AI in Talent Acquisition a Big Advantage for HR

What if there was a way to spend less time filling open roles? A study by Mercer makes a compelling argument that adopting AI in talent acquisition can make that a reality, while building a targeted and skilled workforce for your organization.

A survey of 477 respondents from various types of organizations suggests that AI in talent acquisition is driving a shift in the way organizations are approaching hiring, and employers will either have to innovate or stagnate.

When asked how they’re using AI in talent acquisition, they said:

• Sourcing and engaging talent for pipeline purposes (40%)
• Analyzing internal recruitment data (28%)
• Creating social posts (28%)
• Helping candidates find the right position (26%)
• Analyzing talent acquisition market trends (24%), and
• Researching compensation data and benchmarks (20%).

In addition, the survey points out that HR pros are starting to use AI to automate many recruiting functions:

• 30% use it to create job descriptions
• 25% use it for communication via mobile apply and SMS texts
• 23% schedule interviews with it
• 22% use AI to assist candidates with the application process
• 20% assess candidate skills related to position requirements
• 18% use it for screening resumes, and
• 18% deploy conversational AI to communicate with potential and active candidates.

Common Barriers to AI in Talent Acquisition

However, 42% of companies say they’re not using AI in talent acquisition because of a lack of:

• systems integration (47%)
• understanding about the efficacy of tools (38%), and
• knowledge of recruiting tools (36%).

If you’re part of that 42%, besides making investments in the right interfaces to integrate AI tools with your pre-existing systems, you’ll need to address the lack of understanding and knowledge with training programs and/or workshops to educate your talent acquisition team about AI tools.

To address concerns surrounding compromised data privacy and possible algorithmic bias, Mercer advised companies to be transparent with candidates about the use of AI in the recruitment process and conduct regular internal audits to ensure that their AI tools adhere to legal and ethical standards.

Before moving toward any full-scale AI implementation, a smart strategy is to initiate a pilot program that allows a subset of the talent acquisition team to experiment with AI tools and evaluate them. Then comes developing a strategy road map for the adoption of AI in talent acquisition, including defining clear goals, metrics and Key Performance Indicators.

In addition, establishing knowledge-sharing platforms, where employees can learn from one another’s experiences and share insights about the usage and benefits of AI tools, can be beneficial.

The Future of AI in Talent Acquisition

According to Mercer, four potential future frontiers of AI in talent acquisition, as well as the post-hiring employee experience, include:

1. Enhancing Diversity, Equity, Inclusion and Belonging (DEIB): Bias in recruiting, including unconscious bias, can cause all kinds of problems for companies. An AI-based talent acquisition strategy has the potential to foster DEIB by leveraging algorithms designed to be unbiased. AI can highlight discrepancies in diversity hiring, suggest corrective measures and promote a more inclusive hiring process.
2. Predictive analytics for job candidates: The more data that’s available about a candidate, and your workforce in general, the more AI will be able to predict a candidate’s career trajectory, cultural fit and compatibility with specific teams or projects. How organizations describe their corporate culture doesn’t necessarily reflect the culture of individual teams. AI-powered predictive analytics have the capability to suggest a candidate’s fit into a respective team in terms of competence, personal traits and characteristics.
3. Interviewing in the Metaverse: Instead of hearing how a job candidate would hypothetically handle a certain situation in their prospective job role, you could assess it for yourself with a virtual/augmented reality simulation. This would give the candidate a more realistic experience of what to expect in their new role.
4. Improved training and development: As your customized AI system becomes more sophisticated as it gets exposed to more data and a variety of scenarios, that can lead to more refined and personalized training and development recommendations and decisions that take an employee’s traits, personal interests and job preferences into account.