Strengthened AI governance
Efficient project onboarding
Optimized AI operations
Scalable AI industrialization
The challenge
Responsible AI framework for scalable deployment
A leading telecom company aimed to implement a Responsible AI framework for Authorization to Operate (ATO) and Fraud Detection. The goal was to establish best practices from ideation to decommissioning while integrating a Governance Framework to ensure scalability and compliance across both legacy and new solutions.
Key challenges
Coordinating diverse teams effectively
Establishing scalable, compliant procedures
Ensuring adherence to Responsible AI standards
Leveraging capabilities for ethical AI deployment
The solution
Optimizing AI governance
Platform assessment
Identified gaps
Mapped AI integration
Evaluated governance and metadata
Scalable AI framework
Built flexible architecture
Reduced upgrade risks
Ensured scalability
Implementation approach
1
Automated governance
Embedded AI governance
Streamlined approvals
Enabled compliance checks
2
Collaborative execution
Ensured smooth deployment
Partnered with teams
Aligned with goals
3
Optimized AI workflows
Standardized SOPs
Improved lifecycle
Enhanced ML efficiency
The impact
Driving scalable and responsible AI
AI governance
Standardized framework
Compliance checklists
Improved oversight
Efficiency gains
45% effort reduction
Streamlined onboarding
Clear entry and exit rules
Scalable AI
AI CoE setup
40% use case boost
Enabled industrialization
Looking ahead
Strengthening governance
Expanding AI governance framework
Smarter compliance
Enhancing automation for compliance
Scaling Responsible AI responsibly
Scaling Responsible AI adoption
