Artificial intelligence is reshaping workforce management, changing the skills employers require and creating new responsibilities for human resources teams, according to an analysis by Aon. Human resources is at the forefront of AI utilization, pioneering advancements that blend technology with human insight.
AI is already being deployed across recruitment, employee onboarding, compensation planning and professional development. Aon warns that organizations must balance the potential productivity benefits with investment in workforce skills, stronger governance and continued human involvement in critical decisions.
The shift is moving beyond the automation of routine administrative activities toward broader changes in how businesses organize work and manage employees.
Teams are already using AI to optimize a host of processes, including the automation of tasks like interview scheduling, onboarding and addressing employee requests. HR professionals are generating tailored reward packages, updating recommendations in real-time, managing learning paths and creating interactive skill development simulations.
Key highlights
- AI is transforming HR operations, from recruitment and onboarding to compensation planning, workforce analytics and employee development, while creating demand for new technical skills.
- Aon warns that employers must accelerate upskilling and reskilling as AI changes job responsibilities and increases competition for specialized talent.
- AI adoption introduces risks involving data privacy, algorithmic bias, compensation decisions and regulatory compliance, making governance and human oversight essential.
Aon examines how AI is transforming workforce management, creating new HR roles and increasing demand for reskilling, human oversight and data protection.
“AI may not replace HR professionals, but those with AI skills will have an advantage over those without,” said Ernest Paskey, head of Workforce Transformation Advisory at Aon. “The challenge for companies is acquiring these skills quickly.”
AI changes HR operations and workforce requirements
Human resources departments are among the business functions adopting AI to improve operational efficiency.
Organizations are using the technology to automate interview scheduling, streamline onboarding and respond to employee requests. More advanced applications include developing personalized reward packages, updating compensation recommendations, managing individual learning pathways and creating interactive training simulations.
Most companies have initially focused on improving existing processes rather than fundamentally redesigning their operating models.
Aon expects that approach to change as AI capabilities mature over the next five years, with employers increasingly exploring opportunities to reorganize entire workflows and job functions.
The transition is also altering the professional skills required within HR departments.
AI applications across human resources
| HR function | AI applications | Potential business benefits |
|---|---|---|
| Recruitment | Interview scheduling, candidate screening support, recruitment analytics | Faster hiring processes and reduced administrative work |
| Employee onboarding | Automated guidance, document processing and employee assistance | More consistent onboarding and quicker responses |
| Compensation and rewards | Pay benchmarking, reward recommendations and compensation analytics | Better-informed compensation planning |
| Learning and development | Personalized learning pathways and interactive training simulations | More targeted employee development |
| Workforce planning | Skills analysis, workforce data modeling and predictive analytics | Improved visibility into future talent requirements |
| Employee services | AI assistants handling routine HR questions and requests | Lower administrative workload and faster employee support |
| HR strategy | Scenario analysis and workflow redesign | Opportunities to improve organizational efficiency |
Alongside traditional responsibilities involving recruitment, employee relations and organizational development, HR professionals are expected to become more proficient in advanced analytics, data-driven decision-making, machine learning and statistical analysis (see How Insurers Are Reinvent Workplace HR Strategies).
New positions are emerging, including prompt engineers responsible for designing and testing instructions for AI systems.
Other potential roles include AI Ethics Leaders, who oversee responsible technology adoption, and HR GPT Designers, who develop customized AI agents for workforce management.
These positions reflect the increasing integration of technical and human capabilities within HR operations.
Aon expects employees to work more frequently alongside AI systems in a digital labor model, where automated tools perform certain activities while people retain responsibility for judgment, supervision and complex interpersonal interactions.
While technology can aid in efficiency, employees should not rely solely on it. The core understanding of the job function is crucial, and interpersonal skills remain significant for business transactions.
Matt Chmel, chief broking officer for Cyber Solutions in North America at Aon
Critical thinking, emotional intelligence and the ability to verify AI-generated information will consequently remain important workplace capabilities.
Employers face growing pressure to reskill workers
The expansion of AI is creating expectations that employees across business functions will develop at least a basic understanding of the technology.
Aon identifies workforce development as a central challenge for employers seeking to maintain productivity and competitiveness while job requirements change.
Traditional upskilling programs, which improve employees’ existing capabilities, may be insufficient where AI fundamentally changes responsibilities or eliminates certain tasks.
Reskilling, which prepares employees for different roles, is becoming increasingly important as companies reconsider how work is distributed between people and automated systems.
However, Aon warns that many organizations are not developing workforce capabilities quickly enough to match the pace of technological change. Training programs also need to reflect differences between job functions and management responsibilities.
Emerging AI workforce roles and skills
| Role or capability | Main responsibilities | Skills required |
|---|---|---|
| Prompt engineer | Designs and tests instructions for AI systems | Prompt design, testing and evaluation |
| AI Ethics Leader | Oversees responsible AI adoption and ethical risks | Governance, regulatory awareness and risk assessment |
| HR GPT Designer | Develops customized AI agents for HR operations | AI configuration, workflow design and process knowledge |
| HR data analyst | Analyzes workforce information and produces decision support | Statistics, analytics and data interpretation |
| AI-enabled HR professional | Uses AI tools to improve HR processes | AI literacy, critical thinking and human judgment |
| Workforce transformation specialist | Supports organizational redesign and employee transitions | Change management, skills planning and business strategy |
Senior executives may require instruction on AI strategy, governance and investment decisions, while customer service employees may need practical training in automated workflows, AI-assisted communication and quality control.
Organizations have yet to fully understand the necessary steps for upskilling and reskilling in the context of AI’s impact on specific roles. A one-size-fits-all approach to interventions in the AI landscape may ultimately be counterproductive.
John McLaughlin, chief commercial officer and partner in Aon’s Health Solutions practice
The analysis suggests employers should assess existing workforce capabilities before introducing training programs, as some employees may already possess relevant AI skills.
Companies should also evaluate how specific jobs could change and identify where technological investment would deliver measurable operational benefits.
AI adoption increases governance and data privacy risks
The expansion of AI into workforce management raises questions about fairness, accountability and the protection of sensitive employee information.
Aon identifies compensation and pay-setting decisions as particularly sensitive applications because errors or biased outputs can directly affect individual employees.
Although AI can provide useful analytical support, the firm advises organizations against allowing automated systems to determine compensation without appropriate human involvement.
Employers should document how AI contributes to significant employment decisions and ensure that the information underlying recommendations can be evaluated for reliability and fairness.
Transparency becomes especially important when technology influences pay, career progression or other outcomes affecting employees.
“Human oversight should be integral to using AI; it shouldn’t be solely AI making decisions,” said Suzanne Courtney, associate partner in Talent Solutions for Europe, the Middle East and Africa at Aon.
Data protection represents another significant concern
AI systems frequently process large volumes of information, including potentially sensitive workforce data. Inadequate controls over how that information is collected, stored and accessed can increase exposure to privacy breaches and unauthorized disclosure, according to Human Resources Global Benchmark for Insurance.
The risks become more difficult to manage when employees independently use AI applications outside company-approved systems.
Microsoft research indicating that 78% of US workers use generative AI, with 73% of those users accessing the technology through their own devices.
The figures illustrate the challenges employers face in maintaining visibility over AI use and enforcing consistent information security policies.
Organizations therefore need governance frameworks that establish clear responsibilities, define approved applications and address ethical and regulatory requirements. These frameworks should be reviewed regularly as technology capabilities and legal obligations evolve.
Global competition for AI talent intensifies
The rapid adoption of AI is also increasing competition for professionals with specialized technical skills. Aon notes that employers are offering compensation premiums to attract experienced AI talent, creating recruitment and retention challenges in markets where the supply of qualified workers is limited.
The United States remains a major destination for international AI professionals, supported by substantial investment and demand from technology-intensive businesses.
“Every country except for the U.S. is a net exporter of AI talent,” McLaughlin said. Against this competitive backdrop, Aon argues that organizations should not rely exclusively on external recruitment.
Developing existing employees can provide a more sustainable approach to building the technical and managerial capabilities needed for AI adoption.
Investment in education, competitive compensation and workplace cultures that encourage continuous learning can support talent retention and reduce dependence on a limited pool of experienced specialists.
The firm also emphasizes the importance of creativity, analytical thinking, technological literacy and adaptability as companies prepare future leaders.
Key AI workforce risks and recommended controls
| Risk | Potential impact | Recommended mitigation |
|---|---|---|
| Algorithmic bias | Unfair hiring, compensation or workforce decisions | Human review, bias testing and documented decision criteria |
| Employee data privacy | Unauthorized exposure of personal information | Access controls, data minimization and privacy policies |
| Unapproved AI tools | Sensitive business information entering external systems | Approved platforms, employee training and usage policies |
| Inaccurate AI outputs | Incorrect recommendations affecting employees | Fact-checking, validation and accountability procedures |
| Regulatory noncompliance | Legal, financial and reputational exposure | Regular compliance reviews and updated governance frameworks |
| Workforce skills gaps | Reduced productivity and difficulty adopting new technology | Role-specific upskilling and reskilling programs |
| Excessive automation | Loss of human judgment in consequential decisions | Defined human oversight and escalation procedures |
Four priorities for employers implementing AI
Aon identifies four actions organizations can take to establish a stronger foundation for AI adoption.
- First, employers should assess their existing AI capabilities, including the technical knowledge employees already possess and the areas where further development is required.
- Second, businesses should evaluate opportunities within HR functions, distinguishing between applications that improve existing processes and those that could support broader operational redesign.
- Third, companies should establish specific AI use cases through collaboration between senior leadership and employees. This includes identifying measurable benefits, defining responsibilities and assessing how job requirements could evolve.
- Finally, organizations should develop a comprehensive AI strategy covering governance, regulatory compliance, change management, employee communication and the implications for compensation and decision-making.
Successful adoption will depend on more than acquiring AI technology. Employers will also need to redesign workforce development programs, strengthen oversight and ensure employees can use automated systems effectively without surrendering responsibility for critical decisions.
As AI becomes more embedded in everyday business operations, the ability to combine technological capabilities with human judgment will be an increasingly important factor in workforce performance and organizational resilience.
How is artificial intelligence transforming human resources?
AI is automating routine HR activities such as interview scheduling, onboarding and employee support. It is also supporting compensation analysis, workforce planning and personalized employee training. Aon expects its use to expand from improving individual processes toward redesigning entire workflows and job functions.
Will AI replace HR professionals?
Aon does not suggest that AI will eliminate the need for HR professionals. Instead, it expects technology to change their responsibilities and the skills required to perform them. Human expertise will remain important for employee relations, ethical decisions, critical thinking and oversight of AI-generated recommendations.
Which AI skills will be most important for employees?
Important capabilities include AI literacy, data analysis, critical thinking, statistical interpretation and the ability to evaluate automated outputs. Some specialist positions will also require knowledge of machine learning, prompt engineering and AI governance. Communication and emotional intelligence remain relevant because many workplace decisions require human judgment.
What is the difference between upskilling and reskilling for AI?
Upskilling helps employees improve capabilities within their existing roles, such as learning to use AI tools for reporting or administrative tasks. Reskilling prepares employees to perform different responsibilities or move into new positions as AI changes existing workflows. Aon highlights the growing importance of reskilling because some jobs may undergo substantial changes.
Can employers use AI to make salary and compensation decisions?
AI can assist with compensation benchmarking, data analysis and reward recommendations. However, Aon emphasizes that consequential pay decisions should remain subject to human oversight. Employers should verify the information used, assess potential bias and document how automated recommendations influence final outcomes.
What are the biggest risks of AI adoption in the workplace?
Major risks include exposure of employee data, algorithmic bias, inaccurate outputs, regulatory noncompliance and uncontrolled use of unapproved AI applications. Workforce skills shortages and excessive dependence on automated systems can create additional operational problems. Aon recommends governance frameworks, clear accountability, employee training and human review of important decisions.
How should companies develop an effective AI workforce strategy?
Aon recommends starting with an assessment of existing employee skills and identifying practical AI applications within business functions. Employers should then prioritize specific use cases, develop role-based training and introduce governance standards covering privacy, fairness and accountability. The strategy should also include change management and regular reviews as AI capabilities and regulatory requirements evolve.
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Edited by Nataly Kramer – Lead Insurance Editor at Beinsure
