How AI will transform talent and the workforce

AI News

Artificial intelligence (AI) is having a measurable impact on every aspect of HR, from organizational design and talent management to compensation and benefits. To effectively leverage this technology, HR leaders need to ensure that both their teams and the workforce at large are ready, writes Aon leader Wael Hafez.

AI is disrupting every area of ​​business strategy. Various aspects of AI, especially predictive AI, which uses machine learning to identify patterns in past events and forecast future events, have been part of the HR function for quite some time now.

But generative AI, which includes content creation, will accelerate how technology interacts across the business, and with HR in particular. When it comes to managing the workforce in the AI ​​era, HR professionals need to consider the implications and manage the risks and opportunities across compensation and benefits, talent management and organizational design.

There are two ways that AI will impact talent.

First, AI itself can be leveraged by HR professionals across a range of functions, for example, predictive AI can be deployed to identify high-cost medical and benefit claimants, and generative AI can be used in talent management to create job descriptions, and second, HR professionals can prepare their organization's workforce for the upcoming transformation that AI will bring.

How AI will impact the HR function

In a recent Aon survey, nearly 400 HR professionals said the areas of workforce analytics, recruiting, and learning and development will benefit most from AI.

Workforce analytics is a discipline that can be utilized by almost any type of HR function, including identifying employee population characteristics, recruitment strategies, and salary and promotion trends.

Prospects and Strategies for AI in Human Resource Management

Perhaps no area of ​​HR will be more impacted by AI than talent management professionals. As AI becomes more integrated into business strategies, it will be important to prepare employees to take advantage of the new technology. AI will likely require new skills, new jobs, and new ways of working. In-house AI models can help predict employee retention and attrition risks.

Overall, organizations need to start thinking about how all jobs will change substantially today and tomorrow. We help them with this by analyzing jobs and understanding what can be automated, what can be extended, and how jobs need to be redesigned.

Economists have predicted that new technologies would replace workers since the Industrial Revolution. These predictions tend to exaggerate the extent to which workers will be completely replaced and underestimate the idea that workers will adapt to, gain skills, and take advantage of the productivity gains brought about by automation to increase overall output.

Therefore, human resources professionals will need to prepare for the use of AI in terms of reskilling and upskilling, as well as plan for the creation of new jobs to successfully manage AI.

Using Aon's extensive global talent database, we analyzed AI's potential impact on jobs across multiple industries. In the technology industry, we found that 32% of roles and 69% of employees are at risk of significant disruption from AI. The level of disruption varies significantly by industry. In contrast, our analysis of life sciences companies found that 23% of roles and 34% of employees are at risk of significant disruption from AI.

While the level of disruption varies by industry, there is a common thread across industries: HR professionals will need to lead the effort to use technology responsibly and prepare their employees for its adoption. An analysis of HR functions across industries found that 24 percent of job roles and 58 percent of employee populations will be disrupted.

A comprehensive strategy starts with workforce planning, which involves determining the jobs needed for the organization and the impact on the overall work structure. While it is interesting to know the overall disruption that AI is expected to cause in a particular industry, it is more useful for HR and business leaders to understand the types of jobs that will be disrupted.

Tackling AI in the Workforce

Task AnalysisThe first step is to determine which tasks can be automated or achieved with AI. Meeting scheduling and other repetitive tasks are perfect for automation. But the impact goes beyond automating tasks. Certain jobs may fundamentally change in ways that reskilling or upskilling cannot achieve.

Job Design: It is important to determine which jobs will be affected and to what extent, as well as set expectations around reskilling or upskilling rather than role replacement. Job redesign may impact salary ranges. It is also important to plan for severance costs associated with workers whose roles are no longer required.

Talent and transformation strategy: Communication can't be ignored. Managers should be upfront about the possibility of roles being cut, but also have clear talking points to share with employees about the business opportunities and the need for upskilling and reskilling. This will ease some of the uncertainty in conversations around AI.

4 ways to manage your AI transformation

HR professionals are in a strategic position to manage the workforce transformation that AI can bring about by understanding which roles will change and how, and leveraging the capabilities enabled by using AI across the HR ecosystem, including health and benefits, talent management, and retirement planning.

Process governance is essential for transformation: Many of the concerns around AI are around data security, over-reliance on unproven technology, and lack of control over the implementation process.

However, many of these issues and concerns can be alleviated by keeping the following points in mind:

Linking AI use to company values
Ensure that your use of AI applications is aligned with your company's overall vision, mission, and values. For example, organizations committed to promoting inclusion and diversity should ensure that AI recruiting tools are carefully vetted to promote fair and unbiased hiring practices. Building trust in data, mitigating bias, maintaining data privacy, and minimizing cybersecurity risks are all key to integrating AI responsibly.

Leveraging technology to ensure accountability and quality
HR plays a big role in establishing how people use AI. HR teams need to monitor the performance and impact of the AI ​​applications they use, as well as support best practices within their organizations to identify, report, and mitigate potential errors, bias, or harm. HR leaders and professionals should also work with other departments to establish clear roles and responsibilities for the design, development, deployment, and oversight of AI applications and associated data.

Developing workforce skills and capabilities to manage AI
Like any technology, AI will not replace HR leaders and professionals. They intuitively understand that AI is not a substitute for human intelligence and emotions, but rather a complement and facilitator. Therefore, HR leaders and professionals must invest in developing and enhancing the skills and capabilities of their employees to work with AI tools. This includes building data literacy, analytics, and programming skills, as well as supporting soft skills such as critical thinking, creativity, collaboration, and emotional intelligence. Additionally, HR leaders and professionals must foster a culture of learning and innovation that encourages employees to try and learn from approved AI applications.

Proceed with caution and be open-minded about limitations
While the hype around generative AI has been around for a while, some believe the technology is not, or will never be, good enough for general use. AI is only as good as the datasets used to train it, which can leave it open to bias and misinformation. Generative AI is also prone to “hallucinations,” where the output of an AI prompt can contain false or fabricated information.

Other concerns relate to intellectual property and how AI models are trained. Indeed, many AI companies are sometimes frustratingly vague. These issues highlight the need for organizations to adopt AI technologies, like any new approach to work, carefully, thoughtfully, and following best practices.

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