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9 Ways AI Will Change Tech Recruiting – And 3 Ways It Won’t

Written By April Bohnert | September 12, 2023

The world of tech recruiting is abuzz with conversations surrounding artificial intelligence (AI) and its potential impact. Will it replace tech recruiters altogether? Will it render human judgment obsolete? These concerns, while valid, often miss the bigger picture. AI is not here to replace recruiters but rather to empower them, offering invaluable support and transforming the way talent is discovered, evaluated, and integrated into teams.

Rather than being a threat, AI serves as a valuable asset, enabling recruiters to save time, streamline mundane tasks, and gain deeper insights at every stage of the hiring process. A survey by the Society for Human Resource Management found that 85% of HR leaders who use AI for recruitment and hiring said it saves them time and increases efficiency. By understanding how AI can augment their expertise, hiring managers can leverage its power to attract top talent and drive innovation.

From crafting enticing job descriptions and identifying the best candidates to scheduling interviews and enhancing assessments, AI brings unprecedented efficiency and precision to tech recruiting. It automates repetitive tasks, helps mitigate unconscious bias, and generates data-driven insights that enable recruiters to make more informed decisions.

However, amidst this transformation, certain aspects of the hiring process will remain firmly rooted in human judgment and interaction. The ability to engage with candidates on a personal level, assess cultural fit, and manage bias still requires the expertise and discernment of human recruiters. AI cannot replace the nuanced understanding and connection that recruiters bring to the table. But by embracing AI as a key tool in their toolkit, recruiters can leverage its capabilities to streamline operations, unlock new opportunities, and ultimately build stronger, more diverse teams.

9 Ways AI Will Change Tech Recruiting

AI is shaking up tech recruiting in a number of ways, and as AI technologies become more sophisticated, they’ll continue to become more deeply embedded in recruiters’ day-to-day lives. Here are some of the key ways artificial intelligence is changing the tech recruiting landscape.

1. Writing Job Descriptions

In the traditional recruitment process, crafting job descriptions can be a time-consuming task that requires careful consideration of keywords, skills, and qualifications. AI is poised to revolutionize this process by leveraging natural language processing (NLP) algorithms to optimize job descriptions and attract the right talent.

With AI, recruiters can analyze vast amounts of data to identify the most effective keywords and phrases that resonate with potential candidates. By understanding the language and preferences of the target audience, AI-powered tools, such as ChatGPT, can help recruiters create job descriptions that are both compelling and tailored to the specific role. In addition to saving time, this helps job openings stand out in a competitive market, attracting candidates with the right skills and experiences.

2. Sourcing Candidates 

The days of manually scouring various platforms and databases to find potential candidates may not be gone completely — particularly when it comes to sourcing tech talent. But they are getting easier. AI-powered tools have the capability to streamline candidate sourcing, making it faster and more efficient.

Using AI algorithms, recruiters can automate the search process, tapping into multiple platforms simultaneously and analyzing vast amounts of data to identify suitable candidates. AI can analyze job requirements and match them with candidate profiles, significantly reducing the time and effort required to find the right talent.

Moreover, AI can also identify passive candidates who may not actively be seeking new opportunities but possess the desired skills and qualifications. By leveraging AI-powered tools, recruiters can expand their talent pool and uncover candidates that might have been overlooked in a traditional search.

3. Screening Resumes 

One of the most time-consuming aspects of the recruiting process is screening resumes. AI has the potential to transform resume screening, enabling recruiters to efficiently sift through large volumes of applications and identify the most qualified candidates.

AI-powered resume screening tools employ machine learning algorithms to analyze resumes based on predefined criteria, such as keywords, skills, and experience. By automating this process, recruiters can save valuable time and focus their attention on candidates who are the best fit for the role.

The use of resume screening software is already widespread among recruiters. In 2020, 55% of human resource leaders in the U.S. used predictive algorithms to support hiring. That number is poised to increase as AI models become more powerful.

However, the growth of AI resume screening has proven controversial. There have been confirmed cases of bias from these tools in the hiring process. And a wave of legislation and litigation has followed.

Moving forward, recruiters will need to think strategically about how they use resume screening, automating repetitive tasks without introducing additional bias in the process.

4. Scheduling Interviews

Coordinating interview schedules can be a logistical challenge for both recruiters and candidates. AI can simplify this process by automating interview scheduling based on candidate availability and interviewer preferences.

By leveraging AI-powered scheduling tools, recruiters can eliminate the back-and-forth communication involved in finding mutually convenient time slots. These tools can analyze calendars, availability patterns, and time zone differences to suggest optimal interview times. This not only saves time but also enhances the candidate experience by providing a seamless and efficient scheduling process.

5. Engaging Candidates

Candidate engagement is a crucial aspect of the recruitment journey, and AI can play a significant role in enhancing this experience. AI-powered chatbots and virtual assistants can provide timely updates, answer frequently asked questions, and address candidate queries.

By leveraging AI for candidate engagement, recruiters can ensure that candidates receive prompt and personalized responses throughout the hiring process. Whether it’s providing updates on the application status or addressing inquiries about the company culture, AI-powered chatbots can deliver consistent and informative interactions. This level of responsiveness enhances the candidate experience, strengthens the employer brand, and fosters positive relationships with potential hires.

All of these advancements will serve to enhance – not replace – the human aspect of recruiting. Recruiters will still be crucial for engaging with candidates on a personal level

6. Enhancing Interview Assessments

Interview assessments provide valuable insights into a candidate’s skills, knowledge, and potential fit within the organization. And AI has the potential to enhance the interview assessment process by analyzing video interviews for facial expressions, voice tone, and body language.

AI algorithms can analyze these non-verbal cues to provide additional insights beyond traditional assessments. For example, AI can detect patterns in facial expressions to gauge a candidate’s level of engagement or identify potential areas of interest. By leveraging AI in interview assessments, recruiters can gain a deeper understanding of a candidate’s overall communication style, emotional intelligence, and cultural fit. That said, many AI interview assessments still have a ways to go still when it comes to accuracy, transparency, and bias.

AI’s capabilities extend beyond soft skills though. For technical interviews, AI can be leveraged to evaluate signals like code quality, problem-solving skills, technical communications, and coding language proficiency. Following a technical assessment, AI can build a candidate scorecard to save the interviewer time compiling interview feedback as well as provide a detailed snapshot for the hiring team to use when comparing candidates.

7. Providing Deeper Insights 

Data is a powerful asset in making informed recruitment decisions, and AI can help extract meaningful insights from large amounts of hiring data. By analyzing vast volumes of data, AI algorithms can identify patterns, correlations, and trends that might have otherwise gone unnoticed.

AI-powered analytics tools can provide recruiters with valuable insights, such as the effectiveness of different sourcing channels, the success rate of certain interview techniques, or the retention rates of hires with specific experiences. These data-driven insights enable recruiters to refine their strategies, make more informed decisions, and optimize the recruitment process for better outcomes.

8. Streamlining Onboarding

AI can also enhance the onboarding process, ensuring a smooth transition for new hires. AI-powered onboarding platforms can provide personalized learning and development plans based on a new employee’s skills, preferences, and role requirements.

By leveraging AI, recruiters can create tailored onboarding experiences that address individual needs and foster employee engagement. Whether it’s recommending relevant training resources, assigning mentors, answering questions about benefits, or providing interactive onboarding modules, AI can help accelerate the integration of new hires into the organization.

9. Mitigating Unconscious Bias

Unconscious bias has long been a challenge in the hiring process, and AI has the potential to play a vital role in mitigating this bias. Human decision-making can be influenced by unconscious biases based on factors such as gender, ethnicity, or educational background. However, AI algorithms could help remove subjective judgments by focusing solely on objective criteria and qualifications.

AI-powered tools can anonymize candidate information, removing personal identifiable information from resumes and applications, to ensure that initial screening is based solely on qualifications and skills. This approach helps to reduce the risk of unconscious bias seeping into the early stages of the selection process.

Furthermore, AI algorithms can be trained on large and diverse data sets to ensure fair evaluation and minimize bias in candidate assessments. By relying on objective metrics, AI can help recruiters make more inclusive and equitable decisions. 

However, it’s crucial to acknowledge that AI is not immune to biases. Most AI models today carry biases as a result of the data sets used to train them. As such, human oversight remains essential to identifying and addressing any potential bias introduced by the algorithms.

3 Ways AI Won’t Change Tech Recruiting

While AI can serve as a valuable partner in tech recruiting, it doesn’t diminish the power of the human touch. In the high-stakes world of tech recruiting, these three areas, in particular, will continue to require the attention of recruiters.

1. Active Outreach

Even with the remarkable advancements AI brings to tech recruiting, one thing that won’t change is the importance of active outreach by recruiters. Particularly in the world of tech recruiting where talent is in high demand and candidates’ expectations of employers are rapidly evolving. Despite the power of AI tools in sourcing candidates, it is still crucial for recruiters to proactively reach out to potential candidates and build relationships.

Active outreach allows recruiters to tap into passive talent, individuals who may not be actively seeking new opportunities but possess the skills and qualifications desired for a particular role. By engaging with passive candidates and showcasing the unique opportunities available, recruiters can attract top talent that may not have been discovered through AI algorithms alone.

Building relationships with candidates also involves personalized communication and understanding their motivations and career aspirations. Human recruiters can offer valuable insights, answer specific questions, and provide a human touch that AI-powered tools may not fully replicate. By actively reaching out to candidates and establishing connections, recruiters can create a positive candidate experience and cultivate strong talent pipelines.

2. Human Judgment in Assessing Culture Add

While AI can assist in evaluating technical skills and qualifications, it’s not able to identify whether or not someone is a good fit for a team. Assessing the “culture add” and the overall impact a candidate can make within a team or organization still requires human judgment. 

The concept of a culture add involves finding candidates whose unique values, beliefs, and work styles enhance a company’s culture and team dynamics. Understanding and assessing culture add requires contextual knowledge and a deep understanding of the organization’s values, goals, and work environment. 

Human recruiters can engage in meaningful conversations, ask targeted questions, and rely on their intuition and experience to assess whether a candidate will thrive within the team and contribute positively to the company culture.

Additionally, assessing a candidate’s potential goes beyond their technical skills. It involves evaluating their ability to collaborate, innovate, and adapt to new challenges. Human recruiters are adept at assessing a candidate’s soft skills, emotional intelligence, and problem-solving capabilities, factors that are often difficult to quantify through AI alone.

While AI can assist in providing data-driven insights, human judgment remains essential in evaluating the culture add and the potential impact a candidate can have on the organization.

3. Managing Bias 

Despite the advancements in AI, the need to mitigate and manage bias in the hiring process remains unchanged. Bias, whether conscious or unconscious, can inadvertently seep into AI algorithms and perpetuate existing inequalities.

AI systems learn from historical data, which can be biased due to historical hiring patterns or societal biases. If left unchecked, AI algorithms can inadvertently perpetuate bias by making decisions based on discriminatory patterns from the past.

Human intervention is vital in mitigating bias in AI systems. Recruiters need to actively review and audit AI tools used in their hiring process to ensure fairness and inclusivity. This includes monitoring and adjusting the criteria used for candidate evaluation and ensuring diverse representation in training data. This also requires tech recruiters to carefully vet AI vendors, seeking to understand how their AI models were trained and what data is used to evaluate candidates.

Moreover, human recruiters can incorporate structured interviews and standardized assessments that minimize subjective biases. By employing diverse interview panels and establishing clear evaluation criteria, recruiters can mitigate bias and make more equitable and objective decisions.

The responsibility to manage bias extends beyond the use of AI tools. It requires a commitment to diversity, equity, and inclusion throughout the entire recruitment process. Human recruiters play a crucial role in championing these values and creating an inclusive environment where all candidates have an equal opportunity to succeed.

Key Takeaways

As the tech industry continues to evolve, artificial intelligence is poised to bring sweeping changes to the world of tech recruiting. However, amidst this transformation, it is crucial to acknowledge the aspects of tech recruiting that will remain rooted in human judgment and interaction. Recruiters bring a wealth of expertise, intuition, and contextual understanding that complements the capabilities of AI tools.

By embracing the symbiotic relationship between AI and recruiters, organizations can unlock the full potential of tech recruiting. Embracing AI to automate time-consuming tasks, gain data-driven insights, and enhance efficiencies allows recruiters to focus on building relationships, assessing soft skills, and fostering an inclusive and diverse workforce.

This article was written with the help of AI. Can you tell which parts?

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