AI offers opportunities in virtually every sector, but to capitalize on them, an organization must have a solid foundation for adopting and integrating AI technologies. With the help of Joeri (Service Delivery Manager) and Tom (IT Consultant), Alistar has developed an AI readiness model for this purpose. The model helps turn opportunities into concrete actions and provides a roadmap from awareness to implementation. We recently applied this approach at Bouwend Nederland.
As a trade association for the construction and infrastructure sector, it made sense for Bouwend Nederland (BNL) to investigate what AI could mean in concrete terms for the sector and for its own organization. Interest within BNL grew rapidly throughout 2024, both among internal teams and among its members. This also raised important questions: How do you distinguish hype from reality? What truly aligns with the sector?
To find the answer to this question, we were brought in. Alistar and BNL have been working together for over three years: what began at the service desk has grown into a strategic partnership focused on development and innovation. Now, Alistar was asked to use its AI readiness program to identify where the opportunities in AI lie for BNL. The consultants also developed a strategy to capitalize on these opportunities.
Vision and Approach
We see that AI goes far beyond standard tools such as chatbots—it also impacts an organization’s culture, processes, and strategic direction. That is why the IT consulting firm deliberately opted for a holistic approach, in which technology is just one of the pillars. The AI readiness model focuses explicitly on the human and organizational aspects of AI adoption.
Based on this model, Alistar presented a structured framework to BNL. It consists of four levels of ambition, ranging from the deployment of standard applications to the development of advanced machine learning models using proprietary data. These levels of ambition are flexible and may vary by department within an organization. They serve as a strategic compass that enables organizations to define and achieve their AI objectives. During the process, these levels are determined by Alistar or, in consultation, by the organization itself. At BNL, they served as the foundation for a joint exploration of AI applications within the organization. To give these ambition levels concrete form, the model is structured around six central themes: awareness, opportunities, data security, infrastructure, integration, and knowledge.
We highlight where the opportunities lie and where you can make an impact with relatively little effort.
Research Methods
Each theme is linked to specific research questions, such as: To what extent can employees make effective use of standard AI tools? How can AI solutions help save time and money? What policies are in place regarding data security? Is the current infrastructure suitable for integrating AI tools? How are roles and responsibilities distributed in AI implementations? And how is knowledge sharing between teams and departments facilitated? To answer these questions, a combination of quantitative and qualitative research methods was employed. These are divided into three pillars: culture, business, and technology.
Tom: The model helps us identify where the opportunities lie and where you can make an impact with relatively little effort. At BNL, the model was applied through workshops and interviews with team leaders from various departments, both in IT and across the business. The central question was: Where are the opportunities for smart AI-driven support?
Alistar investigated where work processes are repetitive, where unnecessary time is wasted, and where employees themselves see opportunities for improvement. For example, someone wondered whether AI could take over time tracking in the future: “That takes up an unnecessary amount of time right now.”
Such insights make it possible to invest strategically in AI solutions that truly add value. And by actively involving employees as ‘enablers,’ ideas emerged that were not only technically feasible but also widely supported within the organization.
Yuri: Employees felt heard and engaged.
Final Report
The final report that has been prepared contains specific deliverables that contribute to achieving BNL’s level of ambition. These are divided into three categories: metrics, qualitative findings, and recommendations.
What makes this methodology innovative is the introduction of two unique metrics: the adoption score and the opportunity score.
Yuri: These scores are based on the results of surveys and interviews, which identified various task categories that can be supported by AI. The opportunity score indicates the extent to which tasks within a department are suitable for AI support, either through off-the-shelf solutions or through custom solutions such as Copilot Studio.
Custom AI Solutions
The recommendations focus on both the implementation of standard AI tools and the development of customized AI solutions.
Roel Vrenken (Manager of Information and Data Management at BNL): Our organization strives to maximize value by developing and deploying customized AI tools. We believe that specialized AI solutions enable us to achieve our business objectives more efficiently. The potential benefits of training our own models do not outweigh the required investment and risks.
As a standard AI tool, Alistar recommends Copilot for Microsoft 365. In addition, it is recommended to develop custom AI tools for specific processes, such as a solution for automating time tracking and an internal chatbot. The chatbot can help BNL answer members’ questions.
Tom: As a knowledge-based organization, BNL strives to support its members effectively and efficiently. One of the challenges involved in this is answering a wide variety of questions quickly and accurately—a task made more difficult by the fact that internal knowledge is often scattered throughout the organization.
Copilot Studio is used to create a dynamic and up-to-date platform that integrates knowledge from both internal knowledge bases and public sources. This allows questions to be answered effectively, even as the details and context of those questions are constantly changing. This should result in higher-quality service and a reduced workload for the department.
What's Next
In response to Alistar’s final report, BNL’s management is now considering next steps to further integrate AI within the organization. The focus is not only on technical implementation, but also on broad adoption and embedding AI in the organizational culture. Alistar will remain involved in this process as a strategic implementation partner.
Tom: This process shows that AI is not an end in itself, but a powerful tool for organizations to become smarter and more agile.
Yuri: As far as we're concerned, BNL is an example of how curiosity, collaboration, and co-creation can lead to real progress.
