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Today, most organizations don’t lack AI ideas. On the contrary, use cases, pilots, and proof-of-concepts are piling up. Yet, strategic impact often remains limited—not because the technology falls short, but because ideas are treated too quickly as if they were already decisions.
The 4G model was developed to address this challenge. It forces organizations to separate four fundamentally different conversations: Generate, Ground, Grow, and Guard. Only when these conversations are conducted consciously and in the right context does AI strategy emerge, rather than just AI activity.
Today, most organizations don’t lack AI ideas. On the contrary, use cases, pilots, and proof-of-concepts are piling up. Yet, strategic impact often remains limited—not because the technology falls short, but because ideas are treated too quickly as if they were already decisions.
The 4G model was developed to address this challenge. It forces organizations to separate four fundamentally different conversations: Generate, Ground, Grow, and Guard. Only when these conversations are conducted consciously and in the right context does AI strategy emerge, rather than just AI activity.
Generate: produce ideas, not decisions
This phase explores AI possibilities. The focus is not feasibility or business cases, but breadth. The goal is to create options, not narrow focus. Look for different types of value: efficiency, quality improvement, risk reduction, and new opportunities.
A strong Generate portfolio feels uncomfortable: it contains ideas that contradict each other and are not yet logically connected. This is not a weakness—it signals that you haven’t started making choices yet.
Common mistake: Using Generate to justify a pre-decided direction. Then it’s not exploration, it’s packaging.
Want to learn how AI can enhance your strategic thinking as an executive? Discover the AI & Strategy for Executives Masterclass by Jeroen De Flander at TIAS Business School. In this three-day program, you’ll learn how AI can become a lever for smarter analyses, faster decision-making, and more effective strategy execution. Not a technical course, but a strategic exploration for those who truly want to make an impact.
Ground: confront reality
Ground tests ideas against reality. Two questions are central: does it work with the data we actually have, and does it fit within the organization as it functions today?
Ground is not just technical validation—it’s also an organizational stress test. Which roles need to change? Who loses autonomy? Where will resistance appear? An idea that only works if “everyone cooperates” won’t work.
Common mistake: Skipping Ground to move faster. Problems are then pushed downstream, increasing costs later.
Grow: from local idea to strategic scale
Many AI initiatives remain small and local. Grow determines whether an idea can be strategically relevant. Not: “Can this work?” but: “What is needed to make this work broadly and sustainably?”
This often goes beyond technology, touching ecosystems, partners, governance, and standards. Sometimes scale is only possible if other parties move along. Grow requires explicit choices: invest to scale, or consciously keep it local. Both are valid as long as the choice is intentional.
Common mistake: Assuming scale without establishing preconditions. The initiative then depends on exceptions and goodwill.
Guard: consequences, accountability, and control
Guard is often considered last, but it is strategically crucial. It addresses the consequences of AI use: what happens if the system makes mistakes? Who is accountable? Who can intervene, and on what criteria?
Guard is not an abstract ethical debate—it consists of concrete agreements. It touches compliance, reputation, safety, and trust. Without Guard, organizations hesitate to use AI fully. Some applications are stopped here rightly, because the risks outweigh the benefits.
Common mistake: Treating Guard as a checklist after the fact. This makes it defensive and inhibiting rather than guiding.
Why 4G isn’t a linear roadmap
While the model suggests an order, 4G is not a classic step-by-step plan. Organizations often move back and forth between the phases. New insights in Ground can generate new ideas in Generate, and issues in Guard may make scale in Grow undesirable.
The power of 4G lies not in the sequence, but in the distinction. Each “G” represents a different type of conversation, with different criteria and decision-makers. Mixing them leads to confusion and delays.
The always-relevant diagnostic question
When an AI initiative stalls, the key question isn’t “What should we do now?” but: “Which G are we stuck in?”
Are ideas still being generated while Ground is missing?
Is scale expected without Grow decisions?
Is Guard used as an excuse for inaction?
Answering this honestly usually reveals the real bottleneck immediately.
What the 4G model makes explicit
The 4G model shows that AI strategy is not a technological journey, it’s a series of management decisions. It forces organizations to:
avoid confusing ideas with decisions,
avoid confusing validation with scaling,
avoid confusing caution with control.
Organizations that consistently apply 4G run fewer projects, but better ones, with clarity on why some ideas are consciously not pursued.
Want to discover how AI can strengthen your role as a leader?Explore it in our AI & Strategy for Executives Masterclass. Interested? Contact Wendy van Haaren for more information.
Generate: produce ideas, not decisions
This phase explores AI possibilities. The focus is not feasibility or business cases, but breadth. The goal is to create options, not narrow focus. Look for different types of value: efficiency, quality improvement, risk reduction, and new opportunities.
A strong Generate portfolio feels uncomfortable: it contains ideas that contradict each other and are not yet logically connected. This is not a weakness—it signals that you haven’t started making choices yet.
Common mistake: Using Generate to justify a pre-decided direction. Then it’s not exploration, it’s packaging.
Want to learn how AI can enhance your strategic thinking as an executive? Discover the AI & Strategy for Executives Masterclass by Jeroen De Flander at TIAS Business School. In this three-day program, you’ll learn how AI can become a lever for smarter analyses, faster decision-making, and more effective strategy execution. Not a technical course, but a strategic exploration for those who truly want to make an impact.
Ground: confront reality
Ground tests ideas against reality. Two questions are central: does it work with the data we actually have, and does it fit within the organization as it functions today?
Ground is not just technical validation—it’s also an organizational stress test. Which roles need to change? Who loses autonomy? Where will resistance appear? An idea that only works if “everyone cooperates” won’t work.
Common mistake: Skipping Ground to move faster. Problems are then pushed downstream, increasing costs later.
Grow: from local idea to strategic scale
Many AI initiatives remain small and local. Grow determines whether an idea can be strategically relevant. Not: “Can this work?” but: “What is needed to make this work broadly and sustainably?”
This often goes beyond technology, touching ecosystems, partners, governance, and standards. Sometimes scale is only possible if other parties move along. Grow requires explicit choices: invest to scale, or consciously keep it local. Both are valid as long as the choice is intentional.
Common mistake: Assuming scale without establishing preconditions. The initiative then depends on exceptions and goodwill.
Guard: consequences, accountability, and control
Guard is often considered last, but it is strategically crucial. It addresses the consequences of AI use: what happens if the system makes mistakes? Who is accountable? Who can intervene, and on what criteria?
Guard is not an abstract ethical debate—it consists of concrete agreements. It touches compliance, reputation, safety, and trust. Without Guard, organizations hesitate to use AI fully. Some applications are stopped here rightly, because the risks outweigh the benefits.
Common mistake: Treating Guard as a checklist after the fact. This makes it defensive and inhibiting rather than guiding.
Why 4G isn’t a linear roadmap
While the model suggests an order, 4G is not a classic step-by-step plan. Organizations often move back and forth between the phases. New insights in Ground can generate new ideas in Generate, and issues in Guard may make scale in Grow undesirable.
The power of 4G lies not in the sequence, but in the distinction. Each “G” represents a different type of conversation, with different criteria and decision-makers. Mixing them leads to confusion and delays.
The always-relevant diagnostic question
When an AI initiative stalls, the key question isn’t “What should we do now?” but: “Which G are we stuck in?”
Are ideas still being generated while Ground is missing?
Is scale expected without Grow decisions?
Is Guard used as an excuse for inaction?
Answering this honestly usually reveals the real bottleneck immediately.
What the 4G model makes explicit
The 4G model shows that AI strategy is not a technological journey, it’s a series of management decisions. It forces organizations to:
avoid confusing ideas with decisions,
avoid confusing validation with scaling,
avoid confusing caution with control.
Organizations that consistently apply 4G run fewer projects, but better ones, with clarity on why some ideas are consciously not pursued.
Want to discover how AI can strengthen your role as a leader?
Explore it in our AI & Strategy for Executives Masterclass. Interested? Contact Wendy van Haaren for more information.