Fathy GadDesign Automation · Enterprise AI

Fathy Gad Re-architecting how engineering is delivered.

Transforming multidisciplinary engineering through computational workflows, automation systems and governed enterprise AI — measured in delivery speed, protected margin and knowledge that stays with the business.

Fathy Gad is Associate Director and Design Technology & AI Lead at Jacobs in the Middle East. Across 18 years in structural engineering, BIM and design technology, he has architected enterprise automation platforms and AI agents for multidisciplinary design teams, on programmes including The Mukaab, NEOM and Al Maktoum International Airport.

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Leadership roles at
Jacobs Dar Al-Handasah AECOM

Programmes include The Mukaab · NEOM · Al Maktoum International Airport · Iconic Tower · Diriyah Gate

Strategic value

Four levers that move engineering economics.

Technology is not the outcome. Each pillar is defined by what it changes for the organisation — the return on effort, the speed of delivery and the exposure to risk.

01

Enterprise Design Automation

Converting repeat engineering effort — modelling, detailing, scheduling and documentation — into governed, reusable software assets.

Return
Each tool becomes cheaper every time it runs; capability compounds across projects instead of resetting.
Efficiency
Shorter design cycles: modelling, detailing and documentation produced by tools, not by hand.
Risk
Rule-based, auditable outputs replace error-prone manual repetition.

15–40%design cycle time reduction through custom automation

02

AI Integration & Knowledge Infrastructure

Retrieval-augmented assistants, MCP-connected agents and a shared data layer that put institutional knowledge and proven tools behind a plain-language interface.

Return
Expertise is retained by the business rather than lost with individuals.
Efficiency
Faster answers to RFIs, comments and code queries — with cited sources.
Risk
Mandatory human approval on every output; engineers remain the design authority.

2AI agents for design — BIM and structural

03

Computational Scalability

Parametric and integration engines that keep BIM, analysis and documentation in sync — so complexity scales without headcount scaling with it.

Return
Mega-project geometry generated and regenerated by script, not by re-modelling.
Efficiency
Integration between BIM and analysis in minutes, not weeks of re-modelling.
Risk
Fewer translation errors between modelling and analysis environments.
04

Strategic Technology Governance

The operating model around the technology: data standards, measurement, quality gates and a portfolio prioritised by the disciplines that use it.

Return
Every tool run is logged and converted into hours returned — value is reported, not asserted.
Efficiency
Proven solutions are reused across teams, disciplines and geographies.
Risk
Full audit trail of every run and change, on a uniform data schema.
AI for design

Two agents engineers can sign off.

AI agents that work inside the tools engineers already use. They read the model, call proven automation through MCP rather than improvising, and hand every change back to an engineer for approval.

BIM AI agent

An agent that understands the model — and runs the work.

Engineers inspect views, create elements and query references in plain language. The agent plans the steps and executes them through proven automation tools across the Autodesk and CSI ecosystems.

  1. AskA request in plain language, inside Revit
  2. PlanThe agent sequences the automation tools
  3. ApproveThe engineer reviews before any model change
  • Revit · Navisworks · CAD
  • SAP2000 · ETABS · SAFE
  • MCP connectors to proven tools
Design AI agent

A team of specialised agents on top of the structural model.

It reads the BIM and analysis models side by side, checks them against codes and company standards, and flags discrepancies before a reviewer does — with answers referenced to their source.

  1. ReadBIM and analysis models, plus the knowledge base
  2. CheckDesign review, quality and code-compliance agents
  3. ValidateThe engineer remains the design authority
  • Model understanding
  • Code compliance & QA
  • RAG query over standards
  • Learns from expert feedback
S

Uniform data schema

Automation chained to one indexed data structure — a library, not a scavenger hunt.

D

Centralised design data

Everything stored with project and model indexing, and every change tracked.

C

Correlation is key

When data speaks one language, AI stops guessing and starts connecting.

H

Human in the loop

Validation belongs to engineers and architects. Approval cannot be skipped.

Executive briefing

Case studies.

Three programmes, each set out the way a board would review them: the business problem, the architecture chosen and what changed for the organisation.

Case 01 · Middle East & India

Building an enterprise automation capability

Multidisciplinary: structure, architecture, MEP, ports & marine

Challenge

Fee pressure and fewer tenders, while skilled engineers spent a material share of their hours on modelling, scheduling and documentation.

  • Isolated scripts with no shared deployment, measurement or ownership
  • Know-how held by individuals rather than the organisation
  • No evidence base for technology investment decisions

Strategic architecture

A layered platform, deployed and governed like a product — not a collection of tools.

  • Add-ins inside the design applications teams already use
  • A sync layer that ships updates and collects usage telemetry
  • Central application and data services, with an AI layer on the same data
System architecture
  1. Design add-insInside Revit, Rhino and CSI tools
  2. Sync & telemetryUpdates out, usage in
  3. App & data servicesAPIs, logs, licensing
  4. AI layerAgents on shared data
  5. Value ledgerHours returned by project and discipline
Enterprise impact
Production systems used daily by multidisciplinary teams
Updates shipped centrally; usage measured on every run
Know-how captured in reusable tools, not individuals
Technology investment backed by usage evidence
Executive takeaway

Automation becomes a capability — not a cost — when it is deployed, measured and owned like a product.

Case 02 · The Mukaab · Al Maktoum International Airport · NEOM Vault

Computational delivery at mega-project scale

Saudi Arabia and the United Arab Emirates

Challenge

Landmark geometries where every design change ripples through hundreds of thousands of elements across BIM and analysis models.

  • Manual re-modelling could not keep pace with design iteration
  • Translation errors between modelling and analysis
  • Programme risk from late coordination

Strategic architecture

Scripted model generation, with BIM and structural analysis kept in sync from a single source of design rules.

  • Parametric engines generate structure directly from design rules
  • Live integration between BIM and analysis environments
  • A design change propagates in one run instead of a re-model
System architecture
  1. Design rulesGeometry, grids, constraints
  2. Parametric engineScripted generation
  3. BIM modelCoordinated and documented
  4. Analysis modelBuilt and loaded automatically
  5. Drawings & quantitiesRegenerated on change
Enterprise impact
Design changes propagated in one run, not a re-model
BIM and analysis models kept in sync
Fewer translation errors between environments
Coordination issues surfaced earlier in the programme
Executive takeaway

At this scale the advantage is the speed at which a design can change — not the speed at which it can be drawn.

Case 03 · Middle East

A governed enterprise AI layer for engineering

Design, BIM, structural analysis and resource planning

Challenge

Generic AI tools hallucinate on engineering data, and unmanaged adoption creates quality and liability exposure.

  • Project knowledge scattered across documents, models and email
  • Slow responses to RFIs, comments and code queries
  • No control over how AI outputs enter deliverables

Strategic architecture

Data first, then agents, then a human gate — AI that drives proven tools rather than improvising.

  • Uniform data schema and centralised, indexed design data
  • One shared data and agent layer for BIM and structural design agents
  • MCP connectors to existing automation, with mandatory engineer approval and a full audit trail
System architecture
  1. Uniform data schemaIndexed by project and model
  2. Shared data & agent layerRAG, MCP connectors
  3. AI agentsBIM agent · Design agent
  4. Engineer approvalMandatory, never skipped
  5. DeliverableTraceable to source
Enterprise impact
Every output reviewed and approved by an engineer
Answers traceable to source documents
Proven automation reused instead of improvised
Full audit trail of runs and changes
Executive takeaway

AI earns its place in engineering delivery through governance, not demonstrations.

Major projects

Landmark programmes.

Landmark work across Saudi Arabia, the UAE, Egypt and Azerbaijan — from parametric high-rise modelling to automated design delivery on mega-programmes.

The Mukaab, Riyadh, KSA
Riyadh, KSA

The Mukaab

A cube-shaped landmark at the heart of New Murabba — one of the largest built structures in the world.

Design Technology & Automation Lead
Iconic Tower, New Capital, Egypt
New Capital, Egypt

Iconic Tower

Africa's tallest tower, delivered with fully parametric high-rise modelling.

Computational Design · BIM Coordinator
NEOM Vault, NEOM, KSA
NEOM, KSA

NEOM Vault

Complex canyon-scale geometry with a scripted steel structure.

Design Technology & Automation Lead
Sindalah Island, Red Sea, KSA
Red Sea, KSA

Sindalah Island

Luxury island destination in the Red Sea — automated design and delivery workflows.

Design Technology & Automation Lead
Al Maktoum International Airport, Dubai, UAE
Dubai, UAE

Al Maktoum International Airport

One of the world's largest airport programmes — parametric roof and structure modelling.

Computational Design · BIM Coordinator
Capital Business District, New Capital, Egypt
New Capital, Egypt

Capital Business District

The central business district of Egypt's New Administrative Capital.

Computational Design · Lead BIM Specialist
Magdi Yacoub Hospital, Cairo, Egypt
Cairo, Egypt

Magdi Yacoub Hospital

Healthcare facility coordinated to LOD 350.

Computational Design · BIM Coordinator
Crescent Development, Baku, Azerbaijan
Baku, Azerbaijan

Crescent Development

Two towers and an offshore hotel on the Caspian waterfront.

Structural BIM Engineer
Insights

Opinions on the future of engineering delivery.

Short essays on generative infrastructure, the convergence of BIM and computation, and how AI should be governed in design — written from live programmes, not the lab.

25 October 2026 · 1 min read

Rules first. AI for judgment.

The fastest way to lose trust in AI is to use it for work that rules already do well. A practical split for engineering teams adopting AI.

Read
All insights
Focus themes
  • Generative infrastructure: from alignment to drawings in one runHow corridor engines generate bridges, viaducts and structures from a single alignment — and what that does to programme risk.
  • The convergence of BIM and computationWhy the model, the analysis and the code are becoming one system — and what that means for the engineering firm.
  • Governed AI in design deliveryAgents, MCP and the human gate: deploying AI in engineering without creating liability.
  • Measuring automationFrom anecdote to value ledger — how to prove the return on design technology to a board.
Stages & recognition
  • Autodesk University Middle East — SpeakerDubai 2018
  • Big5 Egypt — Speaker2022
  • Cairo University BIM Masters — Guest lecturer2017
  • AEC Tech Hackathon — 2nd placeNew York 2017
Whitepapers
  • The Automation Value Ledger: measuring the return on engineering automationIn preparation
  • Governed AI for Engineering Delivery: a reference architectureIn preparation
Credentials

Foundations.

Structural engineering by training; machine learning, BIM management and value methodology by certification.

Stanford Online

Machine LearningStanford Online

RICS

BIM Project ManagementRICS

SAVE International

VMA · AVSSAVE International

The American University in Cairo

Project ManagementAmerican University in Cairo

Education

  • BSc Structural Engineering, Benha University — ranked 8 of 868
  • Project Management Professional Program, AUC

Memberships

  • SAVE International
  • Society of Engineering UAE
  • Egyptian Engineers Syndicate

Languages

  • Arabic
  • English
  • German
Questions

Frequently asked.

The short answers — for event organisers, executive teams and anyone deciding whether to get in touch.

Who is Fathy Gad?

Fathy Gad is Associate Director and Design Technology & AI Lead at Jacobs in Dubai, UAE. A structural engineer by training, he has spent more than 18 years in BIM, computational design and design technology, and has architected enterprise automation platforms and AI agents for multidisciplinary design teams across the Middle East.

What does Fathy Gad specialise in?

Enterprise design automation, computational engineering and governed enterprise AI for architecture, engineering and construction (AEC) — including Revit and CSI automation, parametric modelling, retrieval-augmented AI assistants and MCP-connected agents with human approval on every output.

Which projects has he worked on?

Middle East mega-programmes including The Mukaab and NEOM in Saudi Arabia, Al Maktoum International Airport in Dubai, the Iconic Tower and Capital Business District in Egypt's New Administrative Capital, and Diriyah Gate in Riyadh.

Does Fathy Gad speak at conferences and events?

Yes. He speaks on generative infrastructure, the convergence of BIM and computation, governed AI in design delivery and measuring the return on automation. Past stages include Autodesk University Middle East and Big5 Egypt. He presents in English and Arabic.

Can I get a copy of his CV?

Yes — the CV is shared on request. Use the request form on this page and choose “CV request”; requests are reviewed personally.

How can I contact Fathy Gad?

Send a request through the form on this page, or connect on LinkedIn at linkedin.com/in/fathygad. He is based in Dubai and works across the Middle East and internationally.

Curriculum vitae

The full record.

Fathy Gad on site on a high-rise rooftop in Egypt's New Administrative Capital
From site engineer to design technology leadership — on site in Egypt's New Administrative Capital.

Fathy Gad — Curriculum Vitae

Experience from site engineering to design technology leadership, major projects, teaching, certifications and achievements.

  • PDF
  • Available on request
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Contact

Send a request.

For CV requests, speaking or event invitations, media and collaboration. Every request is reviewed personally, and a reply comes from Fathy directly.

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