In this Hello Customer webinar, CEO Bram De Vos is joined by CTO Jonas Beullens for a blunt, practical conversation about AI in customer experience, and why the loudest takes are usually the least useful.
They open with a deliberately provocative claim: AI is threatening your job. Then they quickly pop the balloon. Predictions around “AGI is near” and “whole professions will disappear” have been confidently wrong before, and the bigger point is simple: in the next three to four years, CX is far more likely to be reshaped than erased. The work shifts, but the human layer still matters because customers still prefer humans for many moments that count.
From there, Bram reframes the hype cycle: what looks like a sudden revolution is often a long evolution. LLMs feel new because they became visible to everyone at once, but the underlying trajectory has been building for years. And the people shouting “this changes everything” often have something to sell, or at least attention to win.
Then they tackle the opposite complaint: AI doesn’t know our craft. The answer is “it can, but only if you feed it properly.” Jonas breaks down how language models work, and why outcomes depend heavily on inputs. A simple story makes it stick: a friend failed a golf rules exam using ChatGPT, then passed after uploading the rulebook. Same tool, different context, completely different results.
They bring it back to CX execution with concrete examples from Hello Customer: evolving from basic categorization and sentiment to hyper personalized taxonomies, adding implicit feedback from chats, emails, and call transcripts, and using Ask Isaac to turn questions into consistent, data backed reports. A key warning shows up here too: plain ChatGPT can give confident but inconsistent answers to the same question on the same dataset, which is exactly why prompt enrichment, retrieval, and traceability matter.
On trust, they land on two pragmatic guardrails: verify sources (like Perplexity does, and like Hello Customer does by linking back to knowledge base articles or verbatims), and treat privacy as real risk, not an afterthought. They call out data leakage and model training concerns, and explain why keeping models and processing inside the EU and preventing data reuse changes the equation.
They close on the 2026 direction: the real leap is from insights to action. Automate the low risk work, keep a human in the loop for high risk moments, and aim for fewer dashboards and more guided next steps. The final advice for CX people is refreshingly unglamorous: get your hands dirty, try one small use case each week, share what works, and do not give up.
