Lead & Innovate
Becoming AI future-ready by embedding AI in all decision-making and creating new AI-driven business models.
AI Future-Ready
Organizations that reach this final stage are considered "AI future-ready." AI is deeply embedded in all aspects of the organization, from strategic decision-making to daily operations.
These organizations are not just consumers of AI; they are creators and innovators, developing proprietary AI capabilities and using them to drive new business models and disrupt their industries. Only 7% of enterprises have reached this stage.
Key Activities
Embed AI in All Decision-Making
AI-driven insights are a core component of all major business decisions, from product development to customer service. Leaders decide when humans need to be in the loop and when they don't.
Develop Proprietary AI
Invest in research and development to create proprietary AI models and algorithms that provide a unique competitive advantage.
Create New Business Models
Leverage AI capabilities to create entirely new products, services, and business models that were not previously possible.
Shape the Ecosystem
Actively participate in and shape the broader AI ecosystem, collaborating with research institutions, startups, and other partners to drive innovation.
AI-Driven Business Models
In this final stage, AI is embedded in all decision-making, and organizations are using proprietary AI internally. They then sell new business services based on that capability, the AI capability as a service, or both to other enterprises.
AI-Enhanced Products and Services
Embed AI capabilities into core products and services, creating differentiated offerings that competitors cannot easily replicate. AI becomes a key value driver for customers.
AI as a Service
Package proprietary AI capabilities as services that can be sold to other enterprises. This creates new revenue streams and positions the organization as an AI leader.
Platform Business Models
Create platforms that connect multiple stakeholders and use AI to orchestrate complex interactions, generate insights, and create network effects.
Data Monetization
Leverage proprietary data and AI models to create valuable insights that can be monetized, either directly or through improved products and services.
Combining People and Platforms with Four Types of AI
Executives expect that the most value from AI will be created from combining people and platforms with four types of AI:
Analytical AI
Processes data to identify patterns, make predictions, and generate insights that inform decision-making.
Generative AI
Creates new content, designs, code, and solutions based on learned patterns and human guidance.
Agentic AI
Autonomous agents that can perform tasks, make decisions, and take actions within defined parameters.
Robotic AI
Physical robots and automation systems that combine AI with mechanical capabilities to perform tasks.
Characteristics of AI Leaders
All-In on AI-Enabled Decision-Making
AI is not just a tool but a fundamental part of how the organization makes decisions. Leaders have clear frameworks for when humans need to be in the loop and when AI can operate autonomously.
Continuous Innovation Culture
Innovation is not a special project but a continuous process. The organization constantly explores new AI capabilities and applications.
Ecosystem Leadership
These organizations don't just use AI—they help shape its development through partnerships, research, and thought leadership.
Sustainable Competitive Advantage
Proprietary AI capabilities create defensible competitive advantages that are difficult for competitors to replicate.
Maintaining AI Leadership
Reaching Stage 4 is not the end of the journey—it's the beginning of a new challenge: maintaining leadership in a rapidly evolving field.
Continuously monitor emerging AI capabilities and assess their potential impact on your business
Maintain significant investment in AI research and development to stay ahead of competitors
Build a reputation as an AI leader to attract the best AI researchers, engineers, and practitioners
Maintain strong ethical frameworks and responsible AI practices as capabilities advance