Anticipate change. Navigate complexity. Shape what comes next.
Foresight Navigator maps complex defence and AI ecosystems to show how the pieces connect, what is changing, and where the tipping points are.
01
The system map
Actors, organizations, technologies, programs, capital, infrastructure, policy, relationships and dependencies.
02
The tipping points
Where pressure, dependency, timing, interoperability, incentives or coordination can move more of the system than a single tool can.
03
The implications
What the map means for the specific decision: where to look, who matters, what is blocked, what is changing and what deserves attention next.
Proof / selected work
Look at the work.
These are examples of the same analytical workflow applied to different systems.
PHYSICAL AIPARIS / MACHINACORPUS
What is stopping dexterous robotics from becoming deployable?
Source base: a conference corpus spanning robotics platforms, dexterous manipulation, foundation models, simulation, tactile sensing, teleoperation, safety, commercialization and industrial deployment.
Finding: the central problem was not whether the hand could perform a demo. The system bottleneck was dependable deployment including data, safety, integration, workflow, support and economics around the hardware.
Individual technologies were treated as components of a coupled system. The tipping point moved away from “better end-effector” toward proving the complete task and deployment system.
DEFENCE AIARCHITECTURE DEPENDENCYPUBLIC-SOURCE
What happens when a model is embedded deeply enough that it cannot simply be swapped?
The question was treated as a dependency problem across prompts, workflows, agents, data, validation and users not as a vendor-news story.
Finding: model dependence can become operational dependence when model-specific behaviour is distributed through the surrounding system.
The map reveals where replacement costs accumulate. The tipping point becomes architectural modularity, evidence, failover and re-validation not just model choice.
GLOBAL AI ECOSYSTEMFIELD RESEARCHGEOPOLITICS
Where does power sit in the AI system?
The research lens spans companies, governments, capital, compute, chips, energy, data, regulation, alliances, procurement and defence.
The better question is not “what are the AI trends?” It is which dependencies, chokepoints and coordination mechanisms can shift the trajectory of the larger system?
This work treats AI as a geopolitical and industrial system. Tipping points can sit in infrastructure, standards, access, procurement, regulation, data or alliance structure rather than in the model layer.
NATOFORESIGHT → DIGITAL → CAPABILITY2025–26
What changes when you follow the same capability system across different environments?
Participation across NATO strategic foresight workshops, Capability Sprints and Allied foresight environments provided different views of the same system: future demand, digital/AI adoption, interoperability and capability transition.
The map is more useful than the event list, it shows where ideas move and where they stall between strategic intent, technical work, national constraints, industry and delivery.
Instead of treating events as isolated sources, the method compares their roles in one capability ecosystem and looks for recurring constraints, missing links and decision points.
Asset ledger
What the work is built on.
These are the assets behind the maps. Some are public. Some are working research infrastructure.
01 / Context
15 years in a Canadian Joint Warfare Centre environment
Long exposure to joint capability development, experimentation, interoperability, exercises, emerging technology and the practical constraints that shape defence adoption.
EVIDENCE TYPE → career record / delivered defence work / NATO participation
02 / Field research
Go where the ecosystem is forming
International fieldwork across AI, foresight, defence and emerging technology events. The trip is not the output; it is one stage of the research pipeline.
EVIDENCE TYPE → registrations / content / field notes / analysis
03 / Corpuses
Primary-source research collections
Captured Knowledge Corpus, fieldwork, research reports and structured source collections that can be re-analysed across events instead of disappearing into one conference summary.
EVIDENCE TYPE → captured content / document collections / structured signal logs
04 / Maps
Reusable system models
Actors, technologies, programs, institutions, flows, dependencies, interfaces, constraints and tipping points can be retained and updated rather than redrawn from zero each time.
EVIDENCE TYPE → ecosystem maps / dependency maps / capability maps / system diagrams
05 / Relationship intelligence
Who connects to what and why
Entity tracking, partnership mapping, stakeholder relationships, programs, institutions and the surrounding context needed to understand where a node sits in the larger system.
EVIDENCE TYPE → entity records / partner maps / event networks / program relationships
06 / Public record
A visible body of analysis
LinkedIn, Foresight Navigator writing, field notes and analyses create a time-stamped record of what was being watched, connected and argued before a demo.
EVIDENCE TYPE → LinkedIn / Foresight Navigator publication
07 / Method
Shifts → structure → leverage
Strategic foresight, horizon scanning, systems thinking, ecosystem mapping, second-order effects analysis, challenge/contradiction and leverage-point identification.
EVIDENCE TYPE → repeatable analytical sequence across different subject areas
08 / Research infrastructure
AI makes the corpus usable; it is not the claim
Structured memory, entity tracking, research repositories, search, agents and AI-assisted analysis help interrogate a much larger evidence base. The value remains the system interpretation.
EVIDENCE TYPE → internal research backplane / corpus workflows / entity & signal tracking
Field research
The map is built from more than desk research.
Selected locations and ecosystems represented in the recent research base.
Selected 2025–26 fieldwork
ReykjavíkNATO strategic foresight
SingaporeAI ecosystem
Dublinecosystem fieldwork
Virginia BeachNATO strategic foresight
SeoulAsia-Pacific AI
Dubaifuture / innovation ecosystem
IstanbulNATO digital / AI / interoperability
BerlinAllied foresight
Parisphysical AI / robotics
Method / visible
The Workflow, repeated.
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QuestionStart with the decision or system problem, not with a technology category.
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EvidenceCollect primary sources, field observations, documents, people, programs and signals.
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EntitiesIdentify the actors, technologies, institutions, infrastructure and resources.
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RelationshipsMap dependencies, flows, incentives, interfaces, constraints and reinforcing loops.
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LeverageLook for chokepoints, coordination points, timing, standards, access and underused assets.
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ImplicationReturn to the original question: what can the client now see that was difficult to see before?
Bring a question, or a scope of work.
We map the system around it.
Example input → “We have a defence AI capability. What system are we entering, and where could we matter?”
Questions this is suited to
MARKET / ECOSYSTEMWho matters in this capability area, and how are they connected?
TECHNOLOGY / FITWhere does this technology sit in the larger operational and institutional system?
GEOPOLITICS / DEPENDENCYWhich infrastructure, suppliers, policies or alliances create real leverage or vulnerability?
FORESIGHT / CHANGEWhat is moving in the system now that could alter the decision later?