BrazilHow AI is transforming human resources and the workforce
Artificial intelligence (AI) is having a measurable impact across all aspects of HR – from organization design, talent management to compensation and benefits. To effectively harness the technology, HR leaders must ensure both their own teams and the wider workforce are prepared, writes Aon leader Wael Hafez.
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 compensation and benefits, talent management, and organization design.
There are two distinct ways that AI can have an impact on human resources.
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.
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.
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.
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. 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.
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.
Addressing AI in the workforce
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.
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.
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 to 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:
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.
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.
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.
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.
