be currently employed HR professionals. In total, 1,722 HR professionals participated in the survey. Participants represent organizations across multiple types of industries, sectors, sizes, and locations. Data is unweighted. Analyses consisted of descriptives and analysis of variance (ANOVA).

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The AI+HI Project is the event where HR leaders move from reacting to change to shaping it. Gain exclusive insights from AI pioneers, put strategy into practice through hands-on innovation labs, and leave with actionable takeaways that turn artificial intelligence into real organizational impact.

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