WORKING PAPER

Beyond the Chatbot | 10 AI Strategies to Shape the Future

By Stephen Wunker

This framework helps leaders move from experimenting with AI to truly transforming their business:

Revealing ten types of AI innovation, from reimagining value chains to creating entirely new revenue models, that expand what’s possible

Guiding companies to align AI strategy with real customer needs, not just technical capabilities

Offering a disciplined, customer-centered process to prioritize opportunities, test rapidly, and scale with confidence

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Summary

Beyond the Chatbot: 10 Strategies to Use AI in Shaping the Future by Stephen Wunker presents a clear roadmap for moving past surface-level AI applications toward transformative business innovation. It categorizes AI’s potential into four areas—Ecosystem, Business Model, Product, and Customer—each with distinct opportunities for rethinking how organizations create and deliver value. Through vivid examples and practical questions, the paper helps leaders identify where AI can make a genuine difference—redefining markets, driving efficiency, and unlocking new sources of growth.

OVERVIEW

Why Rethinking AI Innovation Matters Today

AI has exploded into the mainstream, yet most organizations remain stuck at the experimentation stage — deploying chatbots or incremental automation without strategic transformation. Beyond the Chatbot reframes AI as a catalyst for re-shaping entire markets, not just improving efficiency. The report argues that meaningful AI innovation starts by identifying real customer needs and aligning technology to serve them. As AI redefines industries, leaders must ask: What kind of change are we truly seeking — and how can AI help us deliver it?

This section highlights that organizations must:

Move from isolated AI pilots to cross-functional strategy
Focus on customer-led, not technology-led, innovation
Treat AI as a driver of new markets and business models
Prioritize transformation that delivers measurable value

10 Types of AI Innovation

How to Get Started with AI Innovation

10 Types of AI Innovation

Based on a study of 5,000 innovations, New Markets Advisors found that the most transformative initiatives leverage five or more innovation types at once. The same is true for AI. These ten forms of AI innovation — spanning ecosystems, business models, products, and customers — show how companies can re-make industries through multi-dimensional change. Leaders should view these categories as combinable levers that amplify one another to create sustainable competitive advantage.

The 10 Types of AI Innovation include:

Value Chain: Streamline or automate intermediaries (e.g., Ping An’s digital insurance)
Partnerships: Combine datasets for new solutions (e.g., Bayer + Microsoft digital farming)
Revenue Model: Use AI to monetize data or customize pricing (e.g., Hungryroot)
Cost Structure: Reduce inefficiencies and automate reporting (e.g., Yseop)
Invention: Generate novel ideas or materials via AI (e.g., DeepMind)
New Value Propositions: Create hyper-personalized services (e.g., Paloma Learning)
New Demand: Identify untapped audiences with predictive insight (e.g., NeuraLight)
Experience: Transform user journeys with personalization (e.g., Nuance)
Acquisition: Optimize targeting and outreach (e.g., Verix)
Retention: Predict churn and drive loyalty (e.g., Flyfish)

Together, these innovation routes demonstrate how AI can reinvent how companies create, capture, and deliver value.

10 Types of AI Innovation

How to Get Started with AI Innovation

10 Types of AI Innovation

The 10 Types of AI Innovation include:

Value Chain: Streamline or automate intermediaries (e.g., Ping An’s digital insurance)
Partnerships: Combine datasets for new solutions (e.g., Bayer + Microsoft digital farming)
Revenue Model: Use AI to monetize data or customize pricing (e.g., Hungryroot)
Cost Structure: Reduce inefficiencies and automate reporting (e.g., Yseop)
Invention: Generate novel ideas or materials via AI (e.g., DeepMind)
New Value Propositions: Create hyper-personalized services (e.g., Paloma Learning)
New Demand: Identify untapped audiences with predictive insight (e.g., NeuraLight)
Experience: Transform user journeys with personalization (e.g., Nuance)
Acquisition: Optimize targeting and outreach (e.g., Verix)
Retention: Predict churn and drive loyalty (e.g., Flyfish)

Together, these innovation routes demonstrate how AI can reinvent how companies create, capture, and deliver value.

10 Types of AI Innovation

How to Get Started with AI Innovation

10 Types of AI Innovation

The 10 Types of AI Innovation include:

Value Chain: Streamline or automate intermediaries (e.g., Ping An’s digital insurance)
Partnerships: Combine datasets for new solutions (e.g., Bayer + Microsoft digital farming)
Revenue Model: Use AI to monetize data or customize pricing (e.g., Hungryroot)
Cost Structure: Reduce inefficiencies and automate reporting (e.g., Yseop)
Invention: Generate novel ideas or materials via AI (e.g., DeepMind)
New Value Propositions: Create hyper-personalized services (e.g., Paloma Learning)
New Demand: Identify untapped audiences with predictive insight (e.g., NeuraLight)
Experience: Transform user journeys with personalization (e.g., Nuance)
Acquisition: Optimize targeting and outreach (e.g., Verix)
Retention: Predict churn and drive loyalty (e.g., Flyfish)

Together, these innovation routes demonstrate how AI can reinvent how companies create, capture, and deliver value.

10 Types of AI Innovation

How to Get Started with AI Innovation

10 Types of AI Innovation

The 10 Types of AI Innovation include:

Value Chain: Streamline or automate intermediaries (e.g., Ping An’s digital insurance)
Partnerships: Combine datasets for new solutions (e.g., Bayer + Microsoft digital farming)
Revenue Model: Use AI to monetize data or customize pricing (e.g., Hungryroot)
Cost Structure: Reduce inefficiencies and automate reporting (e.g., Yseop)
Invention: Generate novel ideas or materials via AI (e.g., DeepMind)
New Value Propositions: Create hyper-personalized services (e.g., Paloma Learning)
New Demand: Identify untapped audiences with predictive insight (e.g., NeuraLight)
Experience: Transform user journeys with personalization (e.g., Nuance)
Acquisition: Optimize targeting and outreach (e.g., Verix)
Retention: Predict churn and drive loyalty (e.g., Flyfish)

Together, these innovation routes demonstrate how AI can reinvent how companies create, capture, and deliver value.

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About The Authors

Steve Wunker

FOUNDER & GLOBAL LEADER IN JOBS TO BE DONE

Steve pioneered JTBD alongside Clayton Christensen and has led innovation work worldwide. He authored Jobs to Be Done: A Roadmap for Customer-Centered Innovation and four other books, and his thinking appears regularly in publications such as Harvard Business Review, Forbes, and The Financial Times.

WORKING PAPER

Beyond the Chatbot | 10 AI Strategies to Shape the Future

By Stephen Wunker

Revealing ten types of AI innovation, from reimagining value chains to creating entirely new revenue models, that expand what’s possible

Guiding companies to align AI strategy with real customer needs, not just technical capabilities

Offering a disciplined, customer-centered process to prioritize opportunities, test rapidly, and scale with confidence

Download File