How Artificial Intelligence is Transforming Human Resources and the Workforce

How Artificial Intelligence is Transforming Human Resources and the Workforce
May 9, 2024 27 mins

How Artificial Intelligence is Transforming Human Resources and the Workforce

How Artificial Intelligence (AI) is Transforming Human Resources and the Workforce

Artificial intelligence is having a measurable impact across all aspects of HR — from talent management to compensation, health and benefits, and retirement planning. To effectively harness the technology, HR leaders must ensure both their own teams and the wider workforce are prepared.

Key Takeaways
  1. HR professionals need to consider both how to deploy AI in their own role and how to prepare the workforce.
  2. AI can help identify ways to lower benefits costs and increase employee engagement with total rewards offerings.
  3. There are workforce opportunities and risks associated with AI, and HR will play a key role in ensuring its responsible deployment.

Artificial intelligence (AI) is disrupting all areas of business strategy. Aspects of AI, specifically predictive AI — which uses machine learning to identify patterns in past events and make predictions about future events — have been a part of HR functions for quite some time. But generative AI, involving the creation of content, will accelerate how technology interacts with the whole business and HR specifically. When it comes to managing the workforce in the era of AI, HR professionals need to consider the impacts and manage risks and opportunities across health and benefits, talent management and retirement.

There are two distinct ways that AI can have an impact on HR. First, AI itself can be used by HR professionals across the different functions of their role. For example, deploying predictive AI to identify high-cost health and benefits claimants or using generative AI to write job descriptions in the talent management space. Second, HR professionals can ready their organization’s workforce for the coming transformation that AI will create. 

To begin, we will explore the impact of AI on HR functions. 

In a recent Aon survey, nearly 400 HR professionals said the areas of people analytics, talent recruitment, and learning and development would benefit the most from AI. People analytics is a discipline that can be leveraged in nearly all types of HR functions, such as identifying characteristics of the employee population, hiring strategy and pay and promotion trends.

"As with all new and rapidly changing technologies, it is natural for people to take a 'wait-and-see' approach," said Lambros Lambrou, Aon's CEO of Human Capital. "But when it comes to AI, human resources teams have a significant opportunity to lead the way. It's important not to miss the moment. By understanding how AI effects the workforce, HR can better prepare everyone for changes to come."


How Artificial Intelligence (AI) is Transforming Human Resources and the Workforce


AI moved up 32 spots, from 49 to 17, in the risks currently faced by companies.

Source: Aon's Ninth Global Risk Management Survey

Outlook and Strategies for AI in Healthcare and Benefits


Different forms of AI have already provided cost savings and an enhanced employee experience in the healthcare sector.

  • Machine learning is used for precision medicine to predict which treatments are likely to be successful based on patient data.
  • Natural language processing can be used for clinical documentation and published research to analyze notes, create reports and transcribe patient interactions. Some chatbots are already being replaced by a fully interactive AI assistant that interacts like a human.
  • Connected devices assess health symptoms, as well as deliver high-definition diagnostics and quicker response times.
  • Physical robots were originally used for more menial tasks, like delivering supplies in hospitals, but are increasingly used for more advanced purposes. For example, the use of robots in surgeries to make precise and minimally invasive cuts and stitch wounds.

By leveraging AI and machine learning, employers and providers can better understand the need and demand for care. The workforce will then be more likely to take advantage of these improved programs and benefits, resulting in positive health-related outcomes. 

AI has been used to predict high-cost health plan claimants — a growing concern in the U.S. and globally. The top five percent of healthcare plan members on average in the U.S. account for more than 60 percent of the total employer healthcare plan. Even more troubling: the number of $1 million claimants rose by more than 45 percent from 2019 to 2022 — driven by specialized care, such as cancer treatment and new gene and cell therapies. 

Case Study: Improving Health and Productivity of Employees with Machine Learning 

Aon worked with a multinational employer that had a large number of recurring high-cost polychronic members. The client wanted to improve engagement among plan members and clinical outcomes, with a focus on the members who were most likely to drive costs higher. Aon’s Health Risk Analyzer, which is powered by machine learning, was used to predict the future claims cost for each member of the plan. We found that half of the predicted high-risk cohort had not been identified by their current care management program, contributing to low engagement. Aon worked with the employer to use those predictions to optimize the employer’s health program by proactively engaging these high-risk members within care management. 

As a result, 20 percent of the identified high-risk members were actively managed by the employer’s clinical programs, and ultimately likely to improve health and cost outcomes. This translates to an anticipated claim savings of over $2,000 per additional managed individual.


Drug discovery takes an average of 12-15 years and has a 90 percent failure rate. AI can help reduce that time to eight years on average, while increasing the chances of success.

Source: World Economic Forum

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Tools like the Health Risk Analyzer help companies engage with their highest risk population to improve both their health and their productivity.

Meghan Rausch
Vice President and Health Actuary, Health Solutions, North America

Aon uses machine learning in a variety of other tools to predict outcomes of interest to our health clients and evaluate the impact of vendor or insurance programs. 

While concerns surrounding unknown AI and machine learning risks are valid, employers can’t afford to ignore the potential AI has for improving the health of their workforces. With AI-powered analytics, employers can synthesize and unlock insights to enable better decision making by:

  1. Improving employee satisfaction with health plan design. Insights derived from use patterns and satisfaction surveys can be used to inform future design.
  2. Lowering healthcare and benefit costs by negotiating better rates with carriers.
  3. Predicting and managing health-related costs. Predictive analytics can be an invaluable tool, allowing companies to “see around the corner” to anticipate health-related costs.
  4. Forecasting lost productivity due to illness and predicting the use of disability and early retirement due to health problems. 

These applications of AI are more of an evolution than a revolution. However, the same care must be taken as with any technology to safeguard employees’ private health information and other data. 

Outlook and Strategies for AI in Retirement Planning

AI has not yet been used as much in retirement planning as in other areas of HR. This is primarily because companies want to avoid having a tool that inadvertently creates a fiduciary responsibility where one hadn’t previously existed. There is concern that AI chatbots in particular could veer into giving advice that bots are not qualified to give, thus putting the organization in potential crosshairs with regulators. 

That’s not to say that there aren’t possible uses for AI in areas of retirement planning. These include:

  • Early retirement programs

    Employers can develop incentives for retirement that cater to individual needs and preferences with the help of AI. Employers today frequently rely on a one size fits all approach, but AI may be able to design programs that offer highly competitive benefits to employees that prioritize retirement savings, and less valuable retirement benefits to employees with other priorities.

  • Options at retirement

    Organizations may want a virtual assistant to help employees through the retirement process. These tools could process documents and recommend considerations for employees. Care must be taken, though, to ensure these tools refrain from exposing the fiduciary to additional risks.

  • Annuities

    In the United States, AI-driven technologies and algorithms are changing how annuities are structured, sold and managed. Virtual assistants will change the way participants select annuity providers and annuity contracts. Implementing these assistants directly into the retirement plan website could help reduce leakage and increase access to lifetime income.

  • Financial advice

    AI can provide long-term financial planning insights by considering various life events and recommending tailored products. Managed accounts are one early implementation of this idea. We will likely see further innovation as AI is incorporated into these programs.

  • Member experience and journey

    AI will unlock the power to easily segment and personalize communications, thereby encouraging member engagement. AI can also help with plan administration and using chatbots to answer questions, encouraging more self-service help.

  • Better governance

    An AI trustee could help improve performance, as could using data and analytics from AI to drive decision making. Using an AI tool to automate tasks could also free up professionals’ time to focus on strategy.

  • Compliance Tools

    AI services will likely be developed to help plan administrators monitor the performance of asset managers and third-party vendors in real time. These tools will keep costs low and drive further efficiencies in the field. An AI assistant could also be useful to identify regulatory issues relevant to an employee question or even summarize information included in those regulations.

Other more routine uses include using chatbots to perform repetitive tasks, such as retrieving plan information to communicate to members and answering basic employee questions about plans.

However, HR professionals should keep in mind some potential pitfalls. For example, employers will need to verify identities carefully. Bad actors will likely deploy AI to gain personalized data that can later be used for fraud. These schemes already exist, but may be more widespread as AI permeates this space.

Another risk is data security. Employers will want to think carefully about which data should and should not be accessible by AI. Sending an employee’s personal identifiable information over the internet may expose the organization to a data breach.

Another tool being used in retirement is predictive analytics to prepare custom estimates of pensioner life expectancy for base mortality tables. 

Outlook and Strategies for AI in Talent Management

It is likely that no area of HR will be affected as profoundly by AI as talent management professionals. As AI is integrated into business strategy, preparing the workforce to use the new technology is critical. AI could require new skills, new jobs and new ways of working. An internal AI model can help predict employee retention or flight risks. Once identified, interventions can be recommended or even implemented by the AI model on behalf of a manager. For example, an employee may receive a reminder about an Employee Assistance Program if they signal to the AI model that they need help managing stress. Managing those requirements will fall to talent management professionals. 

“The clients that I talk to know they have so much they need to comprehend that they're having trouble figuring out where to focus first,” says Marc Pajarillo, a partner in Aon’s Talent practice. “By and large, organizations need to start thinking about how all jobs will be substantively changed today versus tomorrow — and we’re helping them with this by analyzing jobs and seeing what can be automated compared to augmented and how they need to redesign jobs.”

Economists have been making predictions that new technologies would replace laborers since the Industrial Revolution.1 These predictions tend to overstate the degree to which workers would be replaced entirely, and undervalue the notion that workers would adapt, reskill and use the increased productivity afforded by automation to increase overall output. Thus, talent professionals should be looking toward preparing for the use of AI through the lens of reskilling and upskilling, as well as planning for the creation of new jobs to help manage AI successfully.

Using Aon’s extensive global workforce database, we analyzed the potential impact of AI on jobs across several industries. In the technology industry, we found 32 percent of job roles and 69 percent of headcount are at risk of significant disruption from AI. The level of disruption can vary greatly by industry. By contrast, our analysis of life sciences firms found 23 percent of job roles and 34 percent of headcount are at risk of significant disruption from AI.

How AI is Transforming Human Resources

While different industries will experience different levels of disruption, there is a constant across industries: HR professionals will need to lead the charge to both use the technology responsibly and prepare the workforce for its adoption. When we analyzed the HR function across industries, we found that 24 percent of roles and 58 percent of headcount will be disrupted.

A comprehensive strategy starts with workforce planning, including determining which jobs the organization needs and the effect on overall job architecture. While it’s interesting to know the projected overall disruption that AI will create in a given industry, it is more useful for HR and business leaders to understand the types of jobs that will be disrupted.

For instance, in the life sciences example above, some of the sector-specific roles that are most likely to be impacted include: 
  1. Medical & Technical Writers
  2. Clinical (SAS) Programmer
  3. Managed Care Contracts Manager
  4. Medical Billing Specialist
  5. Regulatory Affairs Associate
  6. Pricing & Policy Strategist
  7. Clinical Trials Administrator
  8. Digital Health Platform Developer


An HR trade group in the UK found that 91 percent of HR leaders think their HR professionals need further skills in using and applying technology like generative AI.

Source: Corporate Research Forum, January 2024

Roadmap to Address AI in Your Workforce

  • 01

    Task Analysis

    The first step is deciding which tasks can be automated or enabled by AI. Things like meeting scheduling or other repetitive tasks are best suited for automation. But the impact goes beyond automation of tasks. It may fundamentally change certain jobs in a way that cannot be reskilled or upskilled.

  • 02

    Job Design

    It’s important to determine which jobs will be impacted and how much, as well as set expectations around reskilling or upskilling versus replacing roles. Job design changes may impact salary ranges. It’s also important to plan for severance costs associated with workers whose roles become redundant.

  • 03

    Workforce and Change Strategy

    Not to be ignored is communication. Managers should have clear talking points to share with employees about business potential and the need to upskill and reskill, while being forthright that roles may be eliminated. This will help ease some of the uncertainty driving the conversation around AI.

Four Ways HR Professionals Can Manage the AI Transformation

HR professionals have a strategic seat at the table when it comes to managing the transformation of the workforce that AI may bring. This will require professionals to understand which roles will change and how, and to harness the capabilities that are unlocked by using AI across the HR ecosystem — from health and benefits, talent management and retirement planning. 

Inherent in the transformation will be governance of the process. Many of the fears around AI revolve around concerns about data security, over-reliance on unproven technology and a lack of control over the process of implementation. However, by keeping in mind the following considerations, many of those issues and fears can be mitigated:

  • 1. Relate AI use back to company values

    Ensure the use of AI applications is aligned with the overall vision, mission and values of the company. Organizations that are committed to promoting inclusion and diversity, for example, should ensure AI recruiting tools are carefully vetted so they promote fair and unbiased hiring practices. Building trust in data, mitigating bias, maintaining data privacy and minimizing cybersecurity risk are all keys to responsibly integrating AI.

  • 2. Ensure accountability and quality with the use of the technology

    HR has a big role to play in establishing how people use AI. HR teams should monitor the performance and impact of any AI applications they use, while also supporting best practices within their organizations to identify, report and mitigate any potential errors, biases or harms. HR leaders and professionals should also partner with other functions to establish clear roles and responsibilities for the design, development, deployment and oversight of AI applications and related data.

  • 3. Develop skills and competencies for the workforce to manage AI

    As with other technology, AI does not replace HR leaders and professionals who intuitively understand AI is not a substitute for human intelligence or emotions, but rather a complement and an enabler. Therefore, HR leaders and professionals should invest in developing and enhancing employee skills and competencies to work with AI tools. This includes building data literacy, analytics and programming skills, as well as supporting soft skills like critical thinking, creativity, collaboration and emotional intelligence. Additionally, HR leaders and professionals should foster a culture of learning and innovation where employees are encouraged to experiment with and learn from approved AI applications.

  • 4. Proceed with caution and keep an open mind about limitations

    While the hype about generative AI has been around for some time now, there are people who believe that the technology is not — and may never be — good enough for general use. AI is only as good as the dataset it is trained on, meaning bias and bad information may persist. And generative AI is prone to “hallucinations,” where the output of an AI prompt includes information that is wrong or fabricated. 

    Other concerns relate to intellectual property and how the AI models are trained. It’s true — many AI companies have been frustratingly vague at times. These issues underscore the need for organizations to adopt AI technology as they would any other new approach to working —carefully, thoughtfully and with best practices guiding the way.


Fifty-one percent of 376 HR professionals polled by Aon in February 2024 said they are not ready to use AI capabilities in their HR organization.

Quote icon

When it comes to AI, human resources teams have a significant opportunity to lead the way. It's important not to miss the moment.

Lambros Lambrou
CEO of Human Capital, Aon
Aon’s Thought Leaders
  • Ben Batho
    Data and Analytics Leader, Health Solutions, Europe, Middle East and Africa
  • Kathryn Davis
    Vice President, Global Benefits
  • Muir Macpherson
    Partner, Global Human Capital Analytics
  • Grant Martin
    Associate Partner, Wealth Solutions, North America
  • Marc Pajarillo
    Partner, Talent Solutions, North America
  • Rebecca Peake
    Senior Consultant, Wealth Solutions, Europe, Middle East and Africa

General Disclaimer

This document is not intended to address any specific situation or to provide legal, regulatory, financial, or other advice. While care has been taken in the production of this document, Aon does not warrant, represent or guarantee the accuracy, adequacy, completeness or fitness for any purpose of the document or any part of it and can accept no liability for any loss incurred in any way by any person who may rely on it. Any recipient shall be responsible for the use to which it puts this document. This document has been compiled using information available to us up to its date of publication and is subject to any qualifications made in the document.

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