The ambition was clear.
A manufacturing company in the midmarket wanted to take the next step. Not because it had to, but because it could. Sensors had been present on machines for years, data was being collected, and the international market demanded flexibility, predictability and scalability. The management saw a clear opportunity: deploy AI to predict maintenance, reduce unplanned downtime, while laying the foundation for further growth.
- The business case was right.
- The technology was available.
- The organisation was motivated.
Until the first question came up. “Do we actually have full visibility of all connected systems within our IT and OT environment?”
It remained silent.
Not because there were no systems, but precisely because there were so many. Production lines with embedded controllers, old PLCs that had been running smoothly for years, cloud platforms for analytics, SaaS applications for supply chain integration, external service parties with remote access, and a growing number of IoT components that had been quietly added to processes.
No one had a complete picture.
And that is exactly where the real story of innovation begins.
Innovation increases your attack surface
Digital initiatives bring value, but they also increase complexity. AI, cloud migrations, IoT integrations and digital chains create new data flows, new links and new dependencies. Whereas innovation used to be often a project within one domain, today it is almost always an ecosystem change.
Every new sensor, every API, every cloud instance and every partner connection increases the organisation’s digital surface. Not only functionally, but also from a risk perspective.
That picture is widely recognised. International studies structurally place cyber threats at the top of business risks, precisely as digitalisation and connectivity continue to accelerate. At the same time, analysts predict continued growth in security investments, driven in part by AI adoption and cloud transformation. Not as hype, but as a necessary correction to a rapidly growing digital landscape.
So innovation and risk grow in parallel. The question is not whether they do. The question is how to deal with it.
From innovation ambition to innovation reality
Back to the production company.
The AI plans did not disappear from the table. On the contrary. But the conversation changed. Where the focus used to be on algorithms and dashboards, it shifted to insight and control. The team realised that predictive maintenance is valuable only if the underlying infrastructure is reliable, visible and controllable.
They started with something seemingly simple: inventory.
- What is all connected?
- Which systems communicate with each other?
- Where are data and interfaces located?
- Which OT components are accessible from IT networks?
- Which external parties have access?
It turned out not to be a quick exercise, but a very fundamental one.
Because innovation is not just adding new technology. It is understanding the environment in which that technology needs to operate.
Visibility as a prerequisite for speed
There is a perception in many organisations that cybersecurity slows down innovation. Extra controls, governance, risk assessments. It sometimes feels like a brake. But in practice, the opposite is apparent. Lack of insight and oversight are the real retarders.
When you don’t know exactly what your digital landscape looks like, any change becomes exciting. Impact is hard to predict, dependencies remain hidden and decision-making becomes cautious.
Once understanding grows, that changes. Architecture discussions become more concrete. Risk considerations become factual. Segmentation decisions gain context. Innovation projects gain confidence.
Visibility accelerates innovation because it reduces uncertainty.
Or in other words, you can only really pace yourself when you know where you stand.
IT and OT: the place where innovation becomes tangible
The convergence of IT and OT makes this topic especially relevant. In manufacturing, logistics, energy and healthcare, operational processes are increasingly shifting towards digital ecosystems. Machines are becoming data points, processes are becoming software-driven and maintenance is becoming predictive.
This is innovation in its purest form.
But it also means that environments that were once isolated are now becoming part of wider networks. Components with long life cycles, limited patching capabilities and specific protocols are being linked to cloud platforms and enterprise networks.
Here again arises the need for segmentation, monitoring and context-aware access models. Not to block innovation, but to make it securely scalable.
Asset management as a strategic building block
During the process, the manufacturing company discovered something interesting. The project that started as a security inventory grew into strategic asset management. Not just from compliance, but from decision-making.
Understanding assets helped:
- lifecycle planning
- investment prioritisation
- vendor dependencies
- modernisation strategies
- innovation roadmaps
What started as “what do we have” became “what does this mean for our future”.
And with that, cybersecurity changed from a layer of protection to a source of information.
Cybersecurity as an innovation accelerator
In the end, the AI project can go on as usual. Indeed, it gets better. Not just because the technology works, but because the context is right. Data is reliable, links are insightful, segmentation is in place and governance aligned.
The difference is not in tooling, but in the foundation.
Cybersecurity creates trust both internally and externally.
Innovation will not be a leap, but a step.
The broader perspective
This story is not an isolated one. Many organisations are at the same crossroads. The ambition to digitise and innovate is there, but the demand for insight, control and resilience is growing along with it.
The organisations that succeed in this do not treat cybersecurity as a final piece of projects, but as a structural part of their digital strategy. They invest in visibility, understand their assets, segment their environments and connect IT and OT from architecture principles.
Not because regulations demand it, but because innovation demands it.
Conclusion
Innovation without cybersecurity is possible, but vulnerable.
Innovation with cybersecurity, on the other hand, is robust. It offers confidence, predictability and scalability.
The production company discovered that the most important question was not which AI tool to choose, but how well they understood their own digital environment.
And that is perhaps the essence of modern digital strategy.
Cybersecurity is not a capstone.
It is the foundation of innovation.
The real question for any organisation is therefore simple:
If a new innovative initiative starts tomorrow, is your foundation already in place?
Peter Mesker
Sources
World Economic Forum – Global Risks Report 2024
Gartner – Forecast: Information Security and Risk Management 2024-2025
IBM – Cost of a Data Breach Report 2025Crowdstrike 2026 Global threat report
89% increase in attacks from AI-enabled adversaries
According to the World Economic Forum, cyber threats are structurally among the biggest global business risks.
Gartner predicts continued growth in global security spending due to AI and cloud adoption.
The IBM Cost of a Data Breach Report 2025 shows that the average cost of a data breach worldwide is in the millions, with delayed detection being the biggest cost driver.