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7 tips for a successful start of AI projects

Veröffentlicht von Sarah Heuser auf Feb 20, 2019 10:42:00 AM
Sarah Heuser


7 Tipps, um KI-Projekte erfolgreich zu starten


 An increasing number of companies want to use artificial intelligence to improve their internal processes across industries. At first glance, initiating and setting on track AI projects seems simple: Just implement some AI-based software, and the company will promptly start to benefit from the latest technology! In reality, however, it is not quite so easy. The preconditions for a truly successful implementation are thorough preparations, well-targeted realization, and permanent monitoring and testing. See the following seven tips for a successful start of an AI project:

1. Collecting meaningful data: Before you think about implementing AI, you need a lot of data. As a precondition for getting good results, the quality of the data is of major importance.

2. Defining (and pursuing) a joint goal: When stakeholders from different departments, such as business decision-makers and data scientists, discuss how to implement a joint project, misunderstandings tend to occur. Not everybody has the same level of knowledge about the technology, and people have different goals they wish to pursue with the help of AI. Therefore, it is important to create a joint knowledge base and to define clear-cut goals. At the same time, projects should be selected which match the respective use case. All stakeholders must keep talking to each other, not only during the initial phase but also during the entire execution of the AI project, to ensure that they have not lost sight of the jointly defined goals. Here, feedback loops are very important: If necessary, the employees can rectify the forecasts and results supplied by the AI whenever necessary.

3. Start small, think big: It is a good idea to start with smaller projects to gather experience instead of making the first attempts with complex large-scale projects, running the risk of getting lost in the intricacies of the technology. High-volume processes should be split into multiple small sections which are easier to automate, and quickly show the first tangible results. Processes with a fixed return on investment (ROI) are best suited for the introduction of artificial intelligence, because they do not have too many different variables and are not exceedingly complex. Still, it is important to face new and larger challenges – this is the only way for the AI to get better.

4. Hiring or outsourcing: Not every company has the manpower to build their own AI systems. That's why it's normal and even recommendable to call in external service providers. To run a team of their own, a company needs many resources and a steep learning curve. Another advantage of outsourcing is that service providers have a wealth of experience in the implementation of AI projects.  

5. Don't forget the user: No matter how fantastic AI is: At the end of the day, it will be used by people, and most of them will not have a technical background. Therefore, when implementing the technology, a user-friendly interface is essential. In this way, the advantages of AI can be fully exploited and made easily accessible to employees.

6. Be patient: It takes time to develop, teach, and test an AI project with all models and algorithms. This means that such projects cannot be implemented spontaneously and quickly. A company needs to take this into consideration also in the planning phase, and for example procure information from a service provider on a realistic schedule. In this way, budget and resources can be used in a meaningful manner.

7. Everybody should benefit from AI: With all the enthusiasm for promoting AI projects, however, a company should never forget its own employees: They, too, must benefit from and be convinced of the new technology. For this reason, it is important to introduce employees to the topic, take away their fears and prejudices about the technology and show them that AI supports them in their work.

Nowadays, the topic of artificial intelligence is a top priority for companies. Nevertheless, there are some typical stumbling blocks which should be avoided in the introduction, execution and permanent application of the technology. If a company identifies them right from the start, their AI projects will be successful.


- Start small: Artificial intelligence cannot be introduced "just like that", and it also takes some time. Starting with smaller projects gives the company a chance to see for themselves how much work is involved, and how relevant the technology is for them.

- There are many ways to a successful AI. Good preparation and, along with it, the meaningful use of budget and existing resources are crucial.

Topics: Customer Experience, Machine Learrning, ML, Artificial Intelligence

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solvatio provides leading solutions for automated troubleshooting and malfunction resolutions in technical systems & devices. Originally founded as spin-off of the Department for Artificial Intelligence and Applied Computer Science of Würzburg University more than 20 years ago, solvatio continues to push the boundaries of AI for automated data-driven knowledge generation and AI orchestrated troubleshooting.

It is our mission to minimize service efforts, reduce support costs and achieve superior operator and customer experience across all interaction channels while ensuring the provision of excellent technical support and flawless operation.

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