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Successfully Implementing AI Projects with the AI Innovation Cycle

Tobias Jonas Tobias Jonas 3 min read
Successfully Implementing AI Projects with the AI Innovation Cycle

Unleashing the AI Revolution: The AI Innovation Cycle

In an era characterized by rapid technological advances, artificial intelligence (AI) has established itself as an indispensable tool for forward-thinking companies. Experimentation with technologies like ChatGPT has opened the doors to the AI world for many, but the real breakthrough lies in transforming these experiments into sustainable solutions that create real value. This is where the innFactory AI Cycle plays a crucial role, providing a systematic approach for identifying, developing, and successfully implementing AI projects.

The innFactory AI Innovation Cycle: From Vision to Reality

The AI Innovation Cycle is a structured process that helps companies harness the full potential of AI. It consists of seven steps that ensure AI projects are not only full of ideas but also feasible and value-creating.

innFactory AI Cycle

1. Orientation: Setting Goals and Introduction

Every successful journey begins with a clear definition of the goal. In the first step of the AI Innovation Cycle, the framework for the AI project is established and the team is aligned on a common mission. This step is fundamental to making the relevance of AI tangible for the company. This step and the do’s and don’ts can either be defined in advance with management or worked out in the workshop.

2. Foundation: Solidifying Basic Knowledge

A deep understanding of AI is essential. Before diving deep, a solid foundation of knowledge is created that shows all participants the possibilities and limitations of the technology. This step forms the basis for developing realistic and effective projects. Our CEO Tobias Jonas has prepared a suitable presentation for this phase and is available to you as a keynote speaker or for the entire workshop.

3. Discovery: Identifying Business Opportunities

Equipped with the necessary knowledge, the creative phase of identifying business opportunities begins. This step requires openness and the ability to transcend existing boundaries to recognize where AI can provide real added value.

4. Selection: Evaluating and Prioritizing Ideas

The challenge lies in selecting those with the greatest potential from the multitude of ideas. This step ensures that resources are deployed in a targeted and efficient manner.

5. Design: Defining Project Outlines

Selected ideas are concretized in this step. Defining project outlines, goals, and necessary steps for implementation is crucial for the success of subsequent phases.

6. Planning: Establishing Next Steps

Now it’s about planning implementation. Responsibilities are defined and necessary resources are allocated. This ensures that projects don’t just exist on paper but are realized.

7. Reflection: Conclusion and Feedback

The cycle concludes with a reflection and feedback session. These insights are valuable for continuously improving the process and motivating the team to implement the projects.

The Path from MVP to Established AI Process

After identification and planning comes the phase of prototype development and exploratory sprints, in which ideas are transformed into tangible solutions. innFactory, with its expertise in cloud and AI solutions, plays a central role here, responding agilely to developments and continuously adapting prototypes to needs.

Continuous Improvement and Scaling

The work is not done with the prototype. Follow-up sprints for improvement and scaling of the solution follow. Through data analysis and feedback, the effectiveness of AI is continuously increased, while the scaling phase ensures that the solution can be deployed broadly.

Conclusion

The innFactory AI Innovation Cycle is more than a guide; it is a compass for companies that want not only to survive in the digital landscape but to thrive. Through this structured approach, companies can fully exploit the transformative potential of AI and thus prepare for the future. The journey from the first idea to an established AI process may be challenging, but with the right tools and partners like innFactory, this path becomes not only feasible but also crowned with success.

Tobias Jonas
Written by Tobias Jonas CEO

Cloud-Architekt und Experte für AWS, Google Cloud, Azure und STACKIT. Vor der Gründung der innFactory bei Siemens und BMW tätig.

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