Why do you see increased interest in AI Readiness right now?
Bogdan: A year ago, many conversations were about AI tools and what they could do. Today, discussions have matured. Organizations want to know how AI can create business value and which investments are actually worth making.
Many have already started with AI in various ways. They have tested Copilot, built some AI solutions, or conducted several pilots. Now they want to understand how AI can be used more systematically to create real business value and become a natural part of the business.
Göran: We also notice that AI is no longer an issue driven solely by IT. It is discussed in management teams and throughout the business. This also creates a need to establish a common understanding of the current situation and alignment on which initiatives should actually be prioritized.
What causes many AI initiatives to lose momentum?
Göran: It’s rarely about a lack of ideas. Quite the opposite. Many organizations have identified a large number of potential AI use cases, but it is significantly more difficult to determine which are most relevant and what prerequisites need to be in place. An important success factor mentioned by some of our customers is that, simply put, there was someone in the organization to ask questions. Is this feasible? Is it complicated? What do we need to do to make it work?
Bogdan: At the same time, we often see that data quality varies, master data is not sufficiently structured, or the same information is defined differently in various parts of the business. AI amplifies these challenges. If you have a stable foundation, it’s much easier to create value. If there are deficiencies, they quickly become apparent.
It’s also easy to get stuck in individual AI projects. Many organizations succeed with one or two use cases, but the next step becomes significantly more difficult. The real challenge is to create the conditions that make AI a part of the organization’s way of working, rather than a series of standalone initiatives.
Is that insight behind the AI Readiness Workshop?
Göran: Yes, we saw that many organizations needed a more structured way to assess their current situation before taking the next step.
The workshop is about creating a clear picture of the organization’s AI maturity and identifying which areas need to be developed. We look at three perspectives – systems, data, and organization – because all three need to work together for AI to be effective.
The result is not only an analysis of the current situation but also a prioritization of AI initiatives with the greatest potential to create business value.
How does the workshop work in practice?
Bogdan: We gather representatives from both business and IT. AI affects the entire organization, so both perspectives need to be included from the start.
We start from the business goals and analyze a prioritized business process. We then assess the organization’s AI Readiness in areas such as strategy, data and master data, processes, technology, organization, security, and governance.
We also identify relevant AI use cases and prioritize them based on business value, feasibility, and their expected impact.
You often talk about alignment between business and IT. Why is that so important?
Göran: Because AI very easily becomes a technical issue, even though it fundamentally concerns business development.
We often see that the business describes the challenges it wants to solve, while IT focuses on technical possibilities. Both perspectives are needed, but they need to converge. One of the great benefits of the workshop is that it creates a common language and a shared understanding of where the organization stands today.
This also makes it significantly easier to prioritize investments and create a roadmap that the entire organization can support.
Which organizations benefit most from this type of workshop?
Göran: Primarily organizations that already operate in a modern ERP landscape and want to use AI more strategically.
This can be companies facing their first major AI investments. But just as often, it concerns organizations that have already started and now want to move from individual AI projects to a more structured way of working.
Bogdan: Furthermore, the methodology is not tied to a specific business system. Regardless of whether the business operates in SAP, Dynamics, or another environment, the fundamental questions are the same. Do we have the right data? Are the processes mature enough? And which AI initiatives will create the greatest benefit?
What does the customer gain after the workshop?
Göran: The most important thing is that the customer gains a common understanding of the current situation. This may sound simple, but many organizations actually lack alignment on how ready they are for AI.
In addition, the customer receives a clear prioritization of the next steps. Which initiatives should be implemented first? What needs to be improved before further investment? And what does a realistic roadmap look like?
This enables the organization to make decisions based on facts instead of assumptions and to focus on the efforts that yield the greatest business value.
If you were to give one piece of advice to organizations that want to achieve greater impact from their AI initiatives – what would it be?
Bogdan: Don’t start with the technology. Start with the business. Consider what problems you want to solve and what value you want to create. Then it will be much easier to prioritize correctly.
But don’t forget that AI also places higher demands on the organization than many previous technology investments. Therefore, I would focus at least as much on the foundation.
For a long time, many have been able to live with unclear data owners, varying data quality, and insufficient governance. The information may not have been perfect, but the business still functioned. AI doesn’t change that – it merely makes these deficiencies visible. That’s why it’s so important to see AI as more than a technology project. To create long-term business value, data, processes, and governance need to evolve in step with technology.
Göran: I would also say that you shouldn’t try to do everything at once. AI is developing rapidly, and the opportunities are many, but the organizations that succeed best are often those that start with a few well-chosen initiatives. This builds experience, creates trust within the organization, and provides a stable foundation for further development.
