How to make AI successful in your business

How do you implement a profitable AI system, but also, how do you sustainably anchor this within your organization? In this blogpost we give five important tips.
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What are the success factors for the adoption of AI and how do you get the most out of your investment?

Companies around the world are currently enjoying the added value that AI offers. Existing workflows and operational processes are optimized, the staff is motivated and activated by automating routine tasks and enabling better decision making.

Despite this added value, many companies are struggling to implement and optimally integrate AI. The technology remains new and the lessons learned by early adopters have not yet spread across all sectors. We give five important tips from our experience.

1: Focus on integration from day 1

The major impact that AI has on the profitability of your company is linked to a major change that occurs within the company itself. As with any major change, a vision must be formulated when embracing AI. AI is part of an organization’s broader digital strategy and must be given the attention it deserves.

The most important change must take place in the corporate culture: cooperation between the various stakeholders is necessary because an impact is often realized across departments and structures. The central question is: “How do we approach things differently from tomorrow onwards? Dare to ask in advance what will change if you have a perfect AI system. Only then ask questions about whether you will develop it and how accurate your AI system needs to be to achieve your goals.

Ask yourself the question: “What would I do differently tomorrow if I had developed a perfect AI solution? And is this change desirable?”
– Joeri Ruyssinck

2: AI is above all a cultural change

We talked about it in the previous point, but we can’t stress it enough: the most important change has to take place in the culture of the company. Inter-departmental collaboration and information sharing must be encouraged to make the adoption of AI success.

It is therefore also essential that the strategy around the implementation of the AI is supported by the entire company.

For example, it happens frequently that money and time are invested by management in an AI system that is not (fully) used by others within the organization for whom it provides added value. What is unknown also remains unloved, and many employees have a negative view of AI. This often finds its origin in misuse of the technology that is covered in the media. There is also a persistent myth that an AI system can replace employees and their knowledge, making the technology a threat rather than an opportunity.

ML2Grow can help. With our expertise, we make the usefulness and necessity of AI clear within your organization. All employees get insight into what AI can do for them. How are their processes and working methods going to change positively? How does AI support them in their work? What knowledge and competences can they further develop? Our experts are ready to explain AI and its benefits to both technical and non-technical employees in detail.

3: The added value of the technology must be put first

Our next point reconnects with the previous one. AI technology is not a one-size-fits-all box that you can buy and gives you a fixed return, but it is nevertheless a powerful tool. The added value lies precisely in creatively handling and adding this technology in the right places and in the right way.

“With AI today, you can basically fix anything.” “It’s not the technology that’s the challenge, it’s the idea. The more powerful that idea, the more powerful the AI solution.”
– Joeri Ruyssinck

So we can say today that the greatest challenge is not technology, but creativity: the idea. Of course, all this has an effect on the adoption of AI in companies. Applying AI requires investments in technology, but also in creation and knowledge, while the benefits are often not immediately quantifiable. As a result, it is sometimes more difficult to obtain the necessary financing. Our experience teaches us that the time investment that it takes to mature an idea turns out to be the biggest stumbling block with companies and not the financial cost. At ML2Grow, we make every effort to remove this stumbling block. For example, we have drawn up trajectories that allow companies to switch quickly and remove these uncertainties. In addition, our experts who have been in the business for many years bring the necessary know-how and creativity to the table.

4: A small step for man, a giant leap for mankind

The previous steps already make it clear. The adoption of AI requires a very specific and often new approach.
To implement AI in a business process, knowledge and experience need to be built up. It is good to build up this knowledge in the process and start small. A simple and small scale process can often already have a large impact and often offers a platform in an incremental and natural way to take follow-up steps.

5: Your data is the key to success

For a successful AI implementation, a good data management strategy, data architecture, and good quality data are the engines. Be critical of AI solutions offered on the market as a generic finished product. The real added value is always realized by tailoring the AI solution to the needs and also to the data that is available.

It is a misconception that AI must use large amounts of data to create value. There is also specific AI technology that is used in scenarios where, by definition, there will always be little data. Think of expensive computer simulations or agricultural experiments.

Much or little data, data quality is important. The better the data, the better the functionality of the AI. Setting up an AI trajectory often generates more and better data as a side effect, which can then be used again. This often creates an amplifying effect. The first step is often the largest, but here too you can count on our expertise. We have already taken this first step successfully dozens of times. We can help you map out your data (flows) and identify bottlenecks and opportunities. In addition, we also migrate and implement data infrastructures and user interfaces. Please feel free to contact us for more information.