Case study 02 · Comcast
Enterprise AI Transformation
Enterprise-wide AI transformation spanning Microsoft Copilot adoption, intelligent automation, conversational AI and AI-assisted productivity across 1000+ users.
- Company
- Comcast
- Role
- AI Solutions Architect
- Timeframe
- Oct 2021 – Apr 2024
- Location
- United States
- Enterprise AI
- Microsoft Copilot
- Automation
- Conversational AI
- AI Adoption
01The challenge
Bringing AI into daily work at enterprise scale is as much an architecture and adoption problem as a technology one. Copilots, automation and conversational AI have to fit existing systems, security expectations and ways of working.
The initiatives needed to reach a large user base while staying aligned with enterprise architecture principles, cybersecurity and operational reliability.
02Keerthi's role
Keerthi led enterprise-wide AI transformation initiatives as AI Solutions Architect, working across product, engineering, infrastructure, operations, cybersecurity and vendor teams.
- Led AI transformation initiatives involving Microsoft Copilot adoption, intelligent automation, conversational AI, operational intelligence and AI-assisted productivity.
- Kept solutions aligned with enterprise architecture principles across cross-functional and vendor teams.
- Contributed to architecture governance, observability, release management and deployment strategy.
- Built executive dashboards in Power BI and Tableau for decision-making and KPI monitoring.
03Architecture / approach
AI capabilities were introduced as part of the enterprise landscape rather than beside it, connected to the systems and data people already rely on.
- 01
AI-assisted productivity
Microsoft Copilot adoption and conversational AI brought AI assistance into everyday work across the user base.
- 02
Intelligent automation
Automation depends on the systems underneath it. The broader architecture integrated CRM, order management systems and operational platforms through APIs and event-driven integration.
- 03
Operational intelligence
Executive dashboards and operational intelligence in Power BI and Tableau made adoption and operations visible to decision-makers.
- 04
Governed rollout
Architecture governance, cybersecurity alignment, observability and release management kept the program consistent as it scaled.
04Technology
AI & Productivity
- Microsoft Copilot
- Conversational AI
- Intelligent Automation
Integration
- REST APIs
- Kafka
- Event-Driven Architecture
- CRM
- OMS
Analytics
- Power BI
- Tableau
- SQL
Platform
- Kubernetes
- Docker
- CI/CD
05Enterprise value
AI-assisted productivity, automation and conversational AI brought to 1000+ users within an enterprise architecture and governance framework.
- Users across AI transformation initiatives
- 1000+
- Enterprise-wide AI transformation initiatives spanning 1000+ users.
- AI capabilities aligned with enterprise architecture principles and cybersecurity requirements.
- Executive visibility through operational intelligence dashboards and KPI monitoring.
Outcomes are described qualitatively. Figures appear only where they are verified.
06Architecture diagram
Users
- 1000+ users
- Business teams
- Leadership
AI experience
- Microsoft Copilot
- Conversational AI
- Dashboards
Automation
- Intelligent automation
- Workflow automation
- Operational intelligence
Integration
- REST APIs
- Kafka events
- CRM
- OMS
Platform
- Kubernetes
- Docker
- CI/CD
07Key takeaways
- 01
Adoption is part of the architecture. An AI capability nobody uses has no enterprise value.
- 02
AI assistance becomes useful when it is connected to the systems where work already happens.
- 03
Give leadership visibility early; dashboards make the transformation measurable and discussable.