HR Summit @ Bucharest Tech Week: What We Heard, What We Think, and What Still Needs to Be Done
What happens when UX meets HR? We attended the HR Masters Summit at Bucharest Tech Week and came back with honest takeaways on AI adoption, trust, and where organizations are still getting it wrong.
On June 17th, we were at the HR Masters Summit, part of Bucharest Tech Week 2026, a nine-day event that brings together professionals from tech, business, and HR. This year's edition included five specialized stages: Innovation, Future AI, HR Masters, Software Architecture, and AI Coding, with 50+ local and international speakers. The HR Masters Summit gathered People & Culture professionals, HR managers, and organizational leaders dealing daily with the same questions: how to hire differently, how to retain people when everything keeps shifting, and what AI is actually doing to the way teams work.
At UXProject, we've been working with that last question for a while now. Not as a debate topic, but as a day-to-day reality, in the product projects we run and in the AI training programs we've built for teams. Our take is straightforward: AI doesn't replace judgment, it amplifies it. But only if you know what you're judging.
What we heard at the summit confirmed the question is real. The practical answers are still being figured out.
Andrei joined one of the day's panel discussions alongside HR leaders and practitioners. Here's what came out of it.
What's actually shifting – and what most organizations still get wrong
One of the opening questions from the moderator set the tone for the entire panel: what is the most important shift already reshaping work today and what do organizations still misunderstand about it?
The most visible change isn't in the tools. It's where the bottleneck moved.
We see this clearly in the two types of clients we work with. Entrepreneurs today can build almost anything they imagined, AI removed most of the technical barriers. But that freedom comes with a cost:
“They usually lose the focus, they get to overengineer something that was supposed to be simple. They forgot what they were building, what was the purpose of that software.”
They don't come to us to design something new. They come to us to simplify something that got out of hand.
Large and medium organizations tell a different story. Most of them have adopted AI in some form. The question is no longer "should we use it" – it's how to build workflows that actually connect to business outcomes. That's where understanding the employee experience matters. Not just the visible pain points, but the latent ones:
“Something that they keep in the back – they know they are there, but nobody tries to attack them.”
One number worth keeping in mind: 85 to 95% of AI and innovation projects fail due to lack of data. Not lack of ambition, not lack of technology. Lack of data, a problem you can address from the start, but only if you ask the right questions before you build anything.
On trust – the part nobody wants to slow down for
Another question from the moderator touched on something that often gets skipped in the rush to adopt: how do you make sure people don't reject AI-powered workflows, or become so distrustful that they simply overwork themselves just to fix what AI got wrong?
“I'm a humanist at core. We are not leaving people behind – this is a message that should be enforced, put in front of everybody, supported by activities around trust, safety, and training.”
If the people using a new AI-powered workflow don't trust it, they'll work around it, double-check everything it produces, or quietly reject it. You won't see it in the adoption metrics. You'll see it in the quality of outputs six months later.
And there's a dimension that often gets skipped in the rush to adopt.
"Businesses should also consider legal aspects, confidentiality – pouring sensitive information into all sorts of black boxes. It's not such an easy topic. I'm personally very interested in the social aspect of it."
Trust is built through transparency, through training, through genuine involvement, not through a company-wide announcement and a new policy document.
One practical place to start
To close the panel, the moderator asked what organizations should actually do differently — what's the one takeaway for those who want to become real architects of the future of work, not just passengers in it.
The answer was simpler than most expect: map the journey first. Whether that's the customer journey or the employee journey, it tells you where to focus before you decide what to automate.
Then run a what-if scenario:
"What if we can change the whole onboarding process? What if we can change the whole recruitment or interview part, try to make it with AI, just see what happens."
Don't implement it immediately. Run the scenario, see what it surfaces. It's one of the fastest ways to find where the real opportunity is, and where the real resistance will come from.
The conversation at HR Masters Summit confirmed something we see in our work every day: most organizations have moved past the question of whether to adopt AI. The harder question – how to do it in a way that's meaningful, trustworthy, and tied to real outcomes – is still open.
That's exactly the work we focus on at UXProject. If your team is navigating the same questions, we'd be glad to talk!
