Quickly from AI potential to tangible reality!

After a potential analysis has identified promising potential applications for artificial intelligence (AI) in your company, you are now faced with the next hurdle: How do you transform these abstract ideas and potentials into a concrete, value-adding application? This is exactly where the concept of AI prototyping, as offered by Vicosmo, comes in. It is the logical and strategically smart next step to turn your AI vision into reality.

What exactly is AI prototyping?

AI prototyping is an iterative process in which a simplified but functional version of your planned AI application is developed. It is not about immediately building a perfect, production-ready solution. Rather, prototyping concentrates on defining the core functionalities and the central assumptions of your AI idea quickly and in a resource-efficient manner.

An AI prototype can take various forms:

• A proof-of-concept (PoC): Primarily demonstrates the technical feasibility of a particular AI method for a specific problem.
• A functional prototype (MVP): Already implements core functions and often allows initial interactions to demonstrate the benefits.
• A user interface (UI) mock-up with simulated AI: Visualizes the user experience, even if the AI behind it is not yet fully developed.

Why is prototyping so important for AI projects?

AI projects often differ from classic software development in that there are greater uncertainties:

• Data dependency: Will the idea work with the actual data available? Is the data quality sufficient? Prototyping provides early answers.
• Algorithmic complexity: Is the chosen AI approach (e.g. machine learning model) really suitable to solve the problem? A prototype allows models to be tested and adapted on a small scale.
• Unclear success criteria: What does “success” mean for AI? Prototyping helps to define and check measurable criteria (KPIs).
• High investment costs: Full AI development can be expensive. Prototyping is a cost-effective way to drastically reduce the risk of a bad investment before significant funds are committed.
• Acceptance and understanding: A tangible prototype makes the AI idea understandable for stakeholders (management, specialist departments, future users) and promotes acceptance. It enables valuable early feedback.

The process of AI prototyping

Vicosmo guides you through this process, which typically includes the following steps:

• Concretization of the idea: Joint refinement of the use case and definition of the goals for the prototype. What exactly should be validated?
• Data assessment: Checking the availability and quality of relevant data. If necessary, identification of data gaps.
• Design & technology selection: Design of the prototype architecture and selection of suitable AI methods and tools.
• Agile development: Iterative development of the prototype in short cycles (sprints), often starting with the riskiest assumptions.
• Testing & Validation: Systematic testing of the functionality and performance of the prototype. Measurement based on the defined KPIs.
• Demonstration & feedback: Presentation of the prototype to stakeholders and collection of feedback for further development or decision on next steps.

What do you gain from AI prototyping with Vicosmo?

• Validated feasibility: You know early on whether your AI idea is technically feasible and will work with your data.
• Clear proof of benefit: You can demonstrate and quantify the potential added value of the AI application.
• Realistic market assessment: The prototype helps to better understand the interest and requirements of potential users or customers.
• Risk minimization: You make informed decisions about further development and avoid high costs for unpromising approaches.
• Accelerated development: The findings from prototyping flow directly into the development of the final solution and accelerate it.
• Stakeholder buy-in: A working prototype convinces decision-makers and promotes internal support for the project.

Vicosmo’s “AI Prototyping” offer is therefore a decisive catalyst to benefit from a promising AI potential analysis to a validated, tangible application. It is a structured, low-risk and cost-efficient approach to set the course for a successful implementation of your AI vision and ensure that your investment in AI delivers the deliver the desired business value.

It transforms the “What if?” into a “This is how it could work!”.