AI Practitioner

Solidify your AI agenda: Implementing the AI strategy and driving value through operationalized AI applications

Steps of the AI Maturity journey

The Experimenter

The Practitioner

The Professional

The Shaper

The operationalization

Systematically drive business value through AI technology

AI is often considered a "technology", when really it is much more: a shift in paradigms how value is created. Since 2019 many companies started to realize that an AI agenda and first "proof of concepts" are deceivingly easy to start. But it turns out to be fiendishly hard to operationalize. Conventional wisdom about "digital products" seems to translate poorly to AI.

What it means

Being a practitioner

Operationalization is the first and major challenge each AI strategy and its implementation faces [White paper - Building the organization for scaling AI]. Practitioners are taking on the challenge to systematically develop and implement their AI strategy, focusing on optimizing processes or re-inventing products [White paper - AI Use Cases]. This includes a principled approach to identifying opportunities, setting up central AI-Teams and first cooperations [2020 AI German Startup Landscape], setting up the right training programs for the organization and preparing the AI data strategy. Change management becomes heavily involved in reducing barriers. Technical prototypes are taken from a "proof-of-concept" to a running service and processes are adapted to allow for the new type of development AI systems ask for.

How appliedAI can help

Services for practitioners


AI Project Management course

If you implemented an AI system already, you will know this: Managing AI projects is very different from managing classical software development. AI poses its own challenges, on the development team, on the managers, on the company, and on the user. In this course, we teach you the basics of AI project management and introduce you to our battle tested framework ("RAID") for it.


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, how to create an AI vision 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".

Click here for a preview of our AI Strategy Workshop


Comprehensive digital AI Academy programs

AI transforms all areas and units of the company. Just as the internet did. A holistic AI reskilling program is part of a broader AI strategy and adding the elements to it that fit your company is a complex task. We give you the blueprints to do this and develop them further with you to suit your companies needs. We also share the original course content with you and your employees to get you ready to take the next steps in adopting AI in your company.


AI Product development

If you grasp AIs potential, you will inevitably rethink your products and change their inner DNA to utilize AI-Technology. We have a lot of experience about what it means to bring an AI-System into production, and it is fiendishly hard. We know about the challenges that are "technical debt" or "user acceptance / UX" and "scalability" and how they are different for AI-Systems. We build these systems for you based on our experience of 35+ implementations so far. For an example of product development see our Village Data Analytics (VIDA) case study, an earth observation and AI-powered custom software.


Being your AI center of excellence

A proven structure to act quickly and autonomously is the AI-Center of Excellence that most companies adopt relatively early. However, it requires the right surrounding and factors to attract the talents, right enablers, roles, and people. appliedAI can bootstrap your AI-Center of Excellence (AI-CoE) and run it for you long-term.


AI strategy and organization development

Defining your AI-Strategy means not only asking the right questions but knowing what to do to achieve each goal exactly. Executing on an AI-Strategy can be fiendishly hard so we are your partner in making it work. Our approach to AI-Strategy implementation and organizational development is based on our view on "building the organization for scaling AI".


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.

Case Study - EnBW

Towards scaling AI across the organization - How EnBW is driving AI in its business units. Read the following case study to find out more about the approach and methodology used to help EnBW on their journey to AI maturity!

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