applied intelligence | Strategies Rooted in the Prevailing REALITY!

Applying ai to the Global Political Economy and Leadership

When asked about applied intelligence, the straightforward answer is that applied intelligence (ai) is a methodology that applies critical and independent thinking to transform information into knowledge, fostering insight and rational strategic decision-making. Defined by a six-step (6ai) Socratic, human-centric process, ai doesn’t seek to make artificial intelligence competitive, surpassing, or replacing human intelligence. It takes an augmenting approach instead, amplifying human intelligence capacity, capabilities and purpose, for optimal strategy development and implementation!

This essay revolves around critical thinking and traditional strategy development models, in the context of the global political economy and leadership. Utilizing Canadian Prime Minister Mark Carney’s epic speech at Davos as a backdrop to arguing for a new paradigm in thinking and application.  

Why do we need applied intelligence? 

The ancient Greek philosopher Parmenides, born around the year 515 BCE, was one of the first to define reality. Reality represented ‘Truth’, that what is possible is only so in relation to what is real! That reality/truth can be tested through mathematics, because ‘What Is Not’ cannot be true.

We critically look at the fallacy of informal logic, which relies on in-formalities, inference, unstructured thinking, unscientific belief systems, biases, and pure mathematics like thinking systems models to formulate strategy.

While applied intelligence (ai) functions by a process of formal logic. Framing the core problem and processing ideas into logical propositions (“If A, then B”) for discovery. It defines the terms, assumptions, and required outputs at the outset, with clarity, similar to setting up a mathematical proof or outlining an experimental procedure.

In contrast, traditional strategy takes a less explicit approach, drawing immediately from vast patterns they’ve seen before — pre-trained — thesis becomes implicit or inferred rather than explicit and structured.

This is similar to what large language models (LLMs) do: trained on certain data, primarily using inference and pattern recognition. And if it doesn’t know the answer…it just makes stuff up, hallucination by design, paralleling conventional status quo strategy design.

When applied intelligence is formally applied to strategy, it serves as an effective tool for addressing abstract complexity through reality rather than through personal perceptions.

As a first principle, therefore, strategies must be grounded in objective truth; otherwise, strategy becomes a useless academic exercise.

Similar to LLMs, traditional often generate plausible-sounding but unverifiable or incorrect statements (i.e., hallucinations). And unlike LLMs, ai provides a traceable path where every conclusion is tied to its premises and supporting evidence. Its architectural structure and scale prevents it from relying on pattern matching or inference. Its a disciplined scientific process-methodology, that enforces checks at every step of the way.

Therefore, the cornerstone of applied intelligence rests on Formal Logic, structure and premise, never engaging in Informal Logic. It’s methodology stresses that nature is the source of all true knowledge, and that we must incorporate scientific systems based in reality to optimize our existence in nature.

Reality is not merely a backdrop to the universe, it’s the universe itself. Nature’s patterns…the human condition, its rhythms, cycles, and natural wisdom…a priori.

With a full adherence to reality we won’t stray into the abyss of theoretical ambiguity, classroom models. We can build strategy, instead, at the intersection of real complexity and simplicity.

The applied intelligence framework, therefore, aims to create highly useful functional strategies by rigorously defining “reality” first! As the bedrock of strategy development. Like in calculus, for example, ai utilizes a set of proofs, if you will, along the way to ensure staying on track, with adherence to certain first principles and practical constraints.

The Problem with Conventional Strategy

For years, strategy development has leaned heavily on top-down theories favoured by top business schools and academics, often amplified by major consulting firms such like McKinsey & Co., these big consultants often partner with and recruit academics to validate their approach.

This has led to academic ‘models’ dominating global political economy discourse with decision-making and leadership. Often feeling out of touch with reality and intellectually dishonest.

This is why Canadian Prime Minister Mark Carney’s speech so well received. Carney had the courage to say what many of us in the real world know to be objectively true. This top-down approach has creates fragility in global systems because, essentially, we are living a lie.

Top-down academically-led political economy strategy development poses several significant dangers, primarily stemming from an overreliance on academic theories and disconnected from reality. Often resulting in ineffective strategies.

Key dangers include:

• Lack of Local Context and Reality-based Decisions top-down expert or consultant driven models are simply theoretical and dishonest themselves.

  
  

• Top-down stifles critical thinking, creativity and innovation. The best and most useful practical ideas usually come from those closest to the work.

Applying applied intelligence thinking helps leaders identify the gaps in problem-solving, ai brings clarity and clarity is intelligence. In the realm of political economy, with global actors, traditional models, for far too long have come to rely on the assumption of the ‘rational actor.’

The Rational Actor Model (RAM) is a decision-making framework assuming individuals or states act logically to maximize benefits and minimize costs, based on stable preferences and available information. It is a foundational concept in economics, political science, and foreign policy, treating actors as unified, rational agents seeking the most efficient, goal-oriented outcomes.

However, RAM is a fragile and intellectually dishonest theory which does not account for critical factors in the strategy equation. It doesn’t account for reality: intangible drivers, i.e., political narratives or domestic priorities often get overlooked.

Traditional strategy is built on incomplete definitions of reality — overlooking cognitive, cultural, or ideological dimensions and risk being blindsided by actions from actors that defy rational actor logic.

These incomplete strategies often fail when they assume reality is defined solely by tangible factors (e.g., economic data, historical trade patterns), while ignoring intangible forces like political identity, ideology, or societal narratives. So applied intelligence fully accounts for reality: the environment, domain or playing field, not just trade data and related, but also the political symbolism…nationalism.

In the global political economy, strategy approaches must entail three important components because failure occurs when they ignore the full spectrum of reality.

1. Precise Context: Traditional trade strategies’ reliance on mutual benefit vs. the U.S. tariff case, as an example of disconnect or misalignment.

   
   

2. Core Problem: A gap forms between strategy and reality when cognitive and ideological dimensions are unaccounted for.

   
   

3. Stakes: Systemic misalignment leading to ineffective policies, adversarial surprises, or wasted resources.

Traditional trade strategies have been primarily driven by informal logic and a lot of emotion — assumes rational decisioning (e.g., “free trade reduces costs for all”). Yet recent U.S. Trump tariffs exposes the fragility of this thinking, revealing a disconnect between economic models and the broader reality of political identity, sovereignty narratives, and domestic priorities.

Strategies focused solely on tangible factors or historical patterns overlook critical intangible variables of ideology, cultural values, and delusional leadership.

The applied intelligence methodology, therefore, addresses this fundamental problem, by systematically mapping the variables — all material moving parts — physical (trade volumes, supply chains) and non-physical (political symbolism, public sentiment).

Fortifying strategy by utilizing reality as the foundation for sound decision-making. Ensuring that strategy development account for both principles (e.g., free trade ideals) and pragmatism (e.g., domestic manufacturing revival as a political imperative).

The stakes for ignoring the reality gap include reactive policy making (e.g., tariffs triggering trade wars); Wasted resources on solutions misaligned with on-the-ground realities; Erosion of trust in institutions perceived as out of touch and escalation instead of progress.

The Einstein Relativity Parallel

Einstein’s theory of relativity revolutionized physics by proving that reality isn’t limited to what’s directly observable (e.g., gravity isn’t just a “force” but a curvature of spacetime). Similarly, applied intelligence rejects the notion that strategy can rely solely on visible, quantifiable factors (e.g., tariffs, GDP).

Cognitive science and neuroscience inform us that humans don’t perceive things as they truly are; instead, they are constantly shaping their perceptions of reality. Adjusting belief systems around the world as they see it, microsecond by microsecond. Consider that the value in applied intelligence is to ensure that our cognitive functions are underlined by our intelligence which is intrinsic to our ability to deal with what is real in the universe.

Neuroscientist Anil Seth explains in his book, Being You: A New Science of Consciousness. He states that intelligence “takes crucial contributions from philosophy, biology, cognitive science, neuroscience, and artificial intelligence, developing a new understanding of consciousness and of what it means to be self.”

Therefore, the role of applied intelligence is to assists strategy by offering a disciplined framework to incorporate all the variables, tangible and non-tangible, for realistic strategy design and execution.

The shared Principles between relativity and applied intelligence:

• Holistic Reality: Relativity integrates mass, energy, time, and space; applied intelligence integrates tangible and intangible variables (e.g., trade data + political identity).

  
  

• Rigorous Proof: Einstein used mathematics to reveal hidden relationships; applied intelligence finds the hidden symmetries that are non-obvious, latent, or “shy” physical or mathematical structures that are not immediately apparent but underpin systems (e.g., sovereignty narratives).

  
  

• Practical Outcomes: Relativity enabled GPS technology by accounting for time dilation; applied intelligence enables resilient strategies by accounting for ideological shifts, relative to time and place.

This humble analogy with Einstein’s theory of relativity is a redefining of how applied intelligence is refining how we measure reality and build strategies from it. Einstein’s theory of relativity didn’t merely add new equations to physics; it fundamentally redefined how we measure and validate reality. This is a central tenet of applied intelligence.

Before relativity, time and space were seen as fixed, independent dimensions. Einstein proved they were interconnected, relative to the observer’s frame of reference, and influenced by mass and energy. This shift allowed humanity to explain phenomena (e.g., Mercury’s orbit) that Newtonian physics couldn’t explain — applied intelligence is a paradigm shift in explaining the optimal way to engage reality — objectively an intellectually honest.

1. Redefining Measurement:

• Einstein: Introduced spacetime as a measurable fabric, where gravity isn’t a “force” but curvature.

• applied intelligence: Treats ideology, cultural narratives, and political identity as measurable dimensions of reality, not vague “external factors.”

2. Observer Dependence:

• Einstein: Showed that measurements (e.g., time) depend on the observer’s perspective.

• applied intelligence: Acknowledges that “rationality” depends on a nation’s or a leader’s worldview (e.g., tariffs as economic policy vs. sovereignty symbol).

3. Validation Through Prediction:

• Einstein: Relativity was proven by predicting light bending around the sun.

• applied intelligence: Validates its reality-model by predicting actions that defy traditional logic (e.g., tariffs persisting despite economic harm).

4. Unifying Frameworks:

• Einstein: Unified mass, energy, space, and time into a single theory.

• applied intelligence: Unifies tangible data (trade deficits) and intangibles (voter sentiment) into a single strategic reality.

Step 1: Rigorous Fact-Gathering

• Assumption: “The tariffs are driven by economic logic.”

• Objective Truth: Dig deeper into the counterpart’s incentives.

Is the leader using tariffs to rally a political base (e.g., portraying toughness)? Are they diverting attention from domestic crises? Is the goal to force renegotiation of broader agreements, not just trade?

Outcome: You discover the tariffs are primarily a symbolic tool to reinforce the leader’s “anti-establishment” image. Economic costs are secondary to them.

Step 2: Dynamic Frameworks

• Traditional Approach: Model economic impacts (e.g., GDP loss, job numbers).

• Dynamic Approach: Build scenarios around the leader’s true incentives:

• Scenario A: Leader prioritizes media dominance → Respond with private concessions + public neutrality to avoid fueling their narrative.

• Scenario B: Leader seeks short-term “wins” for re-election → Offer face-saving compromises timed to their electoral calendar.

Step 3: Stress-Testing Beliefs

• Internal Belief: “Tariffs are always about economics.”

• Stress Test: What evidence contradicts this?

The counterpart’s public speeches focus on “winning” rather than economic data. Their past actions show tolerance for economic pain if it boosts political capital.

• Pivot: Shift strategy from “economic retaliation” to “narrative disruption” (e.g., multilateral coalitions that dilute their “lonely hero” narrative).

  
  

• Key Insight: The initial strategy failed because it treated the counterpart as a rational actor. By aligning with the objective truth of their incentives (symbolic/political), Country X could design targeted leverage points for optimal strategic effectiveness.

So effective strategy development requires a multifaceted analysis of all variables influencing an actor’s decisions — not just the visible or ‘rational’ ones, but the hidden incentives, ideological drivers, and even irrational biases that shape behaviour.

For instance, when a leader imposes tariffs, a surface-level economic response often fails because it ignores the political theatre motivating their actions. By rigorously mapping both the stated reasons (“unfair trade”) and unspoken incentives (e.g., rallying a base, projecting strength), strategies can pivot from generic retaliation to targeted interventions — like undermining their narrative rather than escalating economically.

Clearly, in the case of Trump tariffs, appeasement does not work. And it didn’t work against Hitler either, but it seems like European leaders have not taken in or learned from their own history.

Appeasement was a 1930s foreign policy, primarily led by British Prime Minister Neville Chamberlain, that granted concessions to Adolf Hitler to avoid another devastating war. However, this policy failed to stop Hitler, who annexed three key territories — Austria, the Sudetenland, and the rest of Czechoslovakia — before invading Poland and triggering World War II in September 1939.

Hitler was not a rational actor; he was a delusional, paranoid psychopath on drugs. With Trump, European leaders have failed, in critical moments in history, to deploy the right strategy against Trump. Failing to go beyond the RAM to all the real contributing factors involved in strategic decisioning!

Strategy Is Agnostic

Effective corporate strategy demands a holistic examination of all variables shaping market dynamics and organizational behaviour — not just financial metrics or competitor moves, but cultural shifts, employee sentiment, and unspoken customer biases.

This is why leaders must always take a bottom-up approach instead of a top-down one. Top-down academically-led strategy development poses several significant dangers. The bottom-up applied intelligence process, on the other hand, is empirically driven. It empowers and leverages wisdom

• If company X launches a premium product might focus on pricing and features, only to fail if it overlooks cultural trends (e.g., rising demand for sustainability) or internal resistance from teams wedded to legacy processes.

  
  

• By analyzing both quantitative data (sales forecasts) and qualitative drivers (brand perception, workforce agility), strategies can shift from generic “innovation” to targeted actions — like aligning product narratives with customer values or restructuring incentives to overcome internal inertia.

This grounds decisions in the full spectrum of reality! Ensuring strategies adapt to how markets truly evolve, not how leadership assumes or wishes they should.

Risk: Traditional models often treat risk as a checkpoint — e.g., “What if sales drop 10%?” — applied Intelligence systematically maps how variables interact to create vulnerabilities.

Therefore, risk management is intrinsic to applied intelligence, they are coupled and interact by forming an integrated, proactive process known as ai-Risk Management (aRM), where potential risks are analyzed simultaneously with the strategy build.

Shaping, strengthen, and validating the long-term objectives of the strategy, rather than being a separate and defensive from it. aRM acts as a strategic partner that identifies, assesses, and treats risks constructively, as both threats and opportunities — ensuring optimal decisioning in uncertain environments.

For instance, a tech firm entering a new market might analyze not just regulatory hurdles and competitors, but also latent risks like shifting consumer distrust of data privacy or a partner government’s unspoken agenda to favour domestic players.

By stress-testing strategies against these interconnected variables (e.g., “How would a populist backlash against foreign tech impact our supply chain?”), risks become lenses to refine decisions, not roadblocks to avoid.

This transforms risk from a reactive cost into a proactive compass, ensuring strategies are resilient because they’ve been built with uncertainty, not despite it.

The applied intelligence — actionable phases:

Phase 1: Define the Decisioning Universe

• Objective: Map all variables influencing the actor/system you’re engaging (e.g., a political leader, competitor, market).

• Tool: “Influence Web” — Visualize interconnected factors (e.g., for tariffs: public opinion, leader’s re-election calculus, rival factions in their administration, economic dependencies).

• Example: If a leader’s tariff decision is driven by 70% political theatre and 30% economics, your web highlights narrative control as a central node, not trade deficits.

Phase 2: Stress-Test Assumptions

• Objective: Identify and pressure-test hidden beliefs (e.g., “This leader responds rationally to economic pain”).

• Tool: “Red Team Roulette” — Assign teams to defend opposing assumptions (e.g., “What if escalation strengthens their domestic standing?”).

• Outcome: Reveals blind spots, like underestimating the symbolic value of “toughness” to the leader’s base.

Phase 3: Dynamic Scenario Building

• Objective: Create strategies for multiple “truths,” not just the most likely outcome.

• Tool: “Fault Line Scenarios” — Model strategies against:

Baseline Truth (e.g., leader prioritizes political survival). Wild Truth (e.g., leader seeks intentional chaos to destabilize rivals). Silent Truth (e.g., internal factions are pushing tariffs to weaken the leader).

Phase 4: Embedded Risk Mitigation

• Objective: Turn risks into strategy modifiers, not afterthoughts.

• Tool: “Pre-Mortem Analysis” — Assume your strategy failed. Work backward to diagnose why (e.g., “We misread the leader’s need for public conflict”) and build safeguards (e.g., “Include narrative countermeasures in every tactical move”).

Phase 5: Iterative Reality Checks

• Objective: Continuously validate against real-world signals.

• Tool: “Truth Anchors” — Identify 3–5 observable metrics that confirm or contradict your core assumptions (e.g., tracking the leader’s media mentions vs. economic data after tariff hikes).

Putting It All Together: Going back to the tariff example, this process would shift the response from retaliatory tariffs (which assume economic rationality) to a mix of private sector alliances (to reduce the counterpart’s local job-creation claims) and controlled, public de-escalation (denying them the “villain” narrative they feed on).

A strategy divorced from objective truth is like navigating a storm with a faulty compass: it might feel fine but it will falter eventually, when incomplete assumptions collide with the messy, unpredictable forces that govern real outcomes.

Canadian Prime Minister Mark Carney’s applied intelligence based strategy speech

Canadian Prime Minister Mark Carney’s speech at Davos has been hailed as one of the most consequential and effective speeches by a political leader on the global stage, since the dawn of the 21st century!

The layout for a new world order was effective because it was based firmly in intellectual honesty — putting the objective truths out there and doing so with the courage to say what others are thinking. This is the essence of serious leadership for serious times.

Carney was dropping-bars, truth bomb, naming the reality of the moment. Unlike other European leaders kowtowing to Trump — showing weakness by pretending that the “rules-based international order” still exists.

Nations must “calibrate (bilateral) relationships whose depth reflects our values,” and we must be “pragmatic” in building multilateral groupings with “variable geometry” to pursue essential shared objectives: building a cooperative grouping and alliances with members of the Trans-Pacific Partnership, the EU, and Canada, and more, to ensure the World Trade Organization can function for the common good.

The latter is effectively building an applied intelligence playbook for dealing with irrational global actors/bullies/delusional authoritarians.

This is Pragmatic Realism — intrinsic to the applied intelligence playbook.

The world is in a very different place where a hegemonic powers can utilize global trade, commerce, money, and supply chains as tools to be leveraged in its own self-interest. Middle-powers like Canada may not be able to alter this reality, but applied intelligence can help them built strategies, to not only survive but to thrive in such environments!

Countries must avoid “subordination” and intimidation because bad actors feed on that. And appeasement in hopes of avoiding escalation is a failing strategy. It often has the opposite outcome…emboldening delusional, predatory, authoritarian leaders — escalation — conflicts and wars.

Carney is applying applied intelligence thinking and acting, strategically, within the constraints of reality. Unlike European leaders who are burying their collective heads in the sand — running away from the fire.

“Hegemons cannot continue to monetize their relationships,” telling leaders to be realistic, end the charade about the world’s rules-based order — it is “not coming back,” and “let’s be honest…Nostalgia is not a strategy.”

“Going along to get along” is not a strategy, he urged like-minded countries, the “middle-powers,” to band together to form a sustainable force for international cooperation in a redefined “rules-based order” of the willing. This, therefore, is an applied intelligence strategy, based firmly in reality!

Carney backs up his speech with his actions, earlier that week he cut a deal with China. While Americans continue obsess over culture wars, ICE, a modern day Gestapo hunting down immigrants; and kidnapping foreign leaders for their oil, China was taking its place as the world’s true economic superpower.

Carney, has observed the evolving new reality, and shifted to China without hesitation to created new trade and commerce relationships. Signing a landmark agreement with China: China will slash tariffs on Canadian canola seed from 85% to 15%. They’ll also drop tariffs on Canadian canola meal, lobsters, crabs, and peas.

In return, Canada will allow 49,000 Chinese-made electric vehicles into our market at a 6.1% tariff, down from the current 100%. It’s expected that within 5 years, the import price of EV’s from China will be less than $35,000. The current average cost of a new EV car in Canada is just under $67,000.

Collaboration with China also gives Canada access to advanced technology in areas where they excel — take technology, clean energy, and related industries — high-speed rail — Canada is planning its own HSR system and China is a global leader in this space.

China is already the second-largest single-country trading partner to Canada and this new deal, Carney says, “…will help unlock nearly $3 billion in export orders for Canadian workers and businesses as they realize the full potential of the massive Chinese market of 1.4 billion people.” Also setting ambitious goals, like increasing exports to China by 50% by 2030.

Reality: China can’t be ignored; it’s the world’s second-largest economy, contributing one-third of global growth, so in a globalized world, ignoring a country like China threatens your own wealth and prosperity.

The geopolitical shift is occurring, the ground is moving below our feet, intelligence tells you that you must adapt to the new world order and build applied intelligence strategies thrive in the 21st century.