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AI/ML and GenAI at Weaver - Coggle Diagram
AI/ML and GenAI at Weaver
Current AI Usage and Audit :
Introduction: overview of AI implementation at Weaver (FC/PJN)
PJN
FC
Current AI Use Cases
PJN
Personalised recommendatons
Fraud detection: ML models
Customer service
FC
Document automation
Fraud detection
AI/ML Roadmap
Short-term goals (6-12 months)
Enhance existing AI apps/use cases
Integrate AI with further business processes
Medim-term goals (1-3 years)
Expand AI capabilites to new areas such as predictive analyics
Implement AI governance framework
Long-term goals (3-5 years)
Fully integrate AI into all core business functions
Building AI Capability and Competence
Skills Development
Technical training (ML, data science, AI ethics)
Business training: Understranding AI impact on business process
Toolset adoption: making ChatGPT, CoPilot and other tools available to employees
Hiring Strategies
Attracting AI talent through competitive packages and strong AI vision
Collaboration
Partnerships e.g. Dino/Cerasomma/Ecosystem.ai
Data Strategy
Data Governance
Data infrastructure
Data integration
Data analytics
People and Training for AI Leadership in Fintech
Leadership Development: training leaders on AI strategy & implementation
Employee training: regular workshops and courses on AI tools and techniques
AI literacy: making AI concepts available to non-tech staff
Culture of innovation: encouraging experimentation and innovative thinking with AI
Gen AI Use Cases
Content creation
Product design
Customer engagement
Software engineering
Insurance
Introduction
What is AI
Types Of AI
Common AI applications
AI in Fintech
Why AI matters