PhD  ·  Narxoz Business School, Almaty

Agency or abdication:
AI, empowerment, and
the futures we are choosing.

I work on one organizing question: when AI is adopted, who gains agency and who loses it? The research spans education, organizational management, labor markets, knowledge production, and strategic foresight — unified by a single analytical commitment: distinguishing genuine empowerment from dependency dressed up as adoption.

I am based at Narxoz Business School in Almaty, where I lead research on AI governance, institutional futures, and the application of these frameworks in a Central Asian context. I publish through working papers — a deliberate choice that reflects one of my own central arguments: that conventional academic publishing moves too slowly for the world it is trying to describe.

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Working papers 2025–26
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Ewan Simpson
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Research

Working papers published open access on Zenodo and SSRN. Where multiple versions exist, the latest is listed.

Foundational Frameworks
2026  ·  Framework

The AI Matrix as Diagnostic: Access, Agency, and Adoption

The foundational framework separating access to AI tools from agency in their use. Broad access without agency produces passive dependency — high-looking outputs, weakened judgment. Defines the target condition for institutions and societies: high access and high agency, not merely adoption.

Zenodo →
2026  ·  Framework

Decomposing the Capability Overhang: Access, Agency, and the Geography of AI Adoption

Extends the AI Matrix framework into a geographic and organizational analysis of why AI capability accumulates unevenly. The capability overhang — the gap between what AI can do and what organizations actually do with it — is explained by the access-agency distinction, not by technology availability alone.

Zenodo → Key findings →
2026  ·  Governance

Managing AI Like It Matters: The Artificial Intelligence Operating System (AI-OS)

AI-OS is a governance-centered architecture treating AI adoption as an operating model question rather than a tool rollout. Works at the task level — assigning each task a permitted mode of use based on stakes, ambiguity, reversibility, and sensitivity — making the human-AI boundary visible, auditable, and adjustable by evidence.

Zenodo →
2026  ·  Assessment

Beyond Detection: FARABI and the Assessment Credibility Shock in Higher Education

FARABI (Framework for AI-Resilient Assessment and Balanced Integrity) reframes assessment integrity as an evidence design problem. The primary problem is not misconduct but validity: if AI can satisfy an assessment without the student demonstrating the targeted reasoning, the assessment was already weak evidence. FARABI provides a portfolio-level triage method for restoring defensible inference.

Zenodo →
2026  ·  Knowledge Work

Orchestrated Intelligence: Rethinking Knowledge Work in the Age of AI

The defining capacity of an AI-era leader is the ability to design, sequence, and stage-manage complex human-AI workflows. Orchestrated intelligence is a teachable, assessable competence — decomposing problems, running accountable iteration loops, and making reasoning visible.

Zenodo →
2026  ·  Epistemology

Flow Acceleration and the IHACC Model: Human-AI Co-Creation in Epistemology

IHACC (Iterative Human-AI Co-Creation) argues that AI changes the structure of knowledge production, not just its speed. Acceleration without proof standards produces noise. Human judgment, verification, and epistemic standards must remain explicit throughout AI-assisted inquiry.

Zenodo →
2025  ·  Credentialing

The AI Passport: Towards a New Conceptual Framework for Global Skills Certification

Proposes a portable, renewable credential structure linked to program-level proof standards. Designed to make a degree's capability claims legible to employers and to help people navigate AI-driven labor market transitions rather than being stranded by them.

Zenodo →
2026  ·  Research Methods

Too Slow for the AI Age? Building a Dynamic Research Continuum

Academic publishing is structurally misaligned with the pace of AI change. The Dynamic Research Continuum proposes a versioned, continuously updated pipeline that maintains quality standards while closing the gap between frontier developments and peer-reviewed knowledge.

Zenodo →
Education, Credentials & Institutional Futures
2026  ·  Manifesto

Business School 2030: A Manifesto for the AI Operating Environment

Business schools must redesign themselves as capability-and-proof institutions. Integrates the AI Matrix, FARABI, AI-OS, Orchestrated Intelligence, the AI Passport, and the Dynamic Research Continuum into a single operating model for schools that need to remain credible when AI assistance is everywhere.

Zenodo → Op-ed version →
2026  ·  Manifesto

HEI 2030: A Manifesto for the Higher Education AI Operating Environment

Extends the business school manifesto to higher education institutions more broadly — addressing the structural challenges facing universities as AI weakens the evidentiary link between student outputs and the learning claims that underwrite degrees.

Zenodo →
2026  ·  Scenario Planning  ·  Co-authored with A. Wachtel

The Proof and Trust Shock: Generative AI and the Future of Mass Higher Education

Maps six futures for mass higher education — from utopia through muddling along to legitimacy crisis. Current evidence places the highest probability on the more disruptive scenarios. The system faces four interacting walls: a proof wall, a jobs wall, a cost wall, and a legitimacy wall that reinforce each other.

Zenodo (v1.2) →
2026  ·  Evidence Synthesis

General-Purpose Versus Learning-Oriented AI: A Structured Cross-Source Synthesis

A systematic synthesis of evidence on AI and learning, distinguishing between general-purpose AI tools and those specifically designed to support learning. Examines what the evidence actually supports about AI's role in education — and where the inferential gaps remain.

Zenodo → Key findings →
2026  ·  Creativity

A Generation at Risk? Creativity, PISA 2022, and the Demands of an AI Economy

Uses PISA 2022 creative thinking results as a warning about capability readiness for an AI-saturated world. Creativity must be treated as a measurable, teachable competence — not rhetorical aspiration — built into curriculum, assessment, and proof routines.

Zenodo → Research agenda →
Labor Markets & the Jobs Wall
2026  ·  Research Agenda

Is AI Part of the Recruitment Recession? A Research Agenda

The labor market is quietly closing off the entry-level routes that have historically justified mass higher education. The "Jobs Wall" captures the risk that AI tightens junior hiring pathways even while headline employment figures remain stable.

Zenodo →
2026  ·  Data Analysis

The Proof and Trust Shock: What the BLS 2024–34 Projections Suggest About the Jobs Wall

Using US Bureau of Labor Statistics projections, provides empirical grounding for the Jobs Wall concept — showing how graduate employment routes are narrowing in ways that standard labor market analysis tends to understate.

Zenodo →
2026  ·  Commentary

Beyond Adoption: Intensity and Integration as the Missing Link in Firm-Level AI Impact

A response to Yotzov et al.'s firm-level AI impact research, arguing that adoption rates are the wrong unit of analysis. What matters is intensity of use and depth of integration — the same distinction between access and agency that runs through the broader research agenda.

Zenodo →
Foresight, Strategy & Geopolitics
2026  ·  Foresight Framework

Using AI in Scenario Planning: Letting It Rip or Doing the Right Thing?

Introduces the Grey Swan / Archimedes framework for governed, AI-assisted strategic foresight. A grey swan is a plausible, consequential disruption with visible signposts already present in current data — one that goes unaddressed not because it is unknowable but because it is uncomfortable. Results are currently sobering.

Zenodo → Live intelligence brief →
2026  ·  Geopolitics

The AI Triad: Power, Infrastructure, and Agency in US-EU-China Strategy

Applies the access-agency framework to the geopolitics of AI — examining how the three major blocs are positioning on infrastructure, governance, and the distribution of AI-derived agency across their populations and institutions. Updated in a subsequent paper.

Zenodo → Updated version →
Evidence, Commentary & Strategic Reading
2026  ·  Commentary

Speed Is Not the Whole Story: Anthropic’s Claude Study and Orchestrated Intelligence

A close reading of Anthropic's research on Claude's impact on knowledge work. Speed gains are real but secondary. What the data supports is the importance of orchestration — structured human-AI workflows — over unmanaged acceleration.

Zenodo (updated) →
2026  ·  Commentary

The LLM Usage Gap: Evidence from Anthropic, Microsoft, and OpenAI

Examines the gap between reported AI adoption rates and actual intensity of use. Widespread nominal adoption coexists with shallow, unmanaged use in most organizations — supporting the access-agency distinction at organizational scale.

Zenodo →
2026  ·  Strategic Toolkit

Strategic Toolkits: Reading the Major AI Usage Reports

Practical frameworks for cutting through vendor framing in the Microsoft Copilot and OpenAI enterprise usage reports — identifying what the data actually supports and where the inferential gaps are.

Microsoft Copilot toolkit → OpenAI toolkit →
Grey Swan / Archimedes

A governed, AI-assisted foresight framework that converts public data into auditable probabilities for two global scenarios and four outcomes. Named after Taleb’s concept: a grey swan is consequential and visible in today’s data, but uncomfortable enough to ignore. This model refuses to look away. The framework runs on a six-month cadence against a live public evidence base. Results are updated each run. Results are currently sobering.

Spring 2026  ·  Intelligence Brief
The Grey Swan Scenario Framework: The Spring 2026 state of play
Trade fragmentation and health surveillance degradation have driven deterioration since the October 2025 baseline. A third risk — economic stress — is approaching threshold under the revised v11.9 architecture. Two flags are active. The Wealth-Diffusion Gate remains closed.
Read the brief →
Working Paper  ·  WP11
The framework: methodology and first-run results
Full documentation of the Grey Swan / Archimedes foresight model — the evidence tier architecture, the six Archimedes Levers, the two scenarios, the four outcomes, and the governance rules that keep the model honest. Published open access on Zenodo.
Zenodo →
The Virtuous City

A parallel project: recovering the civic framework of Abu Nasr al-Farabi (c. 872–950), philosopher from what is now Kazakhstan, and asking what it still demands of modern cities. Al-Farabi built the most systematic account of civic purpose in the medieval world. His questions — what is a city for, how does governance fail, how does institutional wisdom survive its founders — are more rigorous than most current answers. This work sits alongside the AI research agenda. The name FARABI is not a coincidence.

Essay
The Second Teacher
What a tenth-century philosopher from Kazakhstan knew about cities that we keep forgetting. A public essay on Al-Farabi’s civic framework and the tradition it represents.
Read →
Self-assessment
The Virtuous City Scorecard
A governance diagnostic based on Al-Farabi’s framework. Eighteen statements across six dimensions of civic governance, with a diagnostic drawn from his failure typology.
Open scorecard →

Contact

Research enquiries, collaboration, speaking, and executive education.

I am open to conversations about research collaboration, speaking engagements, consultancy on AI governance and assessment design, and executive education for organisations navigating the shift to AI-mediated work. Based in Almaty; working globally.