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AI in Human Resources: How To Maximize Its Potential

Thursday February 22, 2024

Employee sitting at a desk at a computer, with AI symbols overlaying the image, appearing to come out of the laptop.

Generative Artificial Intelligence (AI) is gaining increasing prominence in the modern business world. Human Resources isn’t an exception. Gartner reports that 76% of HR leaders believe that if their company doesn’t implement AI in the near future, they’ll be less likely to succeed as those that do.

The rapid advancements in these technologies aren’t without concerns, however. Many HR leaders are concerned about factors such as data privacy, bias, and ethical mishaps.

However, despite these concerns, Gartner reports that 52% of HR leaders are exploring generative AI use cases and potential opportunities.

If you’re hoping to capitalize on this technology and lead your HR team to success, you need to learn how to optimize the benefits while mitigating the risks of AI.

Here’s an overview of the pros and cons of AI in HR, and how to maximize its potential.

Benefits of AI in HR

The first step to maximizing the potential of AI in your organization is familiarity with its potential benefits and drawbacks.


Recent research from Zoom shows that 73% of leaders believe that organizations that leverage AI will have a distinct advantage over those that don’t.

There’s no denying that AI has a host of potential benefits when leveraged effectively. Here’s a list of some of those benefits.

Mitigating Bias

A recent Workday report about AI in HR reveals that 36% of HR leaders believe that AI has the potential to mitigate bias in the workplace.

For example, when making hiring or promotion decisions, AI has the capacity to evaluate data and make merit-based decisions without personal feelings getting in the way.

It’s important to remember that since AI is intended to mimic human behavior, it also has the potential to be subject to the same biases.

Learning and Development

According to Harvard Business Review (HBR), AI can help foster learning and development in the workplace. Some AI tools can provide personalized learning and development opportunities based on engagement and performance data.

AI can benefit learning and development in the following ways:

  • Providing personalized learning pathways: Instead of taking a broad, generalized approach to learning and development, AI can leverage employee performance data and suggest areas of improvement.
  • Real-time updates to training materials: As time progresses and technology advances, training resources might become outdated. Generative AI technologies can continuously update these resources as changes are made, rather than requiring humans to manually check for outdated information.
  • Real-time feedback: As you’re working on various projects, AI has the potential to offer real-time feedback and suggestions. Chatbot integrations allow you the ability to ask questions about the feedback, fostering learning.

These learning and development opportunities make processes such as onboarding employees easier, since they can help optimize the experience by improving the training process.

Talent Acquisition

One area in which generative AI has immense potential to improve productivity is in the area of talent acquisition.

According to McKinsey, it can help in the following ways:

  • Identifying skills for a job posting: Generative AI can help you quickly identify job requirements and draft a job description by analyzing which skills are necessary for success in a given position.
  • Drafting job descriptions: If you’re aware of the skills you’re searching for in a position, it can also simply take your inputs and draft a comprehensive description, saving time.
  • Flagging biased language: AI can vet a potential job posting for any bias or discriminatory language. For example, it can correct gender-specific language (such as “the ideal candidate should bring his A-game every day”) or age discrimination (such as “the ideal candidate is young and energetic”). It can also promote skills-based hiring, reducing affinity bias.

Gartner reports that HR leaders also expect to leverage generative AI to complete tasks such as composing interview questions and communicating with candidates.

Another area in which AI can improve the talent acquisition process is through job interviews. According to HBR, there are 5 types of interviews when it comes to AI:

  1. Face-to-face: Humans interacting in the same location and at the same time
  2. Video: Humans interacting at the same time but different locations, conversing through a video call
  3. Automated video interview (AVI): Interviewee is prompted to complete a video recording facilitated by technology. Technology isn’t involved in making the final decision.
  4. AVI, AI-assisted: Similar to AVI, except that AI technology can make recommendations based on facial expressions, tone of voice, and other factors, often in the form of a report that a human reviews.
  5. AVI, AI-led: An automated video interview in which technology makes the hiring decision without human intervention, such as passing a candidate through ot the next part of the process.

The specific type of interview your team conducts depends on a variety of factors, such as how large your company is, how many interviews you get, and how much time your team has to dedicate to the interview process.

Many companies incorporate multiple types of automated interviews during different stages of the interview process, increasing the level of human interaction as the interview progresses.

Organizational Improvements

Ultimately, AI is expected to reduce the amount of time dedicated to redundant or mindless activities, allowing more time and mental brainpower to be committed to human-to-human interactions.

A Gartner survey revealed that 84% of HR leaders believe that generative AI will improve the productivity of existing HR activities, and two-thirds expect it to reduce redundant tasks.

According to Workday, many HR leaders expect the following benefits from generative AI:

  • 34%: Higher levels of productivity
  • 33%: Better collaboration
  • 29%: Higher revenues and profits
  • 29%: Improved data-driven decision-making
  • 28%: Better organizational agility
  • 27%: Improved employee experience and engagement
  • 25%: Talent development and upskilling
  • 24%: Decreased costs
  • 20%: Improved environmental, social, and governance (ESG) factors

Many HR processes that consume valuable time and resources, such as drafting HR documentation, can be significantly expedited with generative AI.

Performance Management

Because empathy is critical to performance management, many leaders don’t consider incorporating generative AI into the process. However, there are benefits to incorporating generative AI into the process, provided it doesn’t eliminate the human element.

35% of HR leaders believe that AI will help in performance management tasks such as evaluating employee performance and drafting performance reviews.

If effectively utilized, AI can actually increase the amount of human interaction and empathy that’s incorporated into performance management. By saving time and reducing redundant tasks, more time and mental resources can be dedicated to personalizing the experience.

Concerns About AI in HR

Many of the benefits of AI are dependent on its implementation.

Simply adding generative AI to your existing processes without considering how it can uniquely benefit your organization, and proactively addressing the potential downsides, can result in the following concerns.

Diminished Trust

According to Workday, one of the top concerns about generative AI is its trustworthiness, with 47% of HR leaders reporting trust as a concern.

The problem arises when AI is used for decision-making without transparency. If decisions are made without knowledge of how or why, the simple fact that AI was involved in the process isn’t likely to improve trust.

Especially when AI is used for decisions that impact employees’ livelihoods—such as promotions or firing—transparency and intentionality is vital.

For this reason, it’s vital to have open communication about how AI is used, and a willingness to hear feedback from employees.

Potential Bias and Ethical Concerns

While AI can be leveraged to mitigate bias, it can also exacerbate it. Approximately 53% of HR leaders are concerned about bias and ethical concerns of AI.

These concerns aren’t unfounded. For example, since generative AI was trained on human writing, many of the biases transferred over to the various models. While many generative AI models have sought to address these biases, there’s still reason to be concerned.

Stanford Social Innovation Review analyzed 133 biased AI systems from 1988 to 2021, and discovered the following:

  • 44.2% demonstrated gender bias
  • 25.7% demonstrated both gender and racial bias

AI detection tools are another source of potential discrimination. Research from Stanford demonstrated that these tools incorrectly flagged writings from non-native English speakers as AI generated 61.22% of the time.

It may also use language that’s common in business, but might be offensive to individuals of various cultures or countries. For example, terms like “guru” or “powwow” are common, but can have harmful impacts on marginalized groups or individuals from different cultures.

Employee Privacy

Many companies have implemented AI technology to track employee activity. HBR reports that these tools have the potential to erode employee privacy, leading to:

  • Stress
  • Burnout
  • Worsened mental health
  • Lower sense of agency

These privacy concerns diminish trust in your organization, especially if there isn’t transparency and communication about AI usage.

Legal Risks

In addition to practical concerns regarding AI usage, there are liability risks associated with AI as well.

The American Bar Association reports that if AI tools aren’t properly vetted and monitored, it can discriminate against employees, subjecting employers to legal action.

For this reason, AI implementation needs to be intentional and completed with care.

AI Generated Job Applications

Not all HR-related AI applications come from within an organization. Gartner reports that 69% of HR professionals report that their company has received at least one job application that contains AI-generated writing, and 14% aren’t sure.

Of those who have reported receiving AI-generated applications, over half report that between 25% and 50% of applications contain AI-generated copy.

41% of HR professionals say their company evaluates AI-generated applications separately, with 69% using applicant tracking software to flag these applications.

According to Gartner, the top concerns HR professionals are encountering regarding AI-generated applications include:

  • 56%: Overlooking good candidates
  • 52%: Verifying authenticity of information provided by the applicant
  • 50%: Determining whether or not the applicant used generative AI technology

The Washington Post recently published an article speaking to the challenges of flagging AI-generated content. An estimated 4% of flagged content is incorrectly identified as AI-generated, and as mentioned earlier, this is even more frequent for non-native English speakers.

The fundamental flaw in leveraging these tools to flag AI-generated applications is that generative AI is intended to replicate human writing styles. This means that some peoples’ writing is likely to be flagged as AI-generated simply because of their writing style, and not because they used any particular tool.

Employee Resistance

The final concern with AI-generated applications is employee resistance. Gallup reports that 53% of employees don’t feel adequately prepared to use AI, with 26% saying they’re not prepared in the slightest.

Furthermore, the majority of employees are skeptical about generative AI, with only 30% believing it to be beneficial.

Simply expecting employees to adapt to generative AI without open conversations and training isn’t likely to be successful.

How To Maximize the Potential of AI in HR

The first step to maximizing AI’s potential in your organization is getting your team on board. If your employees are resistant to using generative AI, and aren’t involved in the decision-making, there will likely be significant friction with its adoption.

According to HBR, HR professionals who leverage AI for talent acquisition need to begin by taking the following steps:

  1. Educating potential employees and obtaining their consent to use AI in the hiring process.
  2. Ensuring any AI systems you use are fair, unbiased, and accurate.
  3. If developing your own AI system, making it open-source and conducting routine third-party audits.
  4. Making sure you’re adhering to the same laws and regulations used in traditional hiring practices, including how data is collected and used (such as mental health conditions, or other private information).

An excellent starting point is the STEP framework.

The Step Framework

One of the top concerns about AI in HR is a lack of skills. Workday reports that 32% of HR leaders are concerned that their HR team won’t have the technical skills to implement AI effectively.

31% are also concerned about HR employees becoming overly dependent on AI technology.

Furthermore, 14% of employees are concerned that their jobs will be eliminated by AI, and 72% of fortune 500 CHROs predict that AI will replace jobs in their organization in the next three years.

To address these concerns, it’s important to ensure that AI can be used in a way that doesn’t just benefit the organization as a whole, but your individual employees as well. Effectively leveraging AI can augment your team’s roles, rather than eliminating them.

Developed by Paul Leonadri, the Duca Family Professor of Technology Management at the University of California, Santa Barbara and host of our team experience, Adopting Gen AI, the STEP framework can help your team effectively implement generative AI.

  1. Segmentation: Identify the tasks that AI shouldn’t—or isn’t able to—perform, the tasks that AI can accomplish that augment or enhance your team’s activities, and which tasks can be fully automated by AI.
  2. Transition: Determine how employees’ roles can be deepened or upgraded because of the time AI has freed up.
  3. Education: Equip employees with the knowledge and skills required to effectively leverage AI technology.
  4. Performance: Consider how performance evaluations should evolve given the usage of generative AI.

Each of these factors can be personalized to fit your company’s specific needs.

Integrating Generative AI Into Your Organization

If you’re interested in working with Paul Leonardi to determine how the STEP framework can be leveraged to integrate generative AI into your organization, consider our team experience, Adopting GenAI.

In this experience, Paul will help your team become more adept at integrating AI into your processes, creating value for employees and your organization as a whole.

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