Abdul Rahim Hirani
Founder and Research Author
AI Logic Engineering
Connect on LinkedIn§ 01 — The Work
Founder and Research Author
Over the past two years, he has authored and researched the body of work set out below — developing AI Logic Engineering from an initial question into a structured, published methodology.
Abdul Rahim Hirani is the founder and research author of AI Logic Engineering, a structured methodology for Human Decision Making in the Age of Artificial Intelligence.
His work focuses on one central question:
How should humans govern Artificial Intelligence rather than simply use it?
Drawing upon more than two decades of experience in financial leadership, governance, strategic planning, business analysis, project control, and executive decision support, he recognised that the greatest challenge presented by Artificial Intelligence is not technological capability but human judgement.
While organisations increasingly invest in AI technologies, many continue to struggle with governance, accountability, structured decision-making, verification, and consistent business outcomes. These observations led to an independent programme of research examining how humans should collaborate with AI while retaining responsibility for every significant decision.
This research culminated in the development of AI Logic Engineering, an emerging academic discipline that places human reasoning, structured logic, governance, verification, and accountability at the centre of Human–AI collaboration.
§ 02 — Published Work
His published work
His published work currently includes:
The Human Decision Framework
The AI Logic Engineering Framework
AI Logic Engineering Principles
AI Logic Centre
AI Boundary Framework
AI Governance Framework
AI Verification Framework
AI Quality Assurance Framework
In addition to developing these frameworks, Abdul Rahim Hirani designed and validated multiple AI-driven projects that served as practical research environments for refining the methodology before publication.
The long-term objective of AI Logic Engineering is to establish a recognised body of knowledge that supports education, professional practice, enterprise governance, and future academic research into Human–AI collaboration.
§ 03 — Areas of Research
Areas of Research
§ 04 — Current Publications
Current Publications
Edition 2026
AI Logic Engineering
Foundation Course
Human Decision Framework
AI Logic Engineering Framework
Research Papers
Enterprise AI Research
§ 05 — Current Research
Current Research
Current research focuses on:
Enterprise adoption of Artificial Intelligence
Human decision-making in AI-assisted environments
Governance frameworks for enterprise AI
AI performance measurement and standardisation
Structured methodologies for AI implementation
Continuous improvement of Human–AI collaboration models
§ 06 — Long-Term Vision
Long-Term Vision
The objective of this work is to establish AI Logic Engineering as an openly published methodology that invites academic discussion, professional adoption, practical validation, and continual refinement through future editions.
§ Professional Background
Professional background & credentials
Two decades of financial leadership, governance, and strategic decision support inform the discipline's emphasis on structured human judgement, accountability, and verification. For the past two years, he has been authoring and researching AI Logic Engineering — developing the methodology, frameworks, and principles that now define the discipline.
Financial Controller
EDGE (Arch) · Dubai, UAE · 2017 – Present
Leads financial and management reporting and strategic decision-making for an award-winning architecture and lead-consultancy firm. Oversees project proposals, profitability analysis, and business-value-model forecasting across a portfolio exceeding AED 400 million, working with developers including Emaar, Aldar, Damac, Bloom, PIF, DP, and KSPP.
Financial Analyst
ENGIE · Abu Dhabi · 2014 – 2017
Steered end-to-end financial operations, budgeting, costing, and corporate compliance; evaluated business proposals, risk management, and commercial relationships to improve profitability across every decision-making process.
Financial Services Consultant
The City Pavilion · London, UK · 2009 – 2012
Advised top management on strategic business plans, monitored financial performance against internal and external factors, and reported to the CEO and GM on the financial condition of the company.
Financial Accounting Manager
ITM O&M — Umm Al Nar Power & Water · Abu Dhabi · 2009 – 2010
Prepared consolidated IFRS financial statements, managed group book closure, coordinated external and internal audit, and assessed the financial feasibility of projects for the CFO.
Accountant
BAUER Spezialtiefbau GmbH · Abu Dhabi · 2008 – 2009
Handled consolidation with the parent entity, on-site cost and revenue appraisal, budgeting, forecast, and variance analysis, with negotiation across customers, suppliers, and banks.
Certification
ACCA Certificate (2010 – 2013)
Education
B.Com, Karachi University — 1st Division
Experience
20+ years in finance & business planning
Membership
Toastmasters International (2017 – Present)
Volunteering
Aga Khan University Hospital
Volunteering
Community Development Authority — Environment
§ Perspective
Perspective
Abdul Rahim Hirani is not a machine learning researcher or software engineer.
His professional background is in financial management, business analysis, project control, governance, and organisational decision support, with more than two decades of experience helping organisations make structured business decisions.
Over the past two years, he has applied Artificial Intelligence extensively to the design and development of practical projects while simultaneously researching the relationship between human judgement and AI-assisted decision-making.
Through this work, he observed that most discussions focused on improving Artificial Intelligence itself, while comparatively little attention was given to improving how humans decide to use Artificial Intelligence.
This observation became the foundation of AI Logic Engineering.
Quote
“AI Logic Engineering is not a discipline about making Artificial Intelligence think more like humans. It is a discipline about helping humans think more effectively when working with Artificial Intelligence.”