Site Content

---

Value:  

Generate early wins and build on them, such as creating use cases that will be game changers for the company. Implement a use case qualification framework and appoint an owner of use case qualification. Track value creation as early as possible and assign an owner of value tracking to coach and evangelize
on the value of AI for the organization

Vision: 

Evaluate their current AI maturity and communicate on it. Determine the organization’s short-, medium-, and long-term visions for AI. Start choosing and mapping out specific use cases
for each stage of the vision

Leverage Data: 

Leverage the data accessible to them. Provide wide self-access to data in order to foster
democratization

System: 

Start operationalizing their AI projects in parallel to their infrastructure transformation projects.
Experiment in agile mode, setting up formal and regular use case ideation and review sessions.
Take a platform mindset — one platform with multiple instances to scale resources up and down in an elastic, responsible, and governed way

Governance: 

Ensure their data is of high quality, usable, and secure. Aim to find a balance between auditability and permission management that doesn’t stagnate the organization’s efforts to accelerate their ability to use data at scale

Talent : 

Define and lead the initial effort for talent hiring, retention, and upskilling. Design the best experience for their existing cross-profile workforce