The Value Vector

Learn how to bring Generative AI applications to life, from conception to production, ensuring they deliver true business value. Follow Dr. Anya’s story as she implements AI in day-to-day business solutions, immersing you in the real challenges of AI-based product development and deployment. Through her journey and notes, you will experience a wide range of challenges and solutions firsthand, demonstrating how AI can be translated into compelling business cases, efficient technical architectures, and innovative applications.
The book begins with you understanding the AI Value Compass – a strategic framework that will provide you with a structure for AI implementation. It then dives into AI-led innovation and how you can extract the most valuable and interesting ideas from the waves of creative thinking that emerges from your organization. It also addresses AI literacy, helping you guide your teams in using AI to tackle the most pressing business challenges. 
Next, you will find a roadmap for creating a Proof of Concept for your AI application that don’t become outdated before review, showing how to build solutions that deliver value rapidly and efficiently. The journey continues as Dr. Anya guides you from a POC to production, teaching how to scale Generative AI applications for enterprise deployment. The book then tackles governance, security, and ethics - all of which are crucial aspects for implementing AI responsibly and sustainably. The final chapter explores the next wave of AI, introducing you to the era of AI agents.   
This book, by providing a comprehensive guide that combines practical advice, ethical considerations, and an incredibly engaging narrative, aims to equip you with the knowledge and tools you will need to successfully implement Generative AI projects that deliver real business value.

What You Will Learn:

• How to identify and prioritize valuable generative AI use cases that help organizations create a path to value.
• Techniques for developing effective POCs and transitioning to full-scale production , including architectural considerations for enterprise readiness.
• Essential ethical considerations in AI-based solution development and strategies to prevent misuse.
• Select, fine-tune and integrate AI models and avoid common pitfalls.