chevron_left Back to insights

Beyond ideas. Practical steps for AI Integration in your business



Reading time

4 minutes


Andreas D.


“How can I transform my AI idea into a tangible digital product?” In our AI insights series, we have thus far discussed the following questions: (1) How to deal with the AI hype? (2) What is AI and what could it mean for your business? (3) How to find the right AI use cases for your company? & (4) How can targeted AI experiments support your decision making process? We can now start thinking of how your AI concept can be turned into reality. In other words: the real AI integration.

Remember John? After a management meeting, John was tasked with ‘exploring the realm of AI’. So far, he has managed to get a good understanding of the potential of AI for his company. He identified a promising AI use case, cleaned and refined a lot of data and he even did some experimentation. Several questions now pop into John’s mind, and most of them come down to “Now what?” 

ai integration cartoon

At this point, he has been asking the right questions and managed to find valuable answers. Now, he's ready to start developing his idea into a working solution. When you get closer to the development phase of an AI idea, we recommend considering some pitfalls & pointers for a successful AI implementation.

Pitfalls & pointers in AI integration

Vision & Strategy

A common pitfall for any project is failing to align expectations. Stakeholders might have different expectations depending on their context. To get everyone on the same page and to align your AI initiatives with your organization’s strategic goals, we recommend elaborating a product vision. A template, such as the product vision board, is a convenient tool to start the discussion, and it can be the basis to further refine your product vision and product strategy during your solution’s lifecycle too.

fictious vision board chat gpt
An example of a fictional product vision board, powered by ChatGPT.

Prioritization & backlog management

Once you have established a clear vision, the next step is to set priorities and start the refinement of what exactly needs to be done during the first stages of development. These insights will help you establish a product backlog to guide the development process.

Technical implementation questions

Now into the weeds. This step contains several common pitfalls that are usually context-dependent. Your AI solution will need to be embedded in an existing IT landscape and it will need to integrate with other solutions on a technical level. Typical questions to ask here are:

  • Which data will our AI solution need to access and where will it get this data?
  • What do we want to do with the output of our AI solution?
  • Which security measures need to be taken when we make our solution available?

Answering these questions often requires specific expertise and entails technical decisions in which a partner can provide guidance.

A new (AI) product or tool is not designed or built with a big bang, but realized in a step-by-step process. Our advice is to consider combining the methodologies of Design Thinking, Lean product management and Agile development to explore all sides of the problem, create the right product and build the product right. 

The human-side of AI

Design for user engagement

To fully valorize your investment in AI, it’s essential to recognize that adoption is the key to success. Bringing users into the fold during the design process isn't just beneficial – it's crucial. Involving them early on raises a sense of ownership and helps tailor the solution to their needs and expectations. 

Process integration and adoption

A key factor in the adoption of your AI solution lies in user-centric training and education. Consider developing training programs that are tailored to different user groups within your organization. These trainings should not only cover the technical aspects of the AI system but also its practical benefits and potential impact on your users’ daily working processes. Empowering your users with knowledge and confidence in the new technology is a significant step towards seamless (AI) integration and acceptance.

Be mindful of the impact.

Finally, implementing an AI solution is as much about technology as it is about cultural change. Therefore, it's equally important to be mindful of the concerns surrounding the disruptive nature of AI. These concerns aren't just about the technology itself, but about how its introduction may alter daily working processes too. Transparent communication about the purpose, benefits, and potential impact of AI can reduce apprehensions and misconceptions.

Your AI integration journey with The Value Hub

On your AI journey, an experienced partner’s expertise is invaluable.

The Value Hub brings clarity to complexity, offers both technical know-how and strategic insight. As a supportive guide, The Value Hub helps you ensure that your AI solutions align with your goals, that AI initiatives integrate within your IT landscape and that they are embraced by your users.

ai integration partner support

Connect with us and let’s start the conversation about how AI can effectively become a game-changer for your organization.

about the author

Andreas D.

Andreas D. is Business & Functional Analyst at The Value Hub. His expertise lies in integration & project finalization. Combined with business understanding & requirement distillation as his strengths, it makes him a truly valuable team member. On top of that, he’s particularly interested in and focused on AI, analysis en predictive machine learning, an interest and expertise he used and shared in his latest projects. Andreas is the one to delve deeper and to realize future proof and innovative projects.

Discover other insights