A new technology quickly creates a new question. Should we use AI here? Can we automate this process? Do we need a new platform? Should we replace an existing system? Those are understandable questions, but they often start too late in the conversation. Before deciding what to build or which technology to introduce, there is usually a more important question to answer first: what are we actually trying to change?
That sounds simple, but in practice it is not. Many organizations have years of existing processes, systems, integrations and ways of working behind them. Something that looks like a technology problem can just as easily be a process problem, an organizational problem or a problem with unclear ownership. A slow workflow does not automatically need AI. A fragmented customer journey is not always solved by another platform. And introducing a new tool does not necessarily improve the way people work.
The more technology becomes available, the more important it becomes to understand the problem behind the request.
From what can we build to what should we change
Earlier in my career, many digital conversations started with what needed to be designed or built. A website, an application, an integration or a new digital service. The challenge was often to turn a clear requirement into a working solution.
Today, I find the conversation before that point increasingly interesting. What is causing friction? Which part of the process really slows people down? What do customers experience? Where is knowledge lost? Which decisions take too long? And if we solve this problem, what changes for the business?
That changes the role of technology as well. Instead of being the starting point, technology becomes one of the possible ways to create improvement. Sometimes that means building something new. Sometimes it means integrating what already exists. In other cases, the biggest improvement comes from simplifying a process before writing a single line of code.
This is especially relevant now that AI is becoming part of almost every technology discussion. The question “How can we use AI?” is easy to ask, but it is often too broad to be useful. A better question might be: where do people spend time on repetitive work that does not require their judgement? Or: where is useful information available, but difficult to access at the moment someone needs it?
Those questions lead to very different solutions. They also make it easier to determine whether AI is actually necessary.
Better questions create better focus
One of the risks of rapid technological change is that organizations start solving too many things at the same time. There is always another platform, another AI application or another opportunity to automate something. Each initiative can make sense on its own, while the organization as a whole becomes more complex.
That is why focus matters. Not every process needs to be automated. Not every piece of data needs to become part of an AI model. And not every existing system needs to be replaced simply because something newer is available.
A useful technology decision starts with understanding what matters most.
What causes the largest operational friction? Where does complexity prevent growth? Which customer experience needs improvement? Which manual steps create risk or unnecessary cost? What do employees repeatedly have to work around?
These questions move the conversation away from technology for technology’s sake. They connect digital choices to something tangible: better service, faster decisions, lower complexity, safer operations or more time for work that requires human knowledge and judgement.
That does not make technology less important. It makes the use of technology more deliberate.
AI makes the human part more important, not less
There is another reason why asking better questions matters. Technology is becoming increasingly capable of producing answers.
AI can generate text, analyse large amounts of information, write software, assist with customer interactions and support decision-making. As those capabilities improve, it can be tempting to focus mainly on what the technology is able to do.
But an answer is only useful when the right question has been asked.
Organizations still need people who understand the context, challenge assumptions and recognise what matters. Someone has to decide which problem deserves attention, which information can be trusted, where risks are acceptable and what a successful outcome actually looks like.
That makes domain knowledge and judgement increasingly valuable. A powerful AI system working on the wrong objective simply allows an organization to move faster in the wrong direction.
For the same reason, I do not think AI discussions should be separated from conversations about people and processes. If a technology changes how work is performed, it also changes responsibilities, decision-making and collaboration. Those changes deserve just as much attention as the technical solution itself.
The same applies to security and the way we work
Cybersecurity is another good example. It is easy to turn security into a purely technical discussion about tools, infrastructure and controls. Those things are essential, but the underlying questions are broader.
Which information is most important to the organization? Where are the real operational risks? What would happen if a particular system became unavailable? Which dependencies exist between customers, employees, suppliers and technology?
Those questions help determine what needs to be protected and why. Security then becomes part of business continuity instead of a separate technical discipline.
The same principle applies to the way organizations work. Discussions about hybrid work, collaboration platforms or digital workplaces quickly turn into conversations about tools. But the more interesting questions are about how people need to work together.
Where should decisions be made? How is knowledge shared? When does someone need access to information? Which parts of a process require collaboration and which should happen automatically in the background?
Only after those questions are clear does it make sense to decide which technology supports them best.
From technology projects to the ability to adapt
Perhaps that is one of the larger shifts taking place. Digital transformation is gradually becoming less about individual technology projects and more about an organization’s ability to adapt continuously.
There will always be a next development. Today much of the attention is on generative AI and automation. Tomorrow another technology will create new possibilities. Organizations cannot rebuild themselves every time that happens.
What they can do is become better at recognising where change is useful, testing ideas, learning from the results and scaling what works.
That requires technical capability, but also curiosity and discipline. It means being willing to challenge existing processes rather than simply digitising them. It means understanding the business context before choosing a solution. And sometimes it means deciding not to build something at all.
Those decisions are rarely made by technology teams alone. They happen where business knowledge, customer understanding, software, data and people come together.
That is also where I believe some of the most interesting conversations are taking place today.
Start with the question behind the question
When someone asks for a new application, an AI solution or an automation, the first request is often only the visible part of a larger problem.
Why is this needed? What happens today? Who experiences the problem? What would become possible if it were solved? And how would we know that the situation had actually improved?
Sometimes the answers confirm that a new technology solution is exactly what is required. Sometimes they point in a different direction.
Both outcomes are valuable. Because ultimately, the goal is not to use more technology. The goal is to use technology where it makes a meaningful difference.
At Infodation, we believe good technology starts with understanding the problem behind the request. That is why our upcoming Infodation Sessions are not just about AI, cybersecurity or new ways of working. They are an opportunity to ask better questions about what these developments actually mean for your organization.
