How to Use AI in Hiring: Techniques and Tools

The AI revolution is sweeping across sectors, transforming everything from customer service with chatbots to operations with machine learning data analysis tools. Hiring processes are no exception. While the integration of AI in recruiting may seem like a recent phenomenon, it’s actually a well-established part of talent acquisition. Long before AI became a household conversation in 2023, algorithms were quietly at work behind the scenes on platforms like LinkedIn, matching job seekers with their next opportunity, and within recruitment software, scanning resumes for standout traits. As AI technology evolves, a surge of new tools is aiming to further expedite the recruitment cycle, promising efficiency for employers and better job-matching for seekers.

Yet, the momentum of AI in hiring is not without its challenges and ethical questions. Algorithms designed to simplify recruitment can inadvertently perpetuate existing biases, casting a shadow over the promise of AI as a tool for fair hiring. Plus, letting algorithms take the wheel can sometimes mean we lose that personal touch so crucial to the hiring process. This article peels back the layers of AI in recruitment, weighing its ability to innovate against the risks it poses. We’ll talk about how to embrace AI to improve the hiring process, ensuring that the human element in hiring stays intact.

Article summary:

• The use of AI in recruitment can lead to faster hiring, cost savings, and potentially less biased decision-making, but also poses risks such as privacy issues and a potential decline in candidate experience.

• Specific AI hiring tools like Phenom AI, which assists in candidate sourcing and screening, and Textio, designed to optimize job listings for inclusive language and better performance, can support recruitment at companies.

• Best practices for AI in hiring involve regularly auditing algorithms for bias, ensuring compliance with data protection laws, and preserving human interaction in the recruitment process to provide a balanced candidate experience.

What is AI in hiring?

AI in hiring refers to the application of artificial intelligence technology, including machine learning algorithms and natural language processing, to automate and enhance the recruitment process. This technology assists in sourcing, screening, and evaluating job candidates more efficiently and effectively than traditional methods. By analyzing large sets of data, AI can identify patterns and insights that help match the right candidates with the right job opportunities.

Here are a few examples of AI in hiring:

• AI-powered chatbots can engage with candidates and answer their questions in real-time, improving communication and candidate experience.

• Machine learning algorithms sift through resumes, identifying key skills and experiences that match job descriptions.

• Predictive analytics are used to forecast the future performance of applicants, helping to make more informed hiring decisions.

• Automated scheduling software organizes interviews and coordinates calendars without the need for manual input, saving time for recruiters.

The benefits of AI in hiring

In LinkedIn’s Future of Recruiting 2023 report, 74% of respondents are hopeful that AI will automate repetitive tasks to prioritize strategic work, while 67% hope that these tools will make it faster and easier to source candidates. This optimism reflects a growing trend in recruitment to embrace AI as a means to streamline the hiring process and change the way organizations connect with talent on a global scale. Here are some benefits of AI in recruitment and hiring:

Supports the early screening process

AI can improve the early screening process by quickly analyzing vast amounts of resumes to identify the most suitable candidates. It can accurately parse information from a resume, such as education, experience, and skills, and match them against job requirements, ensuring that only the most relevant applicants move forward. This level of automation permits recruiters to bypass the initial, often tedious stage of manual resume review. Consequently, it directs attention to vetted candidates, streamlining the pipeline and elevating the overall quality of the applicant pool.

Makes hiring faster and more efficient

Using AI accelerates the hiring cycle by automating communication with candidates, scheduling interviews, and providing swift feedback. By handling these administrative tasks, AI tools like applicant tracking systems (ATS) can significantly cut down the time recruiters spend on logistics. The immediacy of AI’s data processing capabilities also means that job postings can be filled more rapidly, reducing the time positions remain vacant. This efficiency is not only beneficial for the hiring organization but also improves the candidate experience by delivering timely updates and interactions

Potential to reduce unconscious bias in hiring

AI has the potential to create a more equitable hiring landscape by minimizing unconscious bias. By focusing on predetermined skills and qualifications, AI-powered tools can ignore demographic factors such as age, gender, and race that might inadvertently influence a recruiter’s decision. This type of analysis may help foster diversity in the workplace by ensuring candidates are evaluated on their merits. Plus, some AI tools are explicitly designed to help organizations meet their diversity and inclusion goals by analyzing hiring patterns and suggesting corrective actions.

Allows recruiters to focus on more complex hiring tasks

By taking over routine tasks, AI frees up recruiters to concentrate on the more nuanced aspects of hiring, such as building relationships with candidates and understanding the deeper needs of the hiring managers. Recruiters can invest more time in strategic planning, employer branding, and improving the candidate experience—elements that AI cannot replicate. This shift towards high-value work improves the effectiveness of recruitment teams and leads to more satisfying and impactful roles for recruitment professionals.

Cost savings in the recruitment process

Incorporating AI in hiring can lead to cost savings for organizations. By automating routine tasks, companies can reduce the manpower needed for recruitment operations, lowering overall labor costs. Additionally, the improved speed and accuracy in hiring reduce the cost per hire and the likelihood of expensive mis-hires. The long-term financial benefits also include retention improvements due to better-matched candidates, ultimately affecting the organization’s bottom line positively.

The risks of AI in hiring

While AI in hiring can offer advantages in terms of efficiency, it also introduces risks that organizations must carefully navigate—from avoiding the amplification of bias to preventing over-reliance on technology that could lead to a mismatch between job requirements and candidate capabilities. Here are some challenges to think through before implementing AI in hiring:

Privacy and legal issues with candidate data collection

The use of AI in hiring comes with the collection and analysis of candidate data, which raises privacy and legal concerns. As AI systems require large datasets to function effectively, there is a risk of sensitive information being mishandled, leading to potential data breaches. Legal issues may also arise from non-compliance with regulations like GDPR or the CCPA, which dictate strict rules on data collection and storage.

Transparency problems around hiring decisions

AI’s complex algorithms can sometimes act as “black boxes,” providing little insight into how decisions are made. This lack of transparency can be problematic for candidates who receive adverse decisions and want to understand the rationale behind them. It can also lead to challenges in auditing and improving the decision-making process, as it’s difficult to scrutinize something that isn’t fully understood.

Potential to exacerbate bias in hiring

Although AI has the potential to reduce bias, it can also inadvertently exacerbate it if not carefully managed. AI systems learn from existing data, which may contain historical biases, and without proper oversight, these systems can perpetuate or even intensify such biases. This can lead to discriminatory practices and a lack of diversity in the workplace.

Worsening the candidate experience

While AI can streamline certain aspects of the hiring process, over-reliance on automation can make the experience feel impersonal and transactional for candidates. The absence of human interaction can leave candidates feeling undervalued and disengaged, especially if AI-driven communications are not thoughtfully crafted. A negative candidate experience can harm your organization’s brand and deter top talent from applying.

Chance for candidate mismatch

AI tools are programmed to match candidates to job descriptions based on predefined criteria, which may not capture the nuances of a role or the company culture. There is a risk that the AI might prioritize candidates who are good on paper but may not be the best fit in practice. This can lead to hiring individuals who excel in technical competencies but fall short in soft skills or cultural alignment.

AI hiring tools to add to your recruitment process

AI hiring tools are changing the recruitment landscape, offering innovative solutions to traditional hiring challenges. These tools leverage artificial intelligence to streamline the screening, assessment, and selection of candidates, transforming the way organizations approach talent acquisition. Here are a few tools to explore for your team’s recruitment process:

1. Phenom AI

Phenom AI’s Intelligent Talent Experience platform leverages AI to improve the hiring process, offering features like AI Discovery for optimal candidate sourcing, an AI-generated fit score for efficient talent qualification, and personalized job recommendations to enhance the candidate and employee experience. The platform automates time-consuming tasks such as sourcing, screening, and scheduling, while providing actionable insights into talent analytics to help fill roles effectively. Additionally, Phenom caters to various roles within organizations, including recruiters and HR managers, and spans multiple industries, emphasizing compliance with CSA, GDPR, ISO, and SOC II standards to ensure data security and privacy.

2. Textio

Textio provides data-driven inclusion guidance to optimize job posts and other recruitment communications for diversity, aiming to attract a broad audience and top talent efficiently. The platform offers real-time predictive Textio Scores to assess and improve the diversity of your candidate pipeline, along with suggestions to eliminate biased language. Features like bias interruption, AI safeguards, trackable analytics, and integrations with major recruitment and communication platforms help teams recruit smarter, reduce hiring time, and foster an inclusive workplace culture.

3. Fetcher

Fetcher provides AI-powered tools to assist recruiters in sourcing candidates, reducing the time spent searching for potential hires by using technology to identify profiles that match job requirements. The platform includes features such as automated email sequences, verified contact information, and integrations with existing ATS and CRM systems. Fetcher also allows for the setting of diversity-focused search criteria and offers analytics to track the effectiveness of recruitment efforts.

4. Pymetrics

Pymetrics provides a suite of tools for talent acquisition and management, using gamified assessments to gauge cognitive and emotional traits, focusing on potential rather than past experience. Their AI algorithms are custom-built for each company to ensure ethical hiring practices and are regularly audited for bias to support a diverse workforce. The platform offers solutions for various HR needs, including reskilling, career planning, and leadership development, while emphasizing fair and data-driven talent evaluation.

5. Manatal

Manatal is an advanced AI-powered recruitment software that streamlines the hiring process with features such as candidate sourcing from multiple channels, including LinkedIn and job boards, and an intuitive ATS. It enhances candidate profiles with social media data, offers AI-driven candidate scoring for better match recommendations, and provides a customizable recruitment CRM for agencies and headhunters. The platform supports a mobile application for on-the-go recruitment, ensures data privacy compliance with regulations like GDPR, and offers transparent pricing plans.

6. HireVue

HireVue is an AI-enhanced hiring platform that offers video interviewing and assessments to help organizations identify and unlock candidate potential beyond traditional achievements. It streamlines the recruitment process with structured interviews, automated workflows, and ATS integration to facilitate hiring at any time and from any location. The platform is designed for various hiring needs, including hourly, campus, professional, and technical roles, and is used by brands to reduce time to hire, cost per interview, and to support diversity and inclusion in hiring practices.

7. LinkedIn

LinkedIn is enhancing its talent acquisition capabilities with Recruiter 2024, an AI-assisted recruiting experience that speeds up the process of finding qualified candidates by using natural language processing and insights from LinkedIn’s vast data on professionals, companies, and skills. The platform is also introducing AI-powered coaching in LinkedIn Learning, offering real-time, personalized advice and content recommendations tailored to individual career goals and skill interests. Additionally, LinkedIn plans to roll out CRM Connect, an integration that streamlines the recruitment workflow by connecting LinkedIn Recruiter with Candidate Relationship Management systems.

Best practices for integrating AI in your company’s hiring process

Embracing AI in your company’s hiring process can boost efficiency and candidate engagement, but its implementation must be strategic and thoughtful. To ensure a smooth integration and maximize the benefits of this technology, here are some best practices that can guide your organization’s adoption of AI in hiring:

1. Maintain legal compliance in AI deployment

When integrating AI into hiring, stay abreast of and comply with all relevant employment laws and data protection regulations. This includes understanding how AI tools collect, store, and process candidate data, and ensuring these processes meet legal standards such as the GDPR in the EU or other local privacy laws. Companies should work closely with legal experts to continuously monitor and adapt to regulatory changes. This diligence protects the organization from potential legal ramifications and also builds trust with candidates.

2. Ensure transparency and consent in AI usage

Transparency is key to ethical AI implementation in hiring. Companies should clearly communicate to candidates how AI is being used in the recruitment process and what data is being collected. This includes obtaining informed consent for data collection and use, and providing candidates with information on how decisions are made. By being open about the use of AI, companies can alleviate candidate concerns and foster a sense of fairness and respect for applicant privacy.

3. Provide management training on responsible AI use

Management and HR professionals should be trained on the capabilities and limitations of AI in hiring. This training should include understanding the ethical implications of AI, how to interpret AI-based recommendations, and when to override automated decisions. Educating decision-makers ensures that they can effectively manage AI tools, use them responsibly, and maintain a human perspective in hiring decisions. This is essential for balancing the benefits of automation with the need for human judgment and discretion.

4. Audit AI for non-discriminatory practices

Regular audits of AI tools are necessary to ensure they don’t inadvertently discriminate against certain groups of candidates. By examining the algorithms and the data they use, companies can identify and rectify any biases that may exist. These audits should be done by diverse teams or third-party experts to provide an objective assessment of the AI systems. Proactive checks for fairness help to maintain ethical hiring standards within the company.

5. Hold onto the human side of talent acquisition

While AI can improve the efficiency of the hiring process, it’s essential to preserve the human element. Personal interactions, cultural fit assessments, and relationship-building are aspects of recruiting that AI cannot fully replicate. Companies should ensure that AI is used to augment the recruitment process, not replace it. This means having human professionals involved in key hiring stages, especially interviews and final decision-making, to provide the empathy, intuition, and understanding that AI lacks.

Accelerate your AI projects with DigitalOcean GPU Droplets

Unlock the power of NVIDIA H100 GPUs for your AI and machine learning projects. DigitalOcean GPU Droplets offer on-demand access to high-performance computing resources, enabling developers, startups, and innovators to train models, process large datasets, and scale AI projects without complexity or large upfront investments

Key features:

• Powered by NVIDIA H100 GPUs with 640 Tensor Cores and 128 Ray Tracing Cores

• Flexible configurations from single-GPU to 8-GPU setups

• Pre-installed Python and Deep Learning software packages

• High-performance local boot and scratch disks included

Sign up today and unlock the possibilities of GPU Droplets. For custom solutions, larger GPU allocations, or reserved instances, contact our sales team to learn how DigitalOcean can power your most demanding AI/ML workloads.