Introduction
There’s been no end of buzz about the ways generative AI is already turning recruiting and talent acquisition (TA) on its head. A full 80% of CHROs agree that GenAI has the potential to revolutionize talent management practices, according to a recent poll by Bain. And with innovations like unprecedented efficiency in resume screening, enhanced candidate matching, and predictive hiring analysis underway, it’s true that the potential for total TA transformation can’t be overstated.
Generative AI is artificial intelligence that generates content. This content may be fully original or curated and repurposed from multiple available sources. Learn the basics of this technology by downloading our ChatGPT & DEIB report.
While bringing technological advancement to non-tech roles, generative AI is also a disruptive technology. By making workers more efficient, the increased productivity it heralds for process-driven tasks has the potential to eliminate jobs. On the other hand, GenAI will increase career opportunities for professionals who are familiar with, and upskilled in, this technology. Altogether, within DEIB spaces, there’s a mixed reaction to AI adoption, especially at the pace we’ve seen in the past few years.
GenAI in talent acquisition is an area that has major possibilities and implications in particular, in part because TA is extremely process-driven work. Organizations concerned with DEIB should proactively focus on both the positive and negative impacts presented by this emerging technology. With a spectrum of implications in the workplace, let’s explore how to leverage generative AI for talent acquisition without sacrificing diversity and inclusion.
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Contents
The state of generative AI in talent acquisition: An overview
Generative AI is making waves in the business world, impacting everything from how our teams work on a daily basis to how organizations manage their talent acquisition processes. In the year following the release of ChatGPT in 2022, over half of U.S. companies implemented AI in some way. At that time, 93% expressed clear plans to expand its use. Since that initial boom, the use of generative AI has only grown — and is expected to continue its upward trajectory.
Why generative AI is important
In a 2019 AI episode of the TV news program 60 minutes, the so-called “Oracle of AI,” Taiwanese businessman and computer scientist Kai-Fu Lee, explained plainly how AI will disrupt work as we know it.
While laying out his expectations for how AI affects global job markets, he said, "AI will increasingly replace repetitive jobs. Not just for blue collar work but a lot of white collar work… Altogether in 15 years, that's going to displace about 40% of jobs in the world." He cited everything from driving jobs (chauffeurs, taxis, tour guides) to web development (writing code) being affected by the advancements in automation.
That said, he expects tech markets to boom. His own venture capital firm has funded 140 AI startups and over 10 $1 billion companies — including a few $10 billion companies. As detailed in his book AI Superpowers: China, Silicon Valley, and the New World Order, he expects growing pains but, eventually, dynamic adaptation of employees to a new AI-powered business world. He added:
"In some sense, there is the human wisdom that always overcomes these technology revolutions. The invention of the steam engine, the sewing machine, electricity…have all displaced jobs. And we've gotten over it. The challenge of AI is that this 40% [disruption], whether it's 15 or 25 years [away], is coming faster than the previous revolutions."
Why is this important for talent acquisition? It means that smart organizations will use generative AI not only to find candidates, but also to upskill, reskill, and pivot their current talent.
The current state of generative AI
We don’t yet know whether expansions to the tech market will fully cover expected disruptions to the number of people employed today. What we do know is that jobs involving this emerging technology — roles like a generative AI prompt writer, for example — will expand. We can also expect that GenAI expertise will be an in-demand skill for people in all industries, allowing talent to command higher pay the more AI experience they have. And we know, too, that talent acquisition leaders are already deploying AI at a rapid pace: 52% of HR leaders from a June 2023 Gartner benchmarking session reported exploring potential use cases for generative AI.
In fact, according to Mercer, recruitment and hiring were among the first HR tasks where AI technology was applied. In a 2022 Eightfold AI survey of over 1,000 HR employees, 73% already reported using AI for recruitment and hiring. The Chief People Experience Officer of Automation Anywhere quantified savings from their own use of 50 HR chatbots: an 88% reduction in contract processing time and over 12,000 work hours freed up internally. Though a newly emergent field with little more than a few years of usage data, here is how the accessibility of generative AI is unfolding on the cutting-edge of TA.
Business intelligence:
Forbes points out that AI has quickly proven beneficial in data-driven decision-making across industries. Areas such as demand forecasting, product development, and supply chain optimization are more efficient when a bot can quickly assess large datasets, identify patterns, and spit out a recommendation.
“AI for all”:
Thanks to increased capacity from more advanced AI chips to improved dedicated infrastructure, Forbes also predicts exponentially expanded access for smaller organizations to industrial-grade generative AI.
Expanded options:
Where ChatGPT from OpenAI was the only player at first, the options for generative AI platforms are increasing. Apple plans to integrate a proprietary generative AI called AppleGPT into Apple brand devices and platforms. Google has a similar program in Gemini (formerly Bard), a chat-based AI tool. Developed by the minds at GoogleAI, Gemini is currently available in 40+ languages and 230+ world territories and growing.
Proprietary options:
What’s more, enterprise companies are integrating generative AI into their work platforms. This means providing staff with internal AI ‘sandboxes’ where employees can safely play with features without exposing their sensitive data to the parent AI company (or the entire internet).
4 ways AI is changing talent acquisition
As advanced generative algorithms reach new heights in accessibility and adoption, the use of these tools is transforming the current talent acquisition landscape in critical ways. Talent acquisition is about matching the right person to the right role in the right company (yours), right? GenAI is positioned to have an impact on each of these, including by powering:
1. Better matches, faster.
Generative AI can analyze a larger candidate pool than a human in less time. In the hands of an experienced TA professional, this technology can identify a better suited individual (or individuals) based on skills, experience, and even work culture so that a TA professional can find better matches quicker than ever.
2. Customized experiences.
AI tools can interact with candidates, provide tailored answers to questions, and enhance the overall candidate experience. Where custom interactions were clunky in the past and limited to candidate-provided data, like geographic identification or gender, today’s AI-powered chatbots can offer dynamic responses that adjust to candidate information in real time.
3. Upskilling and pivoting talent.
In our 2024 report on What Diverse Talent Wants, we pointed out that more L&D and upskilling are both top asks from diverse candidates today. Consider that a full 91% of the diverse workers we surveyed said they want to see more upskilling from employers in 2024, and 78% said they want more AI training and L&D resources specifically. Generative AI can be used to identify, outline, and enroll current talent in learning opportunities. It can also notify managers, based on predetermined checklists, to take on a mentorship role when necessary. Mitigating loss during restructuring by providing re-skill and pivot opportunities can go a long way towards improving internal TA, too.
91%
of diverse workers want more upskilling from employers in 2024
78%
want more AI training and upskilling specifically
4. More efficiency than ever.
If you haven’t noticed yet, the major bottom line for generative AI adoption is efficiency. Below you’ll find our list of seven ways to leverage generative AI in talent acquisition. Automating just one of the suggested processes in your organization can majorly reduce your company-wide spend on time.
The future is bright. While generative AI in talent acquisition will continue to evolve, looking at AI in talent acquisition while simultaneously being aware of potential DEIB pitfalls will ensure that you don’t undercut your employer branding efforts in the organization or in your local community.
AI from a DEIB lens
There are challenges and considerations to make when adopting generative AI. From a DEIB lens, talent acquisition is an especially sensitive field to fold AI into because it directly affects diversity in your organization. There are ethical concerns. Bias in AI training data can lead to unfair or even discriminatory outcomes. For inclusive talent acquisition, human expertise in diversity and inclusion is still fundamental. AI is meant to be used as a tool, not a replacement for human judgment. Why? Because we know that DEIB takes more than good intentions and following rules. Belonging (the “B” in DEIB) in TA work, as in other areas, still comes from a very human place of purpose-driven action.
Does AI actually reduce bias?
In short, yes, if implemented well and overseen correctly. The best argument for incorporating generative AI into TA processes is that generative AI follows directions. This makes reduced bias possible (but not automatic). By relying on algorithms, AI can remove or mitigate unconscious bias in the candidate selection process. In fact, AI can be instructed to remove biases. As a machine learning process, the bot will follow directions, perhaps better than a bias-ridden human can.
Advantages of AI in TA
The advantages of AI for enhancing DEIB best practices are seen in TA’s key applications. Using generative AI can do the following three things for your TA department:
1. Increase diversity in your pipeline.
AI scans multiple platforms and finds potential candidates for a more diverse pipeline amongst candidates who may not have applied to your company otherwise. You can even instruct it to ignore historic preferences — for instance, degree requirements, an area of real concern given the elimination of affirmative action in 2023 — and opt for more modern and inclusive profiles.
2. Grow your people-first TA tactics.
AI can generate offer letters, interview questions, and feedback report structures to cut down on busy work for TA professionals. This frees up recruiters’ time for strategic engagement that grows the company-candidate connection on a human level.
3. Reduce application timelines.
Recruiter.com reports that one major issue applicants have with the modern candidate process is that it’s too dang long. AI bots can schedule interviews, make scheduling changes, and pre-qualify candidates to cut down on time and complexity. This will be appreciated by both your teams and applicants. Plus, with a shorter timeline, quality candidates are more likely to stick with the application process.
Disadvantages of AI in TA
1. Letting your guard down can drive disaster.
A major disadvantage of using generative AI in TA is the belief that computers are infallible when it comes to DEIB. In general, technology should not be trusted until well understood and tested in the real world. As an emergent technology, trustworthy generative AI is not quite there yet in the DEIB field. To put it mildly, there have been horror stories. Even with a well-written prompt, generative AI has been shown to mirror biases such as gender bias, racial bias, education bias, and more. Without systems of governance defined at your organization and overseen by a specific accountable party (or parties), AI in TA has the potential to replicate and reinforce rather than remove bias. That’s especially true if your AI systems are drawing on past candidate data that’s never been reviewed or audited for potential biases and DEIB gaps and turning that flawed data into predictive hiring analyses.
"Without systems of governance defined at your organization and overseen by a specific accountable party (or parties), AI in TA has the potential to replicate and reinforce rather than remove bias."
2. There are AI hallucinations.
A hallucination is the term for AI generated information that is presented as fact, but is inaccurate or completely made up. For example, plug the following prompt into Gemini “give me statistics about AI usage in talent acquisition.”
Gemini returns the following:
The global AI in talent acquisition market is expected to reach $7.56 billion by 2028, growing at a CAGR of 18.25% from 2023 to 2028. (Source: Verified Market Research)
Unfortunately, upon searching the VMR reports page, this information is nowhere to be found. The statistics might be buried in some inaccessible report. Or they may be completely fabricated. Be careful not to use uncorroborated information generated by AI without any human fact-checking guardrails.
3. Ease can tempt you not to walk the talk.
When it comes to a budget call, always go with the inclusive option. Let’s use a social impact project as an example. Imagine your company starts a women-led tutoring program in the local school, which happens to be a majority Southeast Asian community. You want to publicize the project and need an image of your tutors working with kids. You have two choices to produce this image. First, you can pay a local photographer to hold a photo shoot, hire representative models (or photograph your actual employees, being careful not to portray students' faces), and produce an image that accurately illustrates your true work in the community. Second, you could feed the image parameters into an generative AI tool that produces “original” art. Though the second option is certainly quicker, more efficient, and less expensive, consider how that choice defeats much of the entire purpose of inclusion. Support a local photographer and the local school, give free PR to the real-life community center, and celebrate your actual employees. For organizations concerned with DEIB, the expense of creating a more inclusive real-life demonstration is an important long-term investment in talent acquisition.
4. Data security dangers are real.
Check with your data security team before using web-based generative AI tools (like those linked in our report). When you feed the AI model, you may potentially leak sensitive data or competitive business information to either the AI developer or a larger cloud. Not all AI developers are transparent with the way they use the content their models are fed. As we have recommended before, find out as much as you can about where your data goes, if it is stored, for how long, if it is used to train other AI models, and the limitations of who and where that data is shared on the provider’s end. Have your team explore the option of an enclosed company-wide cloud so that you can safely play with this technology without risk exposure.
Finally, always review and edit AI-generated content before using or sharing it. This applies whether intended for internal or external circulation. After doing the work of investing in DEIB, don’t tarnish your employer brand over an hour of saved time.
7 ways to leverage generative AI in recruitment
Once data security is established, there are plenty of AI tools available to help recruiters and talent acquisition specialists develop strategies for, source, and communicate with potential talent. Some of these AI tools include:
These powerful tools are available to everyone and are often free of cost. Here are several ways these AI tools can be used by recruiters to streamline the recruitment process.
1. Creating recruitment strategies and proposals
AI tools like ChatGPT can function as a smart sounding board for ideas or concepts that you’re still flushing out. Below, we provide example prompts to understand how this technology works.
If you’re looking for a marketing director in Chicago but you’re based in Mexico, AI can help fill in gaps in local knowledge and strategize the search. Ask your AI tool:
“Create a list of strategies for recruiting a marketing director in Chicago.”
Read through the suggested strategies and ask to elaborate on those that interest you.
AI tools can help you develop a whole proposal for recruitment including budget, KPIs, and key stakeholders.
“Create a proposal for recruiting a 3-person marketing team for [xyz company] and include budget, KPIs, and key internal stakeholders.”
With luck, you’ll have a strong foundation for your recruitment process.
2. Job descriptions
ChatGPT and Merlin AI can help do the heavy-lifting of writing job descriptions for recruiters. Here, it helps to be as specific as possible so that the AI tool can generate a more personalized job description.
“Create a job description for a junior python developer at www.amazon.com based in Denver, Colorado.”
It will return a decent starting point. If you ask an AI tool to “make it DEI-friendly” it will make token mentions of DEI, but this is where a human must step in to ensure it is a truly inclusive job description. The job description will also need to be reviewed by the development team to make sure it has all the appropriate requirements and responsibilities.
3. Email communications
For recruiters doing passive sourcing — i.e. recruiting candidates who aren’t actively job searching — AI tools can be useful in drafting recruitment emails.
Recruiters can also draft email communications to local partners in order to recruit job positions. For example:
“Write an email to [xyz community college] to recruit 2 graphic design interns for a 6-month paid project from amazon music.”
These emails are drafts that will require editing, not just copy-and-paste. Email communications to candidates are important touchpoints that cannot sound generic. Consider this finding from our What Diverse Talent Wants in 2024 research: 73% of underrepresented professionals we surveyed counted “receiving an auto-reply rejection” among negative candidate experiences they’d had. Sixty-four percent said that a negative candidate experience like this had hurt their relationship to a company long-term, and 27% said that after a negative candidate experience, they’d neither apply to that company again or be a customer of it.
4. Employer branding
Use AI tools to generate external-facing content on your website’s career and “about” pages. Your career website should address why an employee should work for your particular company. Having this unique value proposition as an employer is a crucial part of your employer brand. Here, the prompt will need to be a specific as possible:
“Write a summary of why employees should work for xyz company. We offer 100% remote work, unlimited vacation days, free lunch, and a professional development education stipend.”
You can also use ChatGPT to create the foundation of your diversity and inclusion statement.
“Write a diversity statement for www.xyzcompany.com. Make it short and catchy.”
You should of course edit these statements and make them fit for your company’s values, but AI provides a great starting point.
5. Research
If there’s one thing that AI tools like ChatGPT excel at, it’s synthesizing information. Recruiters can use these tools to do recruitment research about locations, salary, competitors, and more. This is useful if you have a geographically dispersed recruitment team.
“What is a competitive salary for an executive assistant in San Diego?”
“List 5 companies similar to www.xyzcompany.com that are also hiring a marketing director. How much do they pay?”
“Where are the best places to find a diverse marketing director in Miami?”
“What are competitive benefits for python developers in Chicago?”
Remember to fact-check these answers with other sources like Indeed and Glassdoor.
6. Interview plans and questions
The interview process is another important responsibility of the recruitment professional, and one where AI can be of assistance. Ask your AI tool to:
“List a 5-stage interview process for a marketing director of a start-up CRM”
“What are 10 interview questions for this position?”
“Which of these questions should be asked at the above stages?”
In moments, you’ll have a solid foundation for conducting the interview process as well as specific questions. Remember to edit and verify these questions with the actual position and through the lens of inclusive hiring best practices.
7. Candidate search
AI is a powerful tool in the candidate search. Recruiters and talent acquisition professionals can input plain text descriptions of a job position and the GPT tool will churn out complex boolean search strings in seconds. These search strings can be dropped into search engines like Google or other platforms like LinkedIn to return resumes and contact information for potential candidates.
Basic boolean operators like AND, OR, and NOT are used in conjunction with the keywords of your job description to zero-in on the exact results you want. An “x-ray” is a type of boolean search string that can be used in Google to search across various platforms.
“Create an x-ray boolean search string to find a senior marketing director based in the usa with experience in start-ups and CRM products.”
Copy and paste the resulting lines into Google for candidate results, and off you go.
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3 key strategies to make AI more DEIB-friendly
There are three straightforward strategies mindful organizations are implementing to ensure that GenAI technology works for both their organization and for the diverse teams they’re trying to build.
1. Transparency
The overall goal of transparency is to build trust. Research has shown that nearly half of Americans (45%) are equally excited and concerned about AI. A commitment to transparency in the use of AI goes a long way in assuaging concerns and demonstrating accountability. Transparency also demonstrates fundamental respect for the clients, employees, and candidates who are interacting with or reading AI-generated content.
- Disclose when AI is or has been used. Use asterisks and footnotes at the bottom of emails or web pages identifying AI-generated content. Ensure chatbots identify themselves as a bot.
- Explain how AI is monitored and reviewed. Include a brief, one-sentence explanation on how AI-generated content is monitored, edited, or reviewed.
2. Create an AI policy in recruitment
There’s no ignoring it: Generative AI is here, and it’s being used in recruitment. The sooner your organization develops policies around its use, the better off you’ll be.
- Create an AI Policy and Oversight Committee. This should be a cross-functional team that includes representatives from all departments, including HR, IT, Data Privacy, Legal, Marketing, and Operations. Don’t be afraid to bring in outside consultants and experts.
- Write a statement against the misuse of AI in the workplace. For now, you don’t have to define what the specific misuses are, but having a statement against the misuse of AI is an important ethical starting point.
- Define what uses of AI are acceptable within recruitment. Will you allow AI to write job descriptions? Will they be copy-and-paste, or are there specific reviewing requirements? These are all valid questions your team should discuss and document.
3. Verify, edit, and use human oversight
Most of the fear surrounding AI revolves around a lack of oversight and regulation. For example, in the case of driverless cars, 87% of Americans want them to have higher testing standards than other vehicles. Organizations need to build-in a robust process of verification, editing, and human oversight in their use of AI within recruitment.
- Verify. Always take information and content generated from AI with a grain of salt. Use other sources such as Indeed, Glassdoor, and LinkedIn to verify key information you receive from generative AI tools.
- Edit. Don’t copy and paste AI-generated content into an email, onto a job description, or onto your website. Always take the time to edit AI-generated content, particularly through the perspective of DEIB. Remember to ask “who is missing?” or “who is being left out?”
- Human oversight. Whether it’s editing AI-generated content, monitoring chatbots, or reviewing AI-based recruitment software, human oversight is essential. There should be designated individuals responsible for reviewing AI-based software, and those individuals should have detailed training and knowledge about how the AI algorithms work.
Next steps and recommended resources
The world of GenAI in talent acquisition is truly just opening up, and with more use (and as this technology continues to evolve), more learnings will continue to stack up. To deepen your understanding of GenAI’s opportunities and obstacles today, we’d recommend exploring:
- The library of recordings from PowerToFly’s Beyond Algorithms: AI’s Impact on Hiring, the Workplace, DEIB, and Beyond Summit
- PowerPro, the first all-in-one diversity recruiting software with 17 million+ diverse candidate profiles and AI Talent Match, helping you to pull a list of diverse candidates whose resumes most closely match each role you have open in seconds.
- Future of Privacy Forum’s Best Practices for AI and Workplace Assessment Technologies — for a framework on how to use AI in hiring and recruitment
- Centre for Information Policy Leadership’s Ten Recommendations for Global AI Regulation— on how to build AI governance into organizational policy
- EqualAI— a nonprofit organization, as well as a movement, focused on reducing unconscious bias in the development and use of artificial intelligence
- The U.S. Equal Employment and Opportunity Commission (EEOC)’s AI Fairness Initiative
- AI Superpowers: China, Silicon Valley, and the New World Order by Kai-Fu Lee
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