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The figures from a new KPMG report don't lie: 45% of Dutch companies are already using AI, but many organizations struggle to turn opportunities into tangible results. While competitors worldwide are at the forefront of AI transformation, CIOs, IT managers and innovation managers experience a complex playing field here. And we are at the bottom of the list of countries in 47th place. What is holding back the acceleration? And how do you use the full potential of AI within the existing infrastructure? Time to clearly outline the technical bottlenecks and possibilities.
The ambition is there, and so is the technical know-how. However, many companies encounter internal bottlenecks that delay further AI integration. Three important factors stand out:
1. Data silos and legacy IT systems
Many organizations still work with outdated applications and separate data sources. This makes it difficult to efficiently unlock and combine data for AI models. Data silos limit insight into customer behavior and operational processes, essential for advanced analysis. Moving to an integrated data platform requires investments and changes in IT architecture, which is not always at the top of the priority list.
2. Lack of AI governance and policies
under clear guidelines about data ethics, privacy and model management, uncertainties arise within teams. AI governance is the framework that ensures that AI applications are reliable, transparent, and compliant. Few organizations still have mature frameworks that allow them to expand AI projects in a structured way, increasing risks for the organization and customer trust.
3. Culture and adoption within teams
AI is more than technology; it changes work processes and roles. Resistance to change and fear of losing a job often block employee acceptance. Without active communication, training and engagement, AI remains a static project rather than a living part of business operations.
The potential of AI in the Netherlands is great — especially if organizations put the right focus on concrete applications where immediate impact can be made. Think about:
Automation of repetitive workflows
By replacing manual processes with AI-driven robotic process automation (RPA), companies increase speed and accuracy. This frees staff from focusing on more complex tasks and innovation.
Improved customer engagement with AI
Chatbots and intelligent support systems provide 24/7 accessibility and personalized customer experience. They analyse customer interactions in real time and advise employees for a more proactive service.
Data-driven decision making
AI can analyze large data sets and make predictions that support management in risk management, supply chain optimization and market forecasting. In sectors such as logistics and finance, this leads to sharper competitive positions.
Many companies use platforms such as Microsoft Azure, Google Cloud, or AWS, but don't always take advantage of the full AI capabilities that these environments offer. That's a shame, because they offer scalable tools and frameworks that accelerate AI development:
Integrated AI Services: All major cloud providers offer pre-built AI services for image and speech recognition, natural language processing, and predictive analytics. This allows organizations to experiment quickly without building extensive models of their own.
Data lakes and pipelines: Building data lakes helps to store and structure various datasets in one place. Then, with modern data pipelines, information can be streamlined and prepared for AI analytics.
Management and Security: Cloud platforms provide advanced layers of security and compliance tools that help comply with GDPR and other regulations. It can also support AI governance by automating and monitoring workflows.
By collaborating with AI specialists organizations can make the right choices more quickly and maintain “ownership” over their AI transformation, without getting lost in technical complexity. This provides control over data, accelerates automation and stimulates sustainable innovation.
If you wait now, you risk competitors taking the lead with more efficient processes and stronger customer relationships. The technological landscape is changing rapidly. The key question for Dutch organizations: do we dare to take the leap and embrace AI as a core component of our business model?
