5 things you need to know about AI in talent acquisition
The rise of generative AI in talent acquisition
We've compiled a list of five things you need to know about AI in hiring talent. By staying informed about the latest developments and leveraging the benefits of AI while maintaining a human touch, you can confidently navigate this rapidly-evolving field.
What is AI?
To answer this question, we first need to differentiate between three terms - robotic process automation (RPA), artificial intelligence (AI), and machine learning (ML) - since each has its own functionality and requires a different level of human intervention.
While RPA is designed to automate repetitive and tedious tasks, freeing up people's time and allowing them to focus on more creative challenges, it can only operate according to pre-defined rules. By contrast, AI can learn from data and adapt to new tasks, improving over time. To do so, AI relies on various forms of machine learning. Predictive talent analytics (in which past data is used to predict future results) and natural language processing (leveraged to interpret human language) rely on machine learning.
What differentiates artificial intelligence from RPA is AI's ability to make decisions and issue recommendations with less human input.
What is generative AI?
Contrary to other types of AI, generative AI not only recognises patterns and makes predictions based on data but also (as the name suggests) generates new content. Generative AI learns through something called generative adversarial networks (GANs). In this process, a "generator" creates new data and a "discriminator" evaluates it, making a distinction between real and fake data, and thus "teaches" the generator which one is which.
However, this learning process requires time, sufficient input of data, and a human-guided and ethical approach. Anyone who has experimented with ChatGPT knows that sometimes it produces answers that sound convincing but don't make sense. The most significant limitations of generative AI today include creating content that is false, misinformed, biased, or prone to unethical or even criminal use.
What is AI in talent acquisition?
AI can enhance decision-making, improve efficiency, and reduce risks, enabling organisations to streamline hiring processes. Some of the most common uses of AI in recruitment include:
Candidate outreach
AI tools help with targeted communication across social media and online platforms. Some of these tools can ensure that the wording of job ads is free from gender bias, which helps to attract female talent to traditionally male-dominated industries. When Pontoon was responsible for closing the gender gap for a technology customer, we invested in a tool specialising in text analysis to optimise job postings with verbiage that appeals to female candidates, allowing the customer to reach their gender quota goals.
Candidate assessment
AI-powered tests and video interviews with face recognition software can help recruiters get a sense of the candidate's personality, confirming their intuitions and ensuring a good cultural fit with the company. Additionally, these tools can improve testing and validating candidate skills. When filling technical roles for a financial services customer, Pontoon implemented an assessment tool that used eye-tracking software to ensure test integrity and automatically ruled in and ruled out candidates. By leveraging technology, we hired 175 Java developers in just nine days.
Other AI assessment tools allow companies to bypass the traditional interview process, significantly decreasing time-to-fill rates. For example, when bulk-hiring contingent administrative workers, Pontoon leveraged a third-party assessment tool to prequalify, confirm, and onboard 200 supplier-identified candidates in less than four weeks.
AI-powered business intelligence
These tools transform vast amounts of operational, market, and regulatory data into actionable insights. With intuitive natural language assistants and user-friendly interactive dashboards, AI-driven analytics empower organisations to make faster, data-backed decisions while staying ahead in a dynamic talent landscape.
Other areas where AI can add significant value include: skills mapping, talent matching, forecasting workforce demand, and more.
What does AI lack that humans have?
Personalised approach: AI can analyse large amounts of data and make recommendations based on patterns, but it cannot provide the same level of personalised attention as humans.
Empathy and emotional intelligence: AI cannot understand and empathise with human emotions, which is essential in providing effective talent management solutions.
Flexibility and adaptability: AI performs specific tasks and may struggle to adapt to unexpected situations that require innovation.
Human judgement: Although AI can provide data-driven insights, it cannot replace human judgement entirely.
Why balancing AI innovation with the human touch?
It's clear that AI has the potential to significantly improve and streamline certain aspects of talent acquisition. However, it's important to remember that it can't fully replace the vital human touch required to build strong relationships, understand unique needs, and provide personalised support to clients and candidates. As the industry continues to evolve and integrate new technologies, it's crucial for talent acquisition professionals to strike a balance between leveraging the benefits of AI and maintaining the essential human element that is critical for success in this field.