The conversation that was not really about AI

Walking through ARMA 2026, I expected artificial intelligence to dominate the conversation. It was certainly present, but by the end of the conference I realised that AI itself was not the main story.

The real story was adaptation.

Again and again, I heard people returning to the same underlying pressures: workload, uncertainty, financial constraint, changing expectations, professional identity and the growing complexity of research environments. The topics were different, but the deeper question was often the same.

How do research professionals continue to create value when the environment around them is changing faster than the institutions they work within?

That question stayed with me because it feels larger than AI. It speaks to the future of research management itself.

Why people are not really tired of AI

The phrase “AI fatigue” appears increasingly often in our sector. It suggests that people are tired of hearing about artificial intelligence, and perhaps there is some truth in that.

But I left ARMA wondering whether we have misunderstood the problem.

People may not be tired of AI itself. They may be tired of conversations that remain theoretical. They may be tired of hearing about transformation while still facing increasing workloads, fragmented systems, limited resources and unclear guidance.

Many individuals are already experimenting because they need practical solutions now. At the same time, many institutions are still developing policies, governance frameworks, training and adoption plans. This creates a gap between individual adaptation and organisational readiness.

That gap may be one of the defining challenges of this moment.

What becomes valuable when information becomes abundant

AI raises uncomfortable questions because so much of research support involves working with information. We search, interpret, organise, coordinate and communicate. When machines can summarise documents, analyse text and structure information quickly, it is natural to ask where professional value sits.

Interestingly, ARMA suggested an answer.

The more technology can handle information, the more important human judgement becomes. Research management is not only about moving information through systems. It is about understanding context, building trust, interpreting risk, supporting decisions and knowing when something needs a human conversation.

AI can process information, but it cannot determine institutional priorities. It cannot understand culture. It cannot build relationships. It cannot take responsibility for difficult decisions.

As routine cognitive work becomes easier, the distinctly human aspects of research management become more visible.

Self-agency may become the most important professional skill

What struck me most at ARMA was not technological optimism or technological anxiety. It was the importance of self-agency.

One of the clearest examples came from a practical poster presentation. Faced with a 300-page Horizon Europe work programme, colleagues had used AI to create a searchable resource that made the information easier to navigate (An AI-Inspired Tracker for Horizon Europe Funding Management, UoS, Claudia Barbosa ,Ying Chen and their team).

The technology was interesting, but the mindset was more important.

Someone saw a difficult, time-consuming task and decided it did not have to stay that way. They started with a real problem, tested an approach and shared what they had learned.

To me, this is what self-agency looks like in practice.

It does not mean acting without governance or ignoring risk. It means taking ownership of learning. It means looking at your own work with curiosity and asking where things could be improved. It means recognising that change is already happening and choosing to participate in shaping it.

This is also why communities such as AIRON matter. They create spaces where research professionals can move beyond abstract discussions and learn from practical examples, shared questions and honest conversations about what AI means for their work.

The real opportunity

ARMA 2026 left me with the feeling that research management is entering a new phase.

For many years, research professionals have been valued for their ability to manage complexity. Increasingly, they may be valued for their ability to help institutions adapt to complexity.

Artificial intelligence is only one part of this story. Financial pressures, changing expectations, workforce challenges and organisational uncertainty are equally important. AI simply makes these changes more visible.

The real opportunity is not technological alone. It is the opportunity to rethink where human expertise creates value, to design work differently, and to create more space for judgement, relationships, leadership and strategic thinking.

The future of research management will not be determined by artificial intelligence alone.

It will be shaped by the people who decide how it is used, where it creates value, and what responsibilities must remain fundamentally human.

That, for me, was the real message of ARMA 2026.