Primaned’s Vision for the Future of Project Controls

Artificial intelligence has already begun to change the way Project Controls professionals work. It helps teams process information faster, analyse more data and prepare better scenarios. Integrating AI will take away the endless hours spent on repetitive tasks, shifting focus towards the work that actively needs a human in the loop. For Primaned, the real opportunity is not simply to automate more tasks. It is to turn information into better project decisions: delivering project insights that improve predictability and give professionals more time to focus on interpretation, communication and control.

With more than 40 years of experience in Project Controls, deep knowledge of Oracle Construction & Engineering solutions and growing expertise in AI, data and analytics, Primaned is closely involved in this development. Our view is clear: the future of Project Controls is a move from building schedules to steering projects. AI will increasingly support the processing and analysis of information, while human expertise remains essential for understanding context, checking results and turning insight into action. This is part of our wider ambition to bring clarity and control to the projects that shape our world.

From processing project information to interpreting it

A lot of Project Controls work still involves collecting, checking, updating and reporting information. Planners update schedules, teams prepare reports and specialists bring together data from different sources before they can start a deeper analysis.

AI will help reduce some of this manual work.

It can support teams by structuring information, finding patterns, highlighting changes and preparing possible scenarios. This means professionals can spend less time on repetitive processing and more time on the questions that matter most:

• What is changing in the project?
• What could happen next?
• Which risks need attention?
• What options do we have?
• What decision should we take?

At Primaned, this is what we mean by moving from building schedules to steering projects. Our purpose is to bring more clarity and control to the projects that shape our world.

The aim is not to remove people from the process. It is to use technology to give people better information and more time to focus on the project itself.

Human judgement remains essential

Our CEO, Paul Vogels, sees this as an important part of the future of Project Controls.

As AI takes over more predictable and repetitive tasks, professionals will be able to focus more on interpretation, judgement and communication. A system may produce an answer, but someone still needs to understand whether that answer makes sense in the real project and communicates the information clearly.

That requires Project Controls knowledge and practical human expertise.

A scheduler must still be able to recognise when a result looks wrong, when important context is missing, or when a proposed scenario is not realistic. Projects are not standard production lines. Contracts, people, suppliers, regulations, resources and changing conditions all influence what the data really means.

This is why we believe human expertise will remain central.

AI can support the analysis. The professional remains responsible for understanding the outcome and deciding what to do with it. This is what is referred to as Human in the Loop

Good AI starts with good data and good context

Mark Roodbol, Manager AI & Analytics at Primaned, focuses strongly on the relationship between AI, data and context.

Different AI applications need different types of information. A language model may be able to work with just a single document, while predictive applications often need a larger set of reliable historical data.

But data alone is not enough.

AI does not automatically know the project, the contractor, the background of a delay or the reason why a team made a certain decision. That context must come from people and from the way the organisation works.

Mark also stresses the importance of clear boundaries and professional review. AI can generate useful output, but people still need to review it.

At a wider organisational level, Primaned also sees shared definitions, data ownership, connected systems and clear governance as important conditions for reliable AI adoption.

In simple terms: AI becomes more useful when the information around it is reliable and the people using it understand both the project and the technology.

What could AI mean in practice?

Michel Molenaar, Senior Consultant at Primaned, looks mainly at the business impact of AI and how it could be used in real Project Controls workflows.

One example is the early planning phase.

AI can help turn project requirements, estimates or tender information into a first concept schedule. This does not mean the system creates a finished planning that can be accepted without review. It means AI can help professionals get to a first structured version faster.

Another area is progress information.

Imagine a normal project meeting. People discuss delays, new dates, risks, actions and dependencies. Today, much of that information is still processed manually after the meeting.

In an AI-supported workflow, the conversation could be structured into proposed updates, actions and assumptions. AI could then help process large amounts of information, identify possible bottlenecks and prepare different scenarios.

The scheduler would still review the outcome, challenge the assumptions and decide what is realistic.

This is an important point: AI can speed up the work, but it does not remove professional responsibility.

Other potential applications include:

• creating a first concept schedule from a project brief or tender;
• asking questions about project data;
• creating initial visualisations and summaries;
• analysing delays and preparing possible recovery scenarios;
• comparing different options before a project decision;
• identifying patterns that could point to increasing schedule or project risk.

Some of these applications are already possible in different forms. Others are still being developed, tested or explored. At Primaned, we believe it is important to be clear about that difference.

The planner’s role will change

Steven Delemarre, Senior PROCON Professional and planner, brings an important practical perspective.

A scheduler does not work only with software. A large part of the job is about people.

Project information comes from conversations with project managers, engineers, contractors, work preparers, and other stakeholders. The scheduler has to ask questions, understand what has happened and decide whether a change is important.

AI can help process that information faster.

For example, it could help structure information from a progress meeting or support the review of a large number of activities. But the conversation itself still matters.

The scheduler still needs to understand the project, recognise different interests, and assess whether the information makes sense.

This means that the planner’s connective and interpretive role becomes even more important.

The technical side of planning may become easier and more automated. At the same time, communication, judgement and the ability to connect different parts of the project become more valuable.

The scheduler remains the human link between information, stakeholders and decisions.

Better technology also needs better governance

AI should not be treated as a separate technology experiment.

Project organisations need to decide how AI fits into their existing processes, responsibilities and systems.

Useful questions include:

• Which project problem are we trying to solve?
• Which decision do we want to improve?
• What information does the AI use?
• Who owns that information?
• Who checks the output?
• Who makes the final decision?
• How do we protect sensitive project data?
• How will we know whether the application is actually creating value?

Without these questions, an organisation may create a faster process without creating a better result.

The goal should not be automation for the sake of automation.

The goal should be better control, earlier insight and stronger decision-making.

Technology is already moving in this direction

AI is increasingly becoming part of existing project platforms instead of being used only through separate tools. This integrated approach is important because AI becomes more useful when project information is connected.

A clear example is Oracle Construction and Engineering Intelligence. Oracle describes it as a way to turn construction data into actionable insights by collecting, transforming, visualising and predicting project information.

Within the platform, Construction and Engineering Analytics includes prebuilt data pipelines to Oracle applications such as Primavera P6 EPPM, Primavera Cloud, Unifier and Aconex. This allows organisations to consolidate project information and analyse areas such as planning, cost, workflows, operational performance and overall project status.

AI is also changing how people interact with information. Users can ask questions in natural language, while generative AI can analyse important measures and generate visualisations based on those questions. Oracle also supports AI-generated explanations and summaries that can be added to dashboards to help users understand the insight behind a visual.

For Project Controls teams, this can make information more accessible. Instead of depending on specialist BI knowledge for every question, users can interact more directly with project data and move more quickly from information to insight.

The platform also shows how AI can support more proactive ways of working. Oracle's Advisor for Safety, for example, uses AI to analyse structured and unstructured data, identify projects with higher safety risk and recommend preventive actions. More broadly, Oracle's analytics can help organisations identify trends, cost pressure, schedule issues, process bottlenecks and operational risks before they grow into larger problems.

For Primaned, this is closely linked to our vision for Project Controls. The goal is not simply to create more dashboards or automate more reporting. It is to help organisations move from fragmented information towards clearer, more useful project insights that support earlier action and better decisions.

Primaned is a Oracle Consulting Partner for Construction & Engineering in EMEA, and we are also the first Oracle AI partner in Europe for Construction & Engineering.

This position allows us to combine Oracle technology with our expertise in Project Controls, implementation, and real project organisations. It also puts us in a strong position to help clients understand where these new capabilities can create value, what foundations are needed, and how they can be introduced responsibly.

Primaned’s role: connecting technology and practice

Primaned is not a generic AI company.

Our role is different.

We help project organisations understand where AI can create value and how it can fit into the way they already manage projects.

That means combining several areas of expertise:

• Project Controls knowledge
• Oracle software and implementation
• Consultancy and process design
• AI, BI and Data Analytics
• Experienced PROCON professionals
• Training and professional development

This combination matters because technology alone is not enough.

A good AI use case also needs the right process, the right data, the right people and a clear way to review the outcome.

That is where Primaned can add value.

Start with the business value, not with AI

One of the clearest messages from our experts is that organisations should not start with a technology name or an impressive demo.

They should start with a real project problem.

Ask:

• Where are we losing time?
• Where do we lack insight?
• Which decisions take too long?
• Where do we discover problems too late?

Then look at whether AI could help.

A practical first step could be a process that is repetitive, time-consuming and easy to review. This gives the organisation a chance to learn without creating unnecessary risk.

From there, the next steps are simple:

1. Choose one clear project challenge.
2. Check whether the necessary data is available and reliable.
3. Decide who will use and review the output.
4. Start with a controlled application.
5. Measure the result.
6. Scale only when the application works.

The Primaned Project Controls Scan can also help organisations understand their current maturity, identify gaps and define a realistic improvement roadmap.

Think big, start small. But start now.

AI will continue to change Project Controls.

Some tasks will become faster. Some activities will become more automated. New forms of analysis and decision support will become possible.

But the strongest results will come from combining technology with Project Controls expertise.

For Primaned, the future is not about replacing people with AI.

It is about using AI to help people understand projects better, act earlier and make stronger decisions.

That is the shift from building schedules to steering projects.

And this is how we bring clarity and control to the projects that shape our world. Because at Primaned, every project matters.