Measuring and managing value and risk for AI projects in an organization
It is a well-known fact that most Data (AI) projects don’t make it to production. This is due to various
risks associated with people, process, and technology aspect of use-case development and
productization. In this project our goal is, to create an advanced business process automation and
optimization tool that helps organizations quantify, measure and manage value and risks
associated with data (AI) projects, track progress of data (AI) projects through different stages of
development (ideation, experimentation, MVP, Production, maintenance and retire or
decommissioning) and recommend actions organizations can take to move forward on their data (AI)
journey i.e. from a low data maturity organization to a high data maturity organization. To the best of
our knowledge such a tool does not exist though similar tools are commonly used in other business
processes within organizations e.g., financial risk estimation tools, business process automation tools
etc.
The goal of the project is to develop a software solution that
- Follows a research-backed approach to quantify value and risks associated with data (AI)
projects - Allows organizations to manage the value and risk of data (AI) initiatives along the AI project
lifecycle
The goal of this call for workshop participation is to determine the desirability and viability of such a
software solution.
We are looking for participants for the 1/2-day databooster shaping workshops to confirm
desirability and viability.
To confirm desirability, we want to understand whether this is currently a question that is raised in
organizations. If the question is raised, how are they solving the problem of risk estimation and
measuring value of data and AI initiatives? We want to understand if the timing is right, as well as what
further pain points can be identified in organizations that are not on our radar yet.
To confirm viability, we will explore what the economic value would be for organizations to be able to
measure and manage value and risks of AI initiatives, from which we aim to derive a potential business
model.
The initial involvement will be 1/2 day, we will however invite the workshop participants based on
the ability and desire to become industry partners for the research or development partner for an MVP
of the product.
We are looking for industry partners in mature organizations that have a significant workforce working
on AI (ca. 5-10 or more FTEs focusing on data and AI) and have brought at least one data (AI) project
into production. A consulting company in data space could also be such a partner. We are interested
in participants coming from both a business background as well as the data science technical side.
Participants should be (or be in direct contact with) decision makers. We are looking for participants
that either are regularly involved in their organization’s AI strategy or in meetings that are deciding on
continuation of specific projects.
Depending on availabilities the workshop will take place either in December 2022 or January 2023
