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Digital trends II:
Supercharge your enterprise strategy: Generative AI Playbooks

May 24, 2024
9 min read



Kanchan Ray,
Chief Technology Officer (CTO) at Nagarro, leads innovation topics and helps customers transform their business.


Rahul Mahajan
is Chief Technology Officer 
(CTO) at Nagarro. He pushes the boundaries of what is possible for the customers.

We have explored the digital frontiers of expanding user base (Digital Trend I: cracking the next billion: expand digital markets into digital ecosystem). Now let's dive into the next game changer for your business: GenAI-powered playbooks.

Generative AI Playbooks: the future of fluidic transformation

As businesses look to leverage Generative AI and big language models to adapt to fluidic forms of transformation— integrating AI/ML workflows into an organization's digital and data architecture becomes key. Every enterprise has a variety of use cases along the value chain where AI/GenAI can play a significant role in decision-making and workflow automation. One trend we are seeing is the creation of AI-led playbooks that help with AI-powered execution and even combine use cases across the value chain. 

What are Generative AI Playbooks?

They are computationally generated, AI-agent-assisted solution recipes for complex B2B/B2C problems. These playbooks are interactive, can run simulations, are connected to a digital twin, are LLM-supported, and are compatible with human language. The solutions in the playbook can contain a future catalog of actions that can be rendered or activated on a variety of channels and devices, intelligently connecting different products, services, ecosystem services, or products with the aim of maximizing utility value.


When we look at persona journeys across the value chain, each journey is unique, but all have the potential to be transformed by AI, which provides a solid foundation for efficient, long-term transformation. Today, it's all about speed – building new experiences and business models quickly. An ideal playbook covers different parts or applications and can influence different areas within the organization to turn isolated applications into an enterprise-wide transformation project. 

Generative AI-based intelligent playbooks are used to create dynamic tactics and workflows for different situations, such as maximizing profits on unsold inventory by predicting customer needs and designing successful sales strategies. GenAI uses rich language models to weave digital knowledge into actionable playbooks that orchestrate your ML firepower. 

Today, advanced MLOps can automate your AI playbooks and run both planned scenarios and “what-if” simulations. It’s like having an AI co-pilot that tests every option and constantly optimizes, with or without constraints, to maximize your key performance indicators. It’s not just efficiency, it’s a dynamic feedback loop that guides your business step-by-step to optimal results. 

This AI-first paradigm embeds intelligence, starting at the core with AI/ML models woven into the fabric of your digital and data architecture. It's a system in which prompt engineering is not just a tool, but the foundation to automatically generate and optimize playbooks for every step of your value chain. It's a seamless symphony of AI that animates every corner of your business. 

Generative AI Playbooks: exemplified

Retail and Manufacturing

A business could use AI to create playbooks that automatically manage the surplus stock, optimize trade routes, and boost demand – all based on real-time data and ROI models. That’s not just efficiency but a self-evolving ecosystem of AI-powered plans that transform every aspect of your business, one adaptable solution at a time. 

What's more, B2B retailers are using AI-powered playbooks to develop real-time sales strategies: personalized retail offers tailored to customers based on just a handful of key attributes. This is more than just automation – it’s an ever-evolving ecosystem of intelligent plans that drive your business forward, one data-driven decision at a time. 

A man working in a manufacturing setup wearing VR glasses


 A college student is looking for a wellness solution. Imagine AI generates an integrated AI playbook for the student that is detailed for the next few weeks and includes the following: 

  • A 360-degree wellness plan connecting diet, fitness, allergies, nutrition, etc.
  • Connecting the student with partners for extended services
  • Tracking and adjusting to progress 

Creating such a playbook is not trivial and requires smart orchestration across different parts while keeping it simple enough to use. An enterprise-ready solution with the right level of governance, observability, and explainability is critical to scaling the solution. 

A happy woman at the beach

What's the need?

In the rapidly evolving digital transformation landscape, the emergence of “Generative AI Playbooks” is a response to the urgent need for organizations to manage fluidic and unique transformation processes efficiently. As businesses strive to digitize their core operations, the ability to quickly adapt and assemble new experiences or business models is critical. Traditional methods such as fixed dashboards, specific problem-oriented apps, or isolated ML models are not sufficient in this dynamic environment. Therefore, the development of playbooks that leverage the power of Generative AI and large language models is required. 

The need stems from the urgency to transform isolated applications into enterprise-wide strategies that enable a longer-term horizon and a greater focus on operational efficiency. Organizations are looking for a solution that enables them to make informed decisions, plan effectively, and execute AI-based tactics and workflows in different situations. This demand is particularly evident in industries such as manufacturing and consumer-facing sectors, where Generative AI playbooks can play a central role in overcoming challenges such as excess or obsolete inventory and formulating commercial strategies to increase demand. 

The opportunity

The Generative AI Playbooks trend presents a significant opportunity to leverage Generative AI and large-scale language models to adapt and transform quickly. Develop comprehensive playbooks that impact different parts of the organization and orchestrate isolated applications into a cohesive, enterprise-wide transformation strategy.

For instance, in B2B retailer digital transformation, organizations can create sales playbooks that leverage Generative AI to create real-time, contextual retail offers based on multiple capabilities. This creates a new generation of playbooks for digital scenarios that enable businesses to overcome dynamic challenges in their respective industries.

Beyond regular MLOps, LLM agent-led action workflows are even more powerful. This includes executing scenario plans and what-if analyses incorporating constrained and unconstrained optimization techniques to maximize key performance indicators (KPIs). The opportunity extends beyond simply adapting to change; it involves proactively shaping the future of business operations through the strategic use of Generative AI playbooks. 

The shift

A city skyline with skyscrapers

Build an AI-first architecture

Implement an AI-first architecture that extends to your company's foundational digital and data architecture. This is not just about adding AI but about realigning your business around AI. Think of dynamic plans driven by AI and machine learning that weave together existing systems, data, and knowledge. This includes executing AI-powered automated workflows considering the target state, seamlessly orchestrating AI and ML models together with ontology-based knowledge retrieval, executing automated scenarios, and connecting APIs with existing systems. By leveraging the capabilities of large language models to vectorize digital knowledge, potential tactics in the playbook are transformed into business-friendly stories.

An illustration depicting a robot using a screen

Extend AI LLM engineering

Extend AI LLM Instant Engineering to generate and automate various automated stories related to playbooks across the organization’s value chain. This includes the development of AI-powered tactical actions or tasks and workflows that cover a variety of scenarios, e.g. intelligent management of overstocks to the formulation of trading strategies or sales playbooks.

image 9Illustration of a brain showing the relationship between AI and human decision making

Symbiotic Generative AI and human intelligence

Integrate Generative AI into the structure of business processes and create a symbiotic relationship between human decision-making and AI-driven insights. This represents a shift towards an intelligent and adaptable business that can master the complexity of digital transformation with agility and foresight.


Traditional transformation methods do not do justice to today's dynamic business landscape. Generative AI playbooks offer a solution: AI-powered, self-adapting playbooks that use rich language models to create intelligent workflows and tactics. These playbooks unify siloed AI applications, optimize decision making, and automate tasks to increase efficiency. This opens new opportunities for manufacturers, retailers, and consumers alike while requiring a shift to an AI-centric architecture with LLM automation and a human-AI collaboration approach. Generative AI playbooks empower businesses to become intelligent and adaptable to conquer the ever-changing digital world. 
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