Over the last couple of years, Artificial Intelligence (AI) has revolutionized many industries, one of which is hiring and recruiting. Artificial Intelligence hiring solutions have the ability to analyze massive amounts of data at unprecedented speed, which has reshaped the hiring landscape, offering promising solutions to issues that recruitment professionals have faced for years, such as recruitment bottlenecks and unconscious bias. AI's algorithms can sift through thousands of resumes, identify suitable candidates, and even assess their suitability through sophisticated analysis, all while saving time and company resources.

However, AI has not yet reached the level where it can be trusted to make hiring recommendations without human supervision. While predominantly advantageous to the hiring process, AI is not without its challenges when left to its own "devices." A significant issue that we've seen come to light recently is its potential for bias. Despite efforts to create AI hiring tools that are as objective as possible, these systems have shown skewed candidate recommendations, mirroring the biases present in the data they were trained on. AI bias examples at tech giants such as Google and Amazon have illustrated the need to stay vigilant when using algorithms to make decisions that affect people's lives and livelihoods.

Now, I believe that these examples are not actually the fault of AI, but a manifestation of human biases. You see, AI does not account for personal traits the way humans do, it doesn't "feel," nor does it have emotion- core aspects of expressing biases. You see, currently, Artificial Intelligence is purely analytical- it takes your inputs and filters a large pool of data to give you a desired output.

Think of this process like a math problem. If you ask for the sum of ten numbers, the computer calculates each factor and gives out an output. In the same way, AI uses the data that it's programmed with to give you the desired results. Therefore, we must ensure that the data AI is programmed with is accurate and unbiased. We must also keep in mind that AI can only make decisions based on what it has been taught and exposed to; hence my point on human biases affecting the outcomes and the need for diverse data to be sure AI recruitment tools can deliver unbiased recommendations.

As the AI recruitment market developed and the rapid adoption of AI tools began to shift hiring trends, the team at Pillar realized that there was an impending challenge that few companies were prepared for - namely, the current market of interview intelligence tools was not prepared to handle how humans were biasing results.

To address the issue of bias in AI-driven recruitment, Pillar built interview intelligence software crafted specifically for diversity and inclusion. This meant accounting for:

1. Diverse Datasets: Pillar's interview intelligence was designed with diversity in mind, hence the need for diverse data used to train algorithms. We ensure that our systems do not leverage biased or incomplete data when making decisions.

2. Unbiased Algorithms: Our team of experts has developed algorithms that are free from human bias and discrimination, providing a fair chance for all candidates in the hiring process.

3. Continual learning and adaptation: Pillar's AI is designed to learn and evolve continuously. It's capable of identifying patterns of bias in the incoming data and self-correcting, thus refining the fairness of its screening process over time.

4. Human-AI collaboration: Pillar embraces the philosophy that the best results come from a symbiotic relationship between humans and AI. Skilled recruiters guide the AI, using their expertise to validate the system's recommendations and ensure fairness.

5. Transparency: Pillar champions transparency to build trust with its clients. The AI's decision-making process is not a "black box" — Pillar provides clear insights into what influences the AI's decisions.

The future of AI in recruitment depends on the ability to find and hire the best candidate for the role - and that means eliminating as many opportunities for bias in the hiring process as possible.

Artificial Intelligence Hiring Process

The full benefits of AI in recruitment are still yet to be seen as many of these tools are in a race to evolve to meet the demands of an ever-changing market. Workforce shortages, automation, and diversity are just some of the factors that are driving this evolution. However, the potential is immense - AI-powered recruitment solutions could theoretically reduce hiring time by up to 70%, and cut cost-per-hire by 60%, over the next decade. This is why examples of AI in HR are increasing at a rapid pace.

One of the primary ways that AI is transforming recruitment is through its ability to automate repetitive tasks. By freeing HR professionals from manual, time-consuming tasks, they can focus on more strategic initiatives and interact with candidates in a more meaningful way. For example, AI can screen resumes and conduct initial screenings, allowing recruiters to spend their time engaging with top candidates and building relationships with potential hires. This not only streamlines the hiring process but also adds a human touch that can make all the difference in attracting top talent.

Using an AI-sourcing solution like HireEZ, recruiting teams can gather resumes and profiles from various sources, such as job boards and social media, with a single search. By leveraging natural language processing (NLP), AI can analyze job descriptions to identify the required skills and qualifications for a specific role. This allows recruiters to quickly find the most qualified candidates, without having to manually sift through hundreds of resumes- and connecting HireEZ to a digital assistant like Paradox's Olivia creates an interactive, personalized candidate experience.

Once you have a pool of candidates to assess, that's when Pillar's interview intelligence can have a huge impact- helping you make better hiring decisions and streamline your hiring process.

For most companies, the artificial intelligence hiring process looks something like this:

1. AI-driven Sourcing: Using AI-powered solutions like HireEZ, recruiters can quickly and efficiently gather resumes and profiles from various sources.

2. Resume Screening: AI analyzes resumes and job descriptions to identify the most qualified candidates, saving time for recruiters.

3. Candidate Screening: With the help of chatbots or digital assistants, initial screenings can be automated or in-person (up to you), allowing recruiters to focus on building relationships with top candidates instead of doing "busy work."

4. Interview Intelligence: Pillar's AI-powered interview intelligence plugs into your video interview platform and piggy-backs on your interviews providing unbiased, data-driven insights to help make better hiring decisions and create a fairer hiring process.

5. Human-AI Collaboration: Skilled recruiters collaborate with the AI, using their expertise to validate recommendations and ensure fairness in the hiring process.

6. Onboarding: AI tools by BambooHR and others can also assist in onboarding processes, ensuring a smooth and efficient transition for new hires.

As the recruitment landscape continues to evolve, companies that embrace AI-driven solutions like Pillar will have a competitive edge in attracting top talent and building diverse, inclusive teams.

AI Hiring Tools

So far, we've talked about the artificial intelligence hiring process, mentioned some AI hiring tools, and given you a foundation of why AI tools need to work in collaboration with human recruiters to get the best results. Now, let's talk about how to choose the right AI hiring tools for your organization.

Choosing the Right AI Hiring Tools:

Currently, G2 lists more than 300 AI hiring tools- many with overlapping features. For this reason, navigating the market can be a challenge. How do you choose the right platform for your needs?

1. Identify your specific needs: What are the pain points in your current hiring process, and how can AI tools help alleviate them? Are you struggling with sourcing candidates or identifying top talent? Understanding your specific needs will guide you in choosing the right AI tools.

2. Consider integration capabilities: Can the AI tool easily integrate with your existing HR technology stack? Choose tools that seamlessly integrate with your current systems for a smoother implementation process.

3. Read reviews, test platforms, and gather feedback: Research and read reviews from other companies that have used the AI tool you're considering. This will give you insight into its effectiveness and potential challenges to consider- but, don't stop there, test, trial, and demo the platforms you're considering and gather feedback from as many of your team members as possible before you reach a conclusion. This will help you refine your options into a solution that's the best fit.

4. Look for diversity and inclusivity features: As mentioned earlier, diversity and inclusion are crucial factors in today's recruitment landscape. Look for AI tools that have features built-in to reduce bias and promote diversity in the hiring process.

5. Consider costs: As with any new technology, it's important to consider the cost and return on investment of implementing AI tools into your recruitment process. Look for platforms that offer transparent pricing and measurable results.

Keeping these factors in mind, you'll be able to make a great choice for your team, your culture, and your candidates. If you're currently struggling to find a solution that helps you save time, and money, and make better candidate decisions, book your demo to chat with someone from Pillar. We'd love to show you how our interview intelligence has helped customers increase diversity in hiring and lower employee turnover by over 50%.