JOHANNES MAUNZ
RESPONSIBLE AI
Johannes Maunz, SVP of AI at Hexagon, emphasises:“ Ethical innovation is not something you appoint a single owner for or capture in a framework and move on from. In practice, it is a daily discipline that shows up in how AI is built, tested and used across the organisation.
“ Ethics becomes real at the point where organisations decide how much responsibility they are willing to take for systems in deployment. If an AI system cannot be trusted in the real world, then using it at scale is not an ethical choice.”
For Roop Singh, CEO at Version 1 – the Ireland-based IT services firm – innovating in an ethical fashion begins with purpose.
“ Ethical innovation means starting with a purpose, not just adopting AI because everyone else is,” he says.“ In practice, you have to define from the outset whether an AI initiative will create real benefit and serve a higher business objective, if it requires upskilling and if people are set up to succeed alongside it.”
Accountability enables speed A persistent myth suggests accountability can slow innovation. Johannes challenges this misconception, explaining that what really harms innovation is uncertainty:“ When teams are unclear about how a system behaves, where its data comes from, who is responsible when something doesn’ t work as planned and where accountability lies.
“ Clear guiding principles and their application through the process landscape remove that friction.
JOHANNES MAUNZ
TITLE: SVP OF AI COMPANY: HEXAGON INDUSTRY: TECHNOLOGY
Johannes has spent almost two decades at Hexagon, having progressed from engineering and R & D roles into leading AI strategy. He possesses deep expertise in leveraging Hexagon’ s core competences and spatial intelligence.
When expectations around data use and ownership are defined early, teams are able to move faster with greater confidence.”
Roop’ s assertion is that speed without clarity tends to lead to confusion.
“ It is so important to match technological ambition with leadership, honest communication and support,” he says.“ The trust comes from helping people understand from the outset what’ s changing, why it matters and how they fit into the plan.”
Similarly, Greg highlights the need to balance speed with trust, which itself requires transparency into how AI systems use data, make decisions and evolve over time.
“ Without clear visibility into data sources, context and decision pathways,” he continues,“ organisations cannot confidently guarantee the safety or ethics of their autonomous systems.”
96 March 2026