How artificial intelligence agents are transforming the way we research, design and make decisions.
What if your new team-mate were an AI agent you could delegate tasks to in order to uncover valuable insights? It is no longer just about using tools — it is about collaborating with systems that act autonomously.
Artificial intelligence agents have moved beyond being a technical promise to become active members of design, product and innovation teams. They are more than assistants: they perceive, reason and execute based on concrete objectives. If you work in Design Research or user experience, this transformation is not science fiction: it is your new professional context.
What is an artificial intelligence agent?
An artificial intelligence (AI) agent is a system designed to act autonomously towards a specific objective, interacting with its environment and adapting its behaviour according to context.
Unlike a "passive" AI that responds when asked (such as a classic chatbot), an agent:
- Has specific goals.
- Perceives its environment (for example, documents, conversations, tools).
- Makes decisions and takes actions independently.
- Learns over time and adjusts its strategies.
From software as a tool to agent as collaborator
For decades, software has been a tool: something the professional uses to carry out tasks. You gave the commands, you made the decisions, you analysed the results.
With AI agents, that logic changes profoundly.
You are no longer simply using the tool. The agent works for you.
You give it an objective, and it makes decisions, executes tasks and delivers results without requiring your constant intervention. It is like moving from using Excel to having a colleague who understands which formula to apply, when and why — and does so automatically.
From deterministic to generative: a paradigm shift
David Hurtado, Technology Strategist at Microsoft, puts it clearly: generative AI behaves more like a person than a tool.
Classic software is deterministic: if you give it the same input, it always produces the same output.
Generative AI, on the other hand, is non-deterministic. Like humans, it can give you different responses to the same stimulus, because its reasoning depends on context, statistical inference and how it has learned to represent knowledge.
This means that an AI agent does not merely "know things" — it interprets, proposes, adapts. That makes it powerful, but also unpredictable. And that is precisely why your role as a professional does not disappear: it transforms into that of guide, trainer, critic and facilitator.
And in Design Research — what can it do?
Imagine a research agent that:
- Detects new relevant questions from technical support conversations.
- Generates research plans and recruits compatible participants.
- Conducts automated interviews using synthetic voice and emotional modulation.
- Extracts insights and cross-references patterns in real time with other studies.
- Adjusts its hypotheses based on team feedback.
This is not a fantasy. Startups are already working on agents with similar capabilities, such as Maisa. According to Anna Piñol, partner at NFX (a Silicon Valley investment fund specialising in emerging technologies) and an expert in agentic architectures, these systems are designed with a focus on traceability, organisational context and distributed capabilities. That is the key difference between a useful system and a risky one: being able to understand how it arrived at each conclusion.
How does this change your role?
If you were previously the one conducting interviews, you might now be the one training the agent to conduct them. If you previously carried out qualitative analysis, you might now be the one who verifies and synthesises the system's analysis. Your value will shift:
From doing → to designing processes.
From collecting → to selecting and supervising.
From executing → to questioning and correcting.
From being a node → to being an orchestrator.
Are we ready?
As Martin Hilbert, professor at the University of California and former digital adviser to the United Nations, points out, the most powerful technologies are those that force us to redefine ourselves. This is one of those moments. Collaboration with agents is not optional — it is inevitable. But the way that collaboration unfolds — human, ethical, critical and meaningful — will depend on us.
Are you going to be replaced by an agent?
No. But you could become irrelevant if you do not learn to work with them.
And if I am afraid…
Anxiety in the face of change is legitimate. The challenge is not to deny that feeling, but to transform it into adaptive energy. The emergence of agents does not eliminate jobs: it redefines their nature. Mechanical, repetitive or low-strategic-value tasks will be automated, yes. But that opens up space for human professionals to focus on what cannot be replicated: empathy, contextual creativity, ethical decision-making, and the ability to connect dispersed knowledge.
Rebeca Hwang, professor at Stanford and Harvard and a leading voice in human innovation, would pose a provocative question: Are we creating technologies that replace us, or that invite us to rediscover what is most valuable about being human? The key is not to compete against AI, but to understand how to collaborate with it to amplify your professional impact. Those who grasp this first will not only protect their role — they will elevate it.
Watch the interview
We are already exploring this path
At Interactius, we are actively researching how AI agents can enhance research work within design and product teams. We want to go beyond the hype: building solutions that are useful, ethical and deeply human. We believe the best technology is the kind created from people, to help us better understand people.
