Q&A: Leveraging AI in Talent Acquisition by Piyush Sharma

 

Q: How did you get into the outward communication role?

My journey into roles focusing on outward communication started back in college when I joined a club and eventually became its president. Initially, I was hesitant and avoided meeting new people. However, as responsibilities grew, I found myself selling event tickets and raising funds, which led me to engage more with others. Over time, I discovered a newfound appreciation for connecting with people.

Q: What unique insights or skills do you believe you possess, stemming from an engineering problem-solving background combined with sales communication skills, that many HR professionals might overlook?

My experience in sales gives me a different viewpoint, especially in understanding sales and revenue functions. Unlike the technical metrics used in IT-focused HR, sales and marketing roles lack clear-cut evaluation criteria.

My firsthand knowledge allows me to objectively assess sales and marketing roles. For instance, I can relate to a salesperson selling in North America and understand their tools and challenges. This helps me engage better with candidates.

Moreover, my sales background taught me the importance of researching before having conversations. This habit helps in any interaction, making it more meaningful, regardless of the person's role. It's about showing genuine interest, which resonates well with others. Simply taking time to research someone before a conversation can make a significant difference in engagement.

Q: How has the internet changed hiring, making companies promote their positions over individuals seeking roles? Amid high unemployment, how does this impact companies in presenting their culture to attract top candidates?

Recruiting has changed a lot. Before, people met face-to-face, shared resumes, and had conversations. Now, everything's online, and it's all about quickly matching keywords and applying.

Recruiters spend very little time, about six to eight seconds, looking at resumes. There used to be more meaningful chats, but now it's more about fast decisions due to the high number of applicants.

Both job seekers and companies need to try harder to stand out. Companies use various tactics to attract talent, and job seekers need to show more than just keywords. It's about making a deeper connection in this quick and busy recruitment world.

Q: How can someone create a personalized experience for the top 15 candidates they've shortlisted for an urgently needed position to be filled within the next week or two, considering the fast-paced nature of business today?

In the context of hiring junior-level candidates, online job postings tend to attract numerous applicants due to the minimal background criteria required. However, as experience levels or specializations increase, finding the right fit becomes more complex. This shift necessitates a more personalized recruitment approach.

Initiating personalization early in the recruitment process is crucial, starting with providing feedback, even in rejection situations. Unfortunately, many job seekers seldom receive responses from the companies they apply to, creating a trust gap.

Recruiters play a pivotal role in engaging with candidates, even when rejecting their applications. Every interaction, particularly during rejections, contributes to building employer branding and establishing trust with potential hires. Though seemingly small, these steps significantly enhance the overall candidate experience and personalize recruitment practices.

Q: How do you personalize the recruitment process within a large volume, especially when candidates progress through various stages where their initial qualifications may differ from later assessments?

When lots of people apply for a job, it's hard to give each person personal attention. So, we're using AI to help with this. For instance, if we're looking for a product marketing manager experienced in a specific field, AI helps us review resumes objectively, without human biases.

Let's say there are 100 applicants. AI checks their resumes based on what we need for the job. It tells us who matches well and who doesn't, making it fairer than human judgment.

After picking the top 10 candidates, we personalize our interactions. For the rest, who might not fit now but could in the future, we send them messages explaining where they didn't match but also express interest in working together later. This way, everyone gets a personalized response instead of a generic one.

This helps us treat everyone fairly, giving more attention to those who fit best while still keeping in touch with others for possible future roles.

Q: Why is it important to provide feedback to applicants after the recruitment process? Is it purely an additional step for the recruitment process, or does it hold significance for the applicants themselves?

From my discussions with numerous job seekers over the past year and a half, a recurring pain point for them is the lack of feedback from companies. Many feel left in the dark about why they weren't selected or if their profiles were even considered. This absence of feedback leaves them without insights to improve their skills or understand where they fell short. This sentiment is shared by around 90% of the job seekers I've spoken to—more than 500 in the last 8 to 9 months.

Q: What do you think about the lack of platforms for career exploration and the trend towards becoming generalists instead of specialists in today's evolving job landscape?

The core issue seems to stem from both ends: these professionals are unclear about their career direction, and there's a lack of a suitable platform to explore different career options.

Reflecting on my own career, transitioning from engineering to various roles like Business development to GTM profiles wasn't something I was directed to do. Explaining such career shifts even to my family was a struggle due to the conventional thinking prevalent at the time. Unlike earlier generations with straightforward career paths, today's professionals seek more alignment between their interests and jobs.

In the past, people stuck with one job due to economic and social conditions. However, today, there's more freedom to pursue interests. The job ecosystem is rapidly evolving, and technologies are reshaping job landscapes. I've noticed a significant shift in job roles since I began working.

The crux of the issue lies in the absence of platforms that facilitate career exploration and experimentation. Without such grounds to try out different paths, many are likely to feel stuck in their current situations, potentially leading to a generation out of work.

Regarding skill sets, there's a visible trend towards becoming generalists rather than specialists. Earlier, if you were a developer, the focus remained on developing skills within that field. However, now, there's an inclination towards broader skill sets, like developers also trying to learn design basics.

Q: How are people using AI to become generalists in different fields, like coding or backend engineering, even without specialized skills in those areas?

I believe that despite the rise of AI, which makes tasks easier and more accessible to newcomers, the importance of specialists in specific domains remains crucial. While AI lowers the entry barrier, the expertise and skills built over time hold significant value. People naturally gravitate towards specialization, and this trend might continue even with a shift towards generalization. In fields like HR or any other domain, there will still be individuals with deep knowledge and experience. These specialists possess insights that contribute to creating more comprehensive and long-lasting solutions. Their expertise is unlikely to become obsolete anytime soon, even in the long run.

Q: Will AI trends result in a shift towards creating more generalists while also encouraging individuals to specialize in specific domains?

Certainly! As seen in recent discussions at an AI conference, platforms like AWS are offering comprehensive AI solutions for businesses to develop their AI-driven applications. For instance, a loan company faced numerous inquiries in multiple languages about loan updates. Using AI, they developed a solution that converts inquiries written in various languages, like Hindi, into English. This automated system extracts information from the company's knowledge base, generates responses in an understandable language, and addresses the queries autonomously.

While such automation reduces manual efforts and operational costs, there are scenarios, especially in critical or nuanced contexts, where solely relying on automated replies isn't viable. This is where specialists with expertise step in to refine and improve these systems. Their insights and experiences contribute to enhancing AI systems, identifying what inputs are necessary, and refining automated responses, especially in areas where human interaction remains crucial. Thus, as AI automation expands, specialized human intervention becomes indispensable for improving and advancing these systems further.

Q: What changes do you expect in India's workforce and global recruitment as AI reduces language barriers?

Getting rid of language barriers in hiring will help many skilled people who may struggle with English but excel in technical fields. It's important for companies to value skills over English fluency. This change will open up opportunities for talented individuals who might not be fluent in English but are great at their jobs.

India can promote its diverse languages to create a more inclusive work culture. This shift not only benefits local talent but also opens doors for global opportunities. It's similar in other countries like Indonesia, where language barriers limit access to talented individuals. Removing these barriers means more diverse talent can contribute globally, going beyond just language translation.

Q: How do you foresee technology's impact on the recruitment process evolving over the next five years, potentially reducing manual involvement from the current standard?

Recruitment has been an early adopter of AI, especially since IBM Watson's introduction in 2016. Despite AI's presence, substantial, fruitful results have been limited in the past decade. However, with the evolution and increased accessibility of technology, what we've achieved in ten years may soon be achievable in just a few years.

The initial stages of screening and filtering candidates have remained time-consuming, and technology hasn't yet provided a comprehensive solution. Now, it seems we're at a stage where we can tackle this issue by offering a more personalized experience to job seekers and enhancing the precision of matchmaking, ultimately making the recruitment process more efficient.

Do you work in HR?

Email abhash.kumar@springworks.in and let’s talk :)

Note: All views expressed in this interview are personal and not linked to any organization.