Decision Trees versus Large Language Models in Conversational AI Systems: What’s the Difference, and Why It Matters for Talent Acquisition
In the wild, life doesn’t follow a strict path. Neither do conversations.
Intent-based chatbots—known for their structured, flow-chart-like decision trees—have long been the go-to for automating customer service and, more recently, talent acquisition. But for hiring teams aiming to engage candidates on a more personal level, it falls short. Decision trees are great for checklists and FAQs, but real conversations are nuanced, unpredictable, and often spark the kind of authentic connection that helps uncover the story behind the CV. That’s where modern-day conversational AI steps in.
Built to adapt, learn, and evolve with each interaction, conversational AI systems powered by large language models (LLMs) open up the possibility for recruiters to hold natural, human-like conversations with candidates at scale. It’s a powerful approach that turns AI from a mere tool into a true partner, helping recruiters engage with people as well, people.
A Tale of Two Approaches: Decision Trees vs. Open-Ended Conversations
Let’s get down to the difference, starting with old-school intent-based chatbots. Decision trees are structured—think of it as a multiple-choice interview. Each answer leads to a pre-set question. If the candidate goes off-script or tries to ask a unique question, the chatbot reroutes them back to the path, or worse, fails to respond in a way that adds value. Decision tree AI is excellent for straightforward inquiries but struggles when faced with the natural flow of conversation.
Conversational AI, however, listens and adapts. Trained on language and context rather than a rigid script, it engages in a flexible, conversational style that can dig deeper and get to the heart of a candidate’s story. For hiring managers and recruiters, that means more than a simple “yes” or “no” answer—it’s about capturing the nuances of experience, skills, and aspirations, which often get buried in applications and resumes.
Take a recent study by Talent Board, which found that candidates are 50% more likely to rate a hiring experience positively when interactions feel genuine and personalised. With conversational AI, every candidate gets that level of engagement, whether it’s their first job or a senior-level role.
Why Conversational AI Is Made for Recruiting
The recruiting world isn’t just about processing applicants—it’s about making connections. Conversational AI takes that seriously. By fostering an open dialogue, it allows recruiters to get more than a set of data points. With every response and follow-up question, conversational AI gathers insights that make it possible to not only understand a candidate’s qualifications but also assess their fit in a meaningful way.
Flexibility at Scale
Traditional chatbots are constrained by their deterministic structure. They require constant manual updates to add new questions or change the flow of dialogue, making it challenging to stay agile in a fast-paced industry. Conversational AI, on the other hand, is continuously learning from each interaction. If a candidate has a unique response, the AI doesn’t get confused; it adapts, making it flexible enough to handle real-time updates in industry lingo, job requirements, or market trends.
A Human Experience, Enhanced
A 2022 survey by Phenom People showed that candidates interacting with human-like AI reported satisfaction scores 40% higher than those experiencing a scripted conversation. Conversational AI takes recruiting beyond transactional. In every interaction, it draws on its language capabilities to provide personalised responses that feel authentic. It listens, assesses, and provides feedback just as a human recruiter would, allowing teams to engage with thousands of candidates in a way that still feels personal and thoughtful.
How Popp AI Uses Conversational AI to Transform Candidate Conversations
At Popp AI, we saw an opportunity to bridge the gap between efficiency and empathy. By designing a conversational AI tool powered by large language models, we created a platform that not only screens and qualifies candidates but does so in a way that respects and amplifies each individual’s story.
Consider this: if a candidate mentions they’re looking to pivot from finance to tech, our conversational AI doesn’t just skip to the next question. It digs deeper, asking why they want to make the switch, what skills they believe are transferable, and what they hope to achieve. It’s as close as you can get to a real conversation with a recruiter, all while saving teams hundreds of hours each week.
Why This Matters for the Future of Recruiting
The recruiting landscape is changing, and candidates expect more. With talent shortages, increased competition, and a demand for meaningful work, the need for authentic engagement has never been more critical. Conversational AI opens up that possibility, creating a future where recruiters can connect with candidates at scale without losing the human touch.
So, as your team continues to grow and adapt, consider whether a structured decision tree approach meets your needs—or if it’s time to lean into the flexibility and authenticity of conversational AI. It’s not just about efficiency; it’s about engagement. And, ultimately, it’s about seeing every candidate not as a checkbox, but as a person.
