Read handbook: Cognizant - Generative AI Handbook

How are early pioneers applying GenerativeAI

• Expert assistants for professional work
  • Generative AI assistants being used in legal software to augment services and accelerate work
• Media generation
  • Entertainment and creative studios using Generative AI to create animation sequences, social reels and more
• Market Insights
  • Aggregating customer feedback (reviews, call, transcripts, etc.) for Generative AI-driven insights
• Text to software product generators
  • Generative AI using component libraries, design system and code bases to build POC software "on-demand"
• Interactive chat-bots
  • Transforming the classic chat-bot, Generative AI powering conversational agents to answer and explain

Known strengths of Generative AI

1. Complex process automation
2. Data augmentation and completion
3. Predictive analysis
4. Driving efficiency and supporting knowledge work
5. Real time optimization
6. Multimedia generation

Known weak points of Generative AI

1. Hallucinations
2. Data quality and AI safety
3. The explainability problem

7 use-cases to inspire Generative AI exploration

1. Market and Competitor Intel
2. Software Development
3. Production
4. Marketing and Sales
5. Expert Advisors
6. Employee Engagement
7. Customer Experiences

Practical guidance for adaptive and leading in a Generative AI world

1. Provisioned initial access to Generative AI tools
2. Put near-term focus on disruptive POCs
3. Introduced AI to the development process
4. Maximized digitization of core business operations
5. Set new expectations with our suppliers

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