A strategic approach to setting up a AI Center of Excellence(CoE)

The word AI, creates quite a lot excitement and expectations in everyone's mind. It also creates a sense of 'aura', some sort of a magical expectation that it can perform everything, that a human can perform. This has an adverse impact. The technique precedes the problem and every idea seems to be a candidate that can be solved by AI/ML. Hence managing this hype and expectation is the first and foremost challenge a Data Scientist and a leader of a COE faces. The second challenge is the data readiness of the organization.

This presentation aims at sharing the wisdom gained from the experience of setting up a global AI practice, the trials and tribulations one goes through in balancing the expectations from the team, stakeholders and organization.

Will share some of the sweet and bitter experiences so that we are fearless in articulating the reality when stakeholders come with the hyped up expectations.


Outline/Structure of the Experience Report

Factors to be considered when setting up a COE

Strategic choices in selecting Business Partners and focus areas

Processes for assessing Use case Value

Developing the AI/ML Competency

Developing the eco-system

Branding strategies for a AI COE

Learning Outcome

The mindset of a AI COE leader

Things that one should not do, when setting up a COE

The way to focus and pick the right areas for delivering value

Techniques to stay away from noise and hype of AI

Target Audience

Senior Data Scientists, Data Science Managers, CXOs and Leaders

Prerequisites for Attendees

Participants can be Data Scientists, Data Science Managers and CXOs. A preliminary understanding of Data Science and having implemented couple of use cases, would help.

schedule Submitted 1 year ago

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