EN

AI Experimenter

Taking the first steps to AI maturity: Driving awareness and first AI success stories

Steps of the AI Maturity journey

The Experimenter

The Practitioner

The Professional

The Scaler


The beginning

Take your first step on the road to AI Maturity

90% of organizations in Germany are just about to take their first steps. This journey is not an optional one, it will hit every company, just as all revolutionary technologies do. Managers and decision makers are starting to be broadly aware of the importance of this technology. And they realize: Starting with AI is not hard at all if one understands and accepts its experimental nature.

What it means

Being an experimenter

Experimentation is the first step of every AI agenda and journey, and it starts at the very top of the organization. AI experimenters spark interest and lobby for AI across the company to reach and enable management as well as core employees [AI Services]. It is driven by the realization that the company is in need of a vision that embeds AI and a strategic approach to follow that vision. Part of the journey is a clear communication inside the management group as well as towards the overall organizations [White paper - Building the organization for scaling AI]. To "walk the talk", these first steps are always accompanied by selecting and experimenting with first technical use cases that solidify the need for AI technology. It is then that change management gets involved and the first shadow IT approach to AI infrastructure appears to keep up speed.

How appliedAI can help

Services for experimenter

Academy

AI Introduction course

Artificial Intelligence means very different things to different people and stakeholders. A necessary first step on any AI-journey is to create a common and shared layer of understanding, interpretation, and expectation towards AI-Technology. In this course, we lay the foundation for an AI-Journey by creating a broad, shared perspective on AI and the current technology behind it.

Academy

AI Strategy course

Asking and answering the right questions early on is a primer for success when applying AI. A fundamental first step is getting a clear picture of what an AI strategy consists of and how it relates to the business goals. In this course, we give you a tested and proven methodology for this and deep dive into the specification and implementation of the "Strategy house".

Engineering

Technical Proof of Concept development

All technical implementations should start with a "proof of concept" that shows the technical feasibility of the use case. However, a PoC must also validate the potential for return on investment as well as scalability, usability and maintainability. We build a PoC in short sprints for you with the goal of enabling the next step: Engineering a complete AI-Solution.

Strategy

Exchange of best-practices between leaders

AI is a new technology and right now there is only a little common wisdom about how to apply it. So at appliedAI we foster the exchange between all our partners. At the core of appliedAI is the exchange of best-practices between individual leaders of companies, be it multinationals / DAX or SMEs. Get in touch with other CXOs, managers or fellow AI-Agenda owners.

Strategy

Usecase discovery and specification

There are plenty of opportunities that can be taken with AI-Technology. We help you to identify these opportunities, to specify them and to prioritize them. This includes asking AI-specific questions, understanding the data behind it and building an implementation roadmap. If you want to move quickly then our engineering team can implement the solution for you.