Generative artificial intelligence (GenAI) is rapidly transforming the landscape of work. While the complete scope of its impact remains uncertain, one thing is clear: the recruiters are majorly interested in GenAI. This interest makes sense—with the potential to advance old-school recruitment methods, improve the hiring process and explore new tech possibilities, generative AI is enticing.
In this piece, we’ll delve into the opportunities that GenAI presents for recruiters, and explore how they are leveraging this new technology to foster creativity, save time and make data-driven decisions.
Artificial intelligence (AI) is technology that enables computers and machines to simulate human intelligence and problem-solving capabilities. GenAI is the latest (and most talked-about) evolution of AI. IBM defines generative AI as “deep-learning models that can take raw data [like all of Wikipedia] and ‘learn’ to generate statistically probable outputs when prompted.” IBM also defines Large Language Models (LLMs) as “a category of foundation models trained on immense amounts of data making them capable of understanding and generating natural language and other types of content to perform a wide range of tasks.”
In practice, these models can be used to create original content including text, images, code, audio and videos. When utilized in recruiting, GenAI can help reshape business workflows, enhance data management capabilities and much more.
Recruiters spend a lot of time and resources managing the hiring process. Consequently, the adoption of AI tools to assist recruiters has grown, with SIA reporting (citing Bullhorn’s Global Recruitment Insights and Data 2024 Industry Trends report) that “more than half of recruitment firms, 55%, began experimenting with artificial intelligence in 2023”.
GenAI tools tend to excel at text generation tasks, such as summarizing a resume to create a candidate summary. Some of the other ways recruiters might utilize GenAI tools include:
Job Text Creation
GenAI tools, including ChatGPT, are often used to create job descriptions, job ads and even LinkedIn posts for jobs. Recruiters leverage these tools to receive ideas and recommendations, or to refine language to be more attractive, inclusive and effective in attracting a diverse range of candidates. Using these tools can help ensure content consistency and also support less confident writers.
Candidate Engagement
GenAI can help recruiters engage candidates more effectively. It could be used to create personalized emails to candidates or power chatbots that allow for real-time responses. A good candidate experience can significantly reduce time-to-fill and elevate the overall quality of hires. Used correctly, GenAI tools can help recruiters provide better engagement at scale, so more candidates have positive experiences with the hiring process.
Screening
Generative AI tools can help screen candidates by analyzing skills assessments rather than relying on a candidate’s credentials. This approach can help recruiters prioritize a candidate’s skills over their background. In addition, these tools can assist recruiters in creating pre-interview briefings, building interview questions and generating emails to communicate with candidates throughout the process.
Onboarding
GenAI tools can help to create a more efficient onboarding experience for new employees. This could include summarizing learning materials tailored to an employee’s role, generating a checklist of tasks from a larger onboarding document or helping employees access resources as they adjust to their new position. This kind of accessible material can help create a positive first impression, laying the foundation for a successful and productive long-term relationship with new hires.
Analytics
GenAI tools can play a transformative role in recruitment analytics by powering data processing, analyzing large amounts of data and leveraging predictive capabilities to help recruiters make more data-driven decisions. This can help recruiters reduce unconscious bias.
Overall, generative AI can be useful in a variety of situations, with it’s specific applications varying depending on the specific task you’re using it for. GenAI has all of the uses listed above, and can also be used for more specialized tasks like sourcing candidates. Building a powerful tech stack and leveraging GenAI tools can not only boost a recruiter's productivity but also free up more time for developing strong connections with candidates.
While GenAI tools have clear advantages, they must be used appropriately to produce good results. Over-reliance on these tools can pose challenges since AI tools are not foolproof.
GenAI can be prone to factual inaccuracies and have a propensity to “hallucinate.” Although GenAI can generate text, it’s not trained to do research, fact-check or cite sources. Because of this, it’s crucial to include human oversight in your GenAI-assisted workflows to check for inaccuracies or errors.
Ultimately, the goal for GenAI tools in recruiting should be to empower recruiters to build strong connections with candidates, rather than to replace recruiters or to make final hiring decisions.
Other things recruiters should consider when looking at GenAI tools include:
Data Quality and Model Training
When selecting AI recruitment technology, it's important to thoroughly vet AI vendors and understand how they developed their AI tool, including the type of data used to train it. The accuracy of AI outcomes depends on the quality of the data employed in training the AI models. High-quality data is important because it directly influences the model's ability to learn and make accurate predictions or decisions.
The specificity of the training data also plays a crucial role. When a model is trained on data that is highly specific to the task at hand, the resulting outputs are more likely to be precise, relevant, and tailored to the particular application. By asking the right questions, organizations can grasp the full capabilities, constraints, and ethical implications linked to AI vendors offering talent management solutions.
Compliance
The data entered into an AI tool in response to a prompt is sometimes used to continue training the model. Therefore, it’s equally important to understand what happens to the data once it’s shared. For instance, if a recruiter employs an AI tool to summarize a resume, they are essentially transmitting data beyond their organization's boundaries, potentially violating data privacy laws. Therefore, it's essential for recruiters to determine how the data is safeguarded, stored, and anonymized before it’s used.
Bias
It’s widely recognized that unconscious biases often influence human decision-making. If an AI model is trained on biased data, it can replicate these biases in its outputs. Thus, it is crucial to scrutinize the training process of an AI solution to ensure that its data does not perpetuate stereotypes or inequalities. Recruiters can further mitigate bias by combining AI tools with human oversight and implementing proactive measures such as anti-bias training. This integrated approach helps ensure fairer and more equitable outcomes in the recruitment process.
GenAI is a powerful tool, with strong implications for recruiters and candidates alike. To learn more about how recruiters are leveraging this technology in 2024, read our Recruiter’s Guide to Generative AI. In it, you’ll learn: