Chatbot for recruiting and HR: key strategies and use

Hiring in life sciences can feel like trying to find a unicorn with an engineering degree, who’s willing to relocate to Visp and isn’t allergic to GMP. Chatbots are stepping into the scene like caffeinated assistants that don’t sleep, don’t complain, and definitely won’t book their own holiday mid-hiring round.

Whether they’re helping to sift through hundreds of applications or politely rejecting the guy who thinks “Team Player” is a personality type, these tools are quietly revolutionising HR.

In this blog, we’ll walk you through where bots bring value, where they face-plant, and how not to let ChatGPT accidentally invite every applicant to a second interview. You’ll also find practical tips on how to implement chatbots in a way that makes life easier not weirder.

Imagine screening 500 CVs for a clinical research associate role… manually. Now imagine a bot doing it in under 10 minutes.

Read also: Life science industry outlook – 6 disruptive trends for 2025

Let’s clear something up: HR chatbots aren’t just those annoying website widgets asking if you “need help” every five seconds.

These bots are purpose-built tools for tasks like screening, scheduling, onboarding, and internal HR support.

There are two main types of chatbots:

• Rule-based bots: These operate using pre-defined scripts and decision trees. They’re predictable and reliable for standardized tasks but limited in flexibility.
• AI-driven bots: Powered by machine learning, these bots can understand and adapt to different inputs, recognize patterns, and improve over time. They’re more dynamic, but also require careful oversight to avoid unintended behavior.

But let’s be clear: bots are here to handle admin, not to make executive hiring decisions. The minute your chatbot starts developing “gut feelings” about candidates, it’s time to call IT.

Read also: AI- based recruitment: benefit, downside and bias 

When you’ve got 200 applicants and 3 recruiters, someone’s going to cry. Chatbots, when deployed wisely, help you avoid emotional breakdowns and inbox implosions. And to reduce overall recruitment costs. 

What they do well:

• Fast response times: Chatbots can instantly answer common candidate questions, improving engagement and reducing delays.
• High-volume handling: They can process hundreds (or thousands) of applications simultaneously,  something no human team can scale to easily.
• 24/7 availability: Bots operate around the clock, making them ideal for global recruitment or candidates in different time zones.
• Improved data management: Chatbots can automatically collect, structure, and store application data, helping with reporting and compliance.

Real-world examples

A biotech startup cut its screening time from two weeks to two days using a chatbot. Meanwhile, a pharma company automated its interview scheduling with a bot that triggered calendar invitations based on questionnaire responses — reducing time-to-interview and boosting candidate satisfaction.

Despite their strengths, chatbots also have notable limitations. Bots can’t read between the lines. Or sarcasm. Or passive-aggressive “looking forward to your response” emails.

Here’s where the technology still struggles:

• Lack of emotional intelligence: Chatbots can’t interpret tone, intention, or emotional nuance, all critical in candidate interactions.
• Bias risks: If training data is flawed or biased, the chatbot’s behavior will reflect those biases.
• Difficulty with complex queries: Chatbots may provide inaccurate or inadequate responses when faced with questions outside their training scope.

Example

A chatbot once rejected a highly qualified candidate with a “Doctorate in Neuroscience” because the system was filtering only for the exact keyword “PhD.”

Without human oversight, the process can become rigid and exclusionary.

This is why escalation protocols are essential. When a conversation becomes too complex or sensitive, there must be a clear path to escalate the case to a human recruiter.

The arrival of ChatGPT made recruiters collectively ask: can this thing write job ads so we don’t have to?

Answer: Yes. And it can do more — like summarising CVs, writing interview questions, or gently rejecting candidates without sounding like a robot divorce letter.

It can:

• Draft job ads that don’t read like they were faxed from 1992.
• Write outreach messages with actual personality.
• Generate custom interview questions based on role requirements.
• Condense long CVs into readable snapshots.
• Send first-round rejection emails with a touch of fake empathy.

But here’s the catch: ChatGPT doesn’t know what it doesn’t know. It’ll invent experience summaries, miscategorize candidates, and occasionally hallucinate credentials. It’s the overconfident intern of recruiting, brilliant at times, but don’t forget to review any document that goes out because you are still the one responsible.

To successfully implement chatbots in your HR operations, it’s essential to take a structured, strategic approach. Here are five best practices to consider.

Start with a single, well-defined use case — such as interview scheduling or entry-level CV screening — and test the chatbot’s performance. This allows your team to evaluate impact, fine-tune workflows, and address any issues before expanding.

Different bots serve different functions. Some are built for high-volume applicant tracking, while others specialise in onboarding, internal communication, or employee support.

Evaluate your priorities!

Are you looking to save time on screening? Improve candidate communication? Simplify internal HR processes? Choose a platform that aligns with your goals.

• Applicant Tracking Bots (Screening & Recruitment)
  Example: Mya – A conversational AI bot that automates candidate screening, schedules interviews, and answers applicant questions. It helps recruiters quickly narrow down the best candidates from a large pool.
• Onboarding Bots (Employee Integration)
  Example: Talmundo – Automates new employee onboarding by guiding them through company policies, setting up their profiles, and ensuring they have all necessary resources, making the process smoother for HR.
• Employee Support Bots (HR Assistance)
  Example: Spoke – An AI assistant that handles employee HR-related queries about benefits, payroll, and policies, reducing the need for HR teams to answer repetitive questions.

The way your chatbot communicates matters. A friendly, conversational tone can make interactions feel more engaging and natural, especially in candidate-facing roles.

Example

Instead of saying “Your query has been logged,” a more approachable message would be “Thanks! I’ve got your info — let’s move to the next step.”

Personalization and tone consistency go a long way in improving user experience.

No matter how advanced the chatbot, there will always be edge cases where human intervention is necessary.

Best practice
Establish clear rules for when and how cases are escalated to a human recruiter. For instance, candidates with unusual qualifications or complex questions should be flagged automatically for manual review.

Chatbots should never operate on autopilot. Set regular checkpoints to evaluate their performance using metrics like completion rates, drop-offs, and candidate satisfaction scores.

Quarterly reviews can help identify trends, spot issues, and refine both the bot’s logic and content.

Chatbots offer powerful advantages in speed, consistency, and scalability — but they’re not a complete solution on their own. In high-touch industries like life sciences, where precision and empathy are equally important, technology must support human judgment, not replace it.

Used strategically, chatbots free up valuable time and reduce inefficiencies. But it’s the people behind the process who make the ultimate difference in hiring outcomes, candidate experience, and company culture.

And yes, a bot might help you find your next brilliant scientist. But it still can’t explain why he showed up to the interview wearing sandals and socks.