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Human Resources
Three areas where AI could transform HR
AI is an increasingly key aspect of HR departments. How can those HR leaders still on the fence lay the groundwork for successful adoption in their organizations?Â
âŻThe march of AI as part of HR continues at pace. According to Gartner, as many as 81% of HR leaders have begun to explore the potential of AI. It is abundantly clear that the technology can add value in critical areas â but how many organizations are capitalizing on the true potential of AI and machine learning (ML) to support the HR agenda?
The much-hyped advent of AI tools such as ChatGPT has opened up new frontiers, but HR has ground to make up in deploying âclassicâ AI and ML. Such tools have rapidly moved from the realm of experimental technology into the mainstream and offer the automatic sifting of vast amounts of data at speed. They are increasingly available to organizations as off-the-shelf solutions, at relatively low costs, making them more accessible than ever and making the barriers to entry to the world of AI-enabled HR look invitingly low.
Yet, if HR leaders are to deploy AI and ML effectively, they must recognize that it involves much more than simply flicking a switch. For HR leaders still assessing the potential of AI, there are three key areas:âŻrecruitment, people management, and learning and evaluation.
Taking the grind out of recruitment
The capacity of AI and ML to analyze vast amounts of data can greatly enhance and accelerate the process of matching talent demand with supply. AI can sift through candidate profiles at speed, rapidly reducing even the biggest pool to those who are best suited to the requirements of any given role. It can also highlight candidates with scarce specialist skills when organizations are fishing in a small pool.
On the supply side of the talent equation, jobseekers can use AI tools to find openings to which their skills and abilities make them well-suited and finesse their CVs to maximize the chance of being invited to interview.
AI as a people-management tool
The second area where there is huge untapped potential for HR to lead the adoption of AI is employee management. To do so, organizations need to tap into the vast amount of employee data that they routinely collect but rarely examine.
For instance, data about employee communications â which are, after all, the property of the organization â can yield valuable insights. The first level of analysis might focus on communication flows, revealing the hidden networks created by individuals and teams. Understanding the communication between teams may reveal the existence of silos, enabling leaders to intervene to break them down. On the individual level, understanding where an employee has built up a strong personal network, and on which areas they should focus on developing relationships, can be a powerful tool for incrementally increasing a businessâs presence in its ecosystem.
Unstructured data, although rarely used, can also provide rich insights. One such area is the content of communications. Large-scale analysis of the language used in emails might, for instance, reveal insights into a given employeeâs overall attitude toward the business. Â
Customer interactions can also offer valuable indicators. For instance, customer service teams can use AI and ML, in combination with voice-recognition tools, to analyze the customer interactions of service agents. If an agent receives an unusually high number of complaints, for example, AI may be able to highlight potential reasons for this, such as a failure to engage the customer at key moments in the interaction, or even something as simple as an overly brusque telephone manner, all of which HR training can address. Â
Learning and evaluationÂ
The third area where AI has huge potential relates to career management and how employees are supported in their learning and development. By using data-driven metrics of the capabilities of existing employees, HR can lead a more active approach to career management. Data relating to employee skillsets can be combined with that related to performance evaluations, willingness to relocate, or interest in taking on a new role. HR can work with hiring managers to identify and approach potential candidates. Particularly in large organizations with high numbers of employees, this can offer an incredibly effective way to leverage the talent already within the organization.Â
AI analysis could also enable a more granular conversation with employees about their opportunities. The message might be: âWe have an opening for a product manager, and you are close to meeting the requirements ââŻbut, currently, you fall short in three specific areas. If you join this other team and work on this project over the next six months, we think you will develop those three areas,âŻso, the next time there is a vacancy, you could be ready for the step up.â Â
This active approach to managing employeesâ careers could significantly impact retention, which is currently a significant challenge for so many organizations. It will also help the effort to enhance diversity, equity, and inclusion (DE&I) by reducing reluctance among members of under-represented groups to put themselves forward for promotion. For example, research has suggested that women are less likely than men to apply for roles when they know that they fall short on specific job criteria. Minority groups may be put off by a lack of visible role models among senior leadership. By enabling a more active approach to learning and development, AI can help reduce the effect of such behavioral differences. It can support the vital aim of ensuring organizations have access to the very best available talent from whichever demographic happens to contain it, while helping create the conditions for those employees to thrive.  Â
Laying the foundations for AI-driven HRÂ Â
HR leaders face multiple challenges as they look to deploy AI across these three areas. First, they must understand the emerging regulatory landscape, particularly in respect of using AI for managing people. Understanding regulatory developments is increasingly important. Â
Regulation relating to digital technology and privacy may make some applications impracticable, at least in certain jurisdictions. The EU, for example, has developed notably stringent rules. Â
Perhaps the more fundamental challenge relates to HRâs existing capabilities and their limits. Most HR teams lack expertise in AI tools and data. HR leaders can begin to change that picture by following three key steps. Â
- Democratization. HR leaders should provide access to AI-relevant capabilities for all employees, particularly within HR. The goal is not to turn everyone into a data scientist, but to ensure that all employees have the basic skills required to work with data. Consider providing distributed learning and easy-to-use tools that employees can access as part of their personal development.Â
- Share best practices. Work with tech colleagues to open HR employeesâ eyes to the potential of AI and ML. Set up a regular point of contact between a member of the technology or data team and the HR team to share how AI is being used elsewhere in the company, to spark fresh thinking. By focusing on practical AI use cases, such discussions may allay fears about the implications for jobs, reducing resistance to change.Â
- Promote a culture of experimentation. HR leaders should set the tone for their teams in adopting AI. Experiment, be prepared to âfail fastâ and iterate, and learn from your failures and successes. By adopting such an open mindset, you will be able to identify where AI can add the most value to the HR agenda in your organization. Â
AI solutions for key HR tasks are proliferating and becoming ever more accessible. HR leaders need not become technology or data specialists. However, they do have a critical role to play in creating the conditions for AI to be used effectively to deliver value for their organizations. The results could be transformative.Â
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