건축 설계 및 도시 계획 분야 생성형 AI 시장 : 점유율 분석, 업계 동향과 통계, 성장 예측(2026-2031년)

According to Mordor Intelligence, the generative AI in architectural design and urban planning market size is expected to increase from USD 2.84 billion in 2025 to USD 3.58 billion in 2026 and reach USD 12.52 billion by 2031, growing at a CAGR of 28.45% over 2026-2031.

This report is Segmented by Offering (Platforms and Solutions, and Services), Deployment (Cloud-Based, On-Premises, Hybrid, and Cloud), Application (Architectural Design, and Urban Planning), End-User (Architectural and Design Firms, Urban Planning and Infrastructure Consulting Firms, and More), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Global Generative AI In Architectural Design and Urban Planning Market Trends and Insights

Growing Demand for Rapid Prototyping and Real-Time Computational Design

The move from sequential design work to concurrent iteration remained one of the strongest demand drivers in the generative AI in architectural design and urban planning market. Autodesk Research stated in June 2026 that Neural CAD was built to reason directly over precise 2D and 3D geometry, which moved AI closer to production-grade design tasks instead of visual experimentation alone. Research published in Automation in Construction in 2025 found that machine learning pipelines now extend across floor plan generation, performance simulation, and construction detailing, which showed that AI utility was spreading across the full design continuum. Snaptrude also positioned its 2026 release around LOD 300 and LOD 350 delivery from early massing through coordinated AI workflows, which supported faster movement from concept work to coordinated design output. As iteration cycles shortened, the cost advantage long held by large studios started to narrow because smaller practices could test more options with fewer manual hours. That shift mattered because early concept work often shaped client retention, pricing power, and downstream subscription value across the generative AI in architectural design and urban planning market.

Increasing Complexity of Urban Planning Projects and Infrastructure Challenges

Urban planning authorities faced rising pressure to speed housing delivery while managing land use constraints, infrastructure gaps, and climate-related risk, which increased the relevance of the generative AI in architectural design and urban planning market. The UK government announced in June 2026 that its Augmented Planning Decisions prototype aimed to reduce the time for processing householder planning applications from 8 weeks to 4 weeks across local authorities in England. Germany's SPARK initiative was released as open source in April 2026 to support complex planning and approval procedures while keeping final decisions in the hands of qualified staff, demonstrating that public agencies were treating AI as an operational tool rather than a trial technology. These programs also had broader commercial value because they created procurement templates that other cities and national agencies could adopt without relying on a single proprietary vendor stack. That pattern supported the fastest-growth outlook for government-linked demand in the generative AI in architectural design and urban planning market, especially where planning backlogs had become politically sensitive. It also widened the addressable market beyond private design firms, which gave vendors a new path into long-cycle public budgets.

Challenges Around AI Accuracy, Reliability, and Design Hallucinations

Accuracy limits remained a real brake on the generative AI in architectural design and urban planning market because design output had to comply with structural, spatial, and code requirements. A 2026 liability framework published in Buildings identified 2 major harm pathways: autonomous hallucination in safety-relevant design information and erroneous or adversarial data entering digital-twin feedback loops. The same study noted that existing tort doctrine and emerging AI regulation did not fully allocate responsibility across distributed AEC workflows, leaving verification burdens on project teams. A separate 2025 study on generative AI in architectural design and urban planning market found that machine learning performed more reliably in standardized building types than in complex civic or heritage structures. That mismatch carried a commercial problem because some of the strongest incentives to adopt AI sat in the same high-value projects where error tolerance was lowest. Until tools prove consistent performance in less regular typologies, parts of the generative AI in architectural design and urban planning market will continue to face slower deployment in high-liability use cases.

Other drivers and restraints analyzed in the detailed report include:

1. Growing Need for Low-Carbon, Energy-Efficient Building Design and Sustainability Compliance
2. Growing Integration of Generative AI With BIM and Cloud-Native Design Platforms
3. Professional Liability, Legal Accountability, and Ethical Concerns

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Platforms and solutions held 71.42% of revenue in 2025, while services are projected to grow at a 29.18% CAGR through 2031. This split showed that the generative AI in architectural design and urban planning market was still led by software acquisition, with firms first securing tools before redesigning internal delivery models. Subscription-led platforms remained the main revenue engine because buyers usually entered through production software that could support massing studies, floor planning, documentation flow, and project coordination. Autodesk's Forma rollout strengthened this pattern by expanding access to AI-enabled design capabilities across a large Revit-linked user base. Bentley also kept the platform case strong by extending AI-enabled digital twin capabilities across infrastructure workflows, which reinforced the position of established software ecosystems.

Services, however, grew faster because firms needed implementation support, workflow redesign, compliance review, and project-specific model tuning after the initial software purchase. This part of the generative AI in architectural design and urban planning market reflected a shift from buying access to buying usable outcomes inside real delivery environments. The services layer also absorbed work around verification and change management, which became important as firms moved AI from pilot use into billable project workflows. Over time, this meant value capture could move beyond licenses toward recurring advisory and managed delivery revenue, especially where design teams lacked in-house computational depth.

Cloud-based deployment accounted for 69.15% of revenue in 2025, while hybrid cloud is projected to expand at a 29.63% CAGR through 2031. Cloud remained the default architecture in the generative AI in architectural design and urban planning market because large 3D generative models required elastic compute that was difficult to replicate through standard in-house hardware. This position was reinforced by the product design of major vendors, as Autodesk Forma, Snaptrude, and ArcGIS planning tools were built around connected, continuously updated delivery environments. Cloud also supported rapid model updates, collaborative access, and easier scaling across distributed project teams, all of which improved the commercial fit of the generative AI in architectural design and urban planning market. For newer adopters, the cloud model reduced the need for large upfront hardware spending and shortened onboarding timelines.

Hybrid cloud grew faster because some buyers needed the design speed of remote compute while keeping sensitive project data and regulated information under tighter internal control. This was especially relevant in public infrastructure, large owner-operator environments, and European design firms working through strict data residency rules. The Czech Republic's Act No. 330/2025 Coll. reinforced the importance of controlled information environments in construction data management, which supported a more mixed deployment pattern over time. On-premises deployments therefore did not disappear, but they increasingly served narrow use cases where confidentiality and sovereignty carried more weight than flexibility. In practical terms, the generative AI in architectural design and urban planning market moved toward a layered deployment model rather than a simple cloud-only outcome.

Complete Report Scope:

• By Offering
  • Platforms and Solutions
  • Services
• By Deployment
  • Cloud-Based
  • On-Premises
  • Hybrid Cloud
• By Application
  • Architectural Design
  • Urban Planning
• By End-User
  • Architectural and Design Firms
  • Real Estate Developers
  • Government and Municipal Authorities
  • Construction and Engineering Companies
  • Urban Planning and Infrastructure Consulting Firms
  • Other End-Users
• By Geography
  • North America
    • United States
    • Canada
    • Mexico
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Europe
    • Germany
    • United Kingdom
    • France
    • Italy
    • Spain
    • Russia
    • Rest of Europe
  • Asia-Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Rest of Asia-Pacific
  • Middle East
    • Saudi Arabia
    • United Arab Emirates
    • Turkey
    • Rest of Middle East
  • Africa
    • South Africa
    • Egypt
    • Rest of Africa

Geography Analysis

North America held 38.26% of revenue in 2025, which kept it the largest regional contributor in the generative AI in architectural design and urban planning market. The region benefited from the concentration of major platform vendors, including Autodesk, Esri, and several AI-focused design software providers, which gave buyers earlier access to commercial tools and ecosystem support. Autodesk's 2026 Forma moves and Esri's 2026 GeoAI releases showed how much product leadership still sat inside North American software stacks. This vendor density supported faster experimentation across private firms and public agencies, especially where digital delivery was already common in design workflows. It also helped North America defend its lead even as other regions posted faster growth rates in the generative AI in architectural design and urban planning market.

Asia-Pacific is projected to grow at a 30.18% CAGR through 2031, making it the fastest-growing regional block in the generative AI in architectural design and urban planning market size. The region combined urbanization pressure, large infrastructure programs, and a policy environment that was increasingly favorable to digital planning and BIM-led delivery. China's BIM-related requirements in major municipalities, India's smart infrastructure push, and broader Southeast Asian urban investment created a large future pipeline for AI-assisted design and planning tools. The region also included markets such as South Korea and Australia, where digital planning and feasibility tools were already gaining practical relevance in housing and property workflows. This meant Asia-Pacific was not growing from one source alone, but from a mix of public investment, private construction demand, and digital planning modernization.

Europe held a strong strategic position in the generative AI in architectural design and urban planning market even without matching North America's 2025 share lead, because it combined regulatory pressure with advanced public-sector pilots. The UK's APD initiative and Germany's SPARK platform became visible reference points for how governments could adopt AI in planning while preserving human oversight. South America, the Middle East, and Africa remained earlier-stage markets, but each offered longer-term room for adoption as digital planning infrastructure and smart city programs matured. The Middle East stood out for city-scale digital twin ambitions, while parts of South America and Africa represented more gradual expansion opportunities tied to public modernization and urban development needs.

1. Autodesk Inc.
2. Bentley Systems, Incorporated
3. Esri
4. Dassault Systemes SE
5. Trimble Inc.
6. Microsoft Corporation
7. NVIDIA Corporation
8. Archistar Pty Ltd.
9. TestFit, Inc.
10. Digital Blue Foam Pte Ltd.
11. UrbanFootprint, Inc.
12. Hypar, Inc.
13. Graphisoft SE
14. Hexagon AB
15. Finch
16. Maket Technologies Inc.
17. Snaptrude Inc.
18. cove.tool

Additional Benefits:

• The market estimate (ME) sheet in Excel format
• 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 Study Assumptions and Market Definition
• 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET LANDSCAPE

• 4.1 Market Overview
• 4.2 Market Drivers
  • 4.2.1 Growing Demand for Faster Design Iteration and Project Feasibility Assessment
  • 4.2.2 Increasing Complexity of Architectural and Urban Planning Decision-Making
  • 4.2.3 Growing Integration of Generative AI Into Cloud-Based BIM, GIS, and Collaborative Design Workflows
  • 4.2.4 Growing Need for Low-Carbon, Climate-Resilient, and Performance-Optimized Design
  • 4.2.5 Rising Demand for AI-Assisted Site Feasibility, Zoning, and Building Code Analysis
  • 4.2.6 Rising Adoption of Automated Design Alternative Generation and Optimization
• 4.3 Market Restraints
  • 4.3.1 Challenges Around AI Output Accuracy, Hallucinations, and Design Reliability
  • 4.3.2 Professional Liability, Design Accountability, and Human Oversight Requirements
  • 4.3.3 Integration Complexity Across BIM, CAD, GIS, and Enterprise Data Environments
  • 4.3.4 Data Privacy, Intellectual Property, and AI Model Governance Constraints
• 4.4 Value Chain Analysis
• 4.5 Regulatory Landscape
• 4.6 Technological Outlook
• 4.7 Porter's Five Forces Analysis
  • 4.7.1 Bargaining Power of Suppliers
  • 4.7.2 Bargaining Power of Buyers
  • 4.7.3 Threat of New Entrants
  • 4.7.4 Threat of Substitutes
  • 4.7.5 Competitive Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

• 5.1 By Offering
  • 5.1.1 Platforms and Solutions
  • 5.1.2 Services
• 5.2 By Deployment
  • 5.2.1 Cloud-Based
  • 5.2.2 On-Premises
  • 5.2.3 Hybrid Cloud
• 5.3 By Application
  • 5.3.1 Architectural Design
  • 5.3.2 Urban Planning
• 5.4 By End-User
  • 5.4.1 Architectural and Design Firms
  • 5.4.2 Real Estate Developers
  • 5.4.3 Government and Municipal Authorities
  • 5.4.4 Construction and Engineering Companies
  • 5.4.5 Urban Planning and Infrastructure Consulting Firms
  • 5.4.6 Other End-Users
• 5.5 By Geography
  • 5.5.1 North America
    • 5.5.1.1 United States
    • 5.5.1.2 Canada
    • 5.5.1.3 Mexico
  • 5.5.2 South America
    • 5.5.2.1 Brazil
    • 5.5.2.2 Argentina
    • 5.5.2.3 Rest of South America
  • 5.5.3 Europe
    • 5.5.3.1 Germany
    • 5.5.3.2 United Kingdom
    • 5.5.3.3 France
    • 5.5.3.4 Italy
    • 5.5.3.5 Spain
    • 5.5.3.6 Russia
    • 5.5.3.7 Rest of Europe
  • 5.5.4 Asia-Pacific
    • 5.5.4.1 China
    • 5.5.4.2 Japan
    • 5.5.4.3 India
    • 5.5.4.4 South Korea
    • 5.5.4.5 Australia
    • 5.5.4.6 Rest of Asia-Pacific
  • 5.5.5 Middle East
    • 5.5.5.1 Saudi Arabia
    • 5.5.5.2 United Arab Emirates
    • 5.5.5.3 Turkey
    • 5.5.5.4 Rest of Middle East
  • 5.5.6 Africa
    • 5.5.6.1 South Africa
    • 5.5.6.2 Egypt
    • 5.5.6.3 Rest of Africa

6 COMPETITIVE LANDSCAPE

• 6.1 Market Concentration
• 6.2 Strategic Moves
• 6.3 Market Share Analysis
• 6.4 Company Profiles (includes Global Level Overview, Market Level Overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share, Products and Services, Recent Developments)
  • 6.4.1 Autodesk Inc.
  • 6.4.2 Bentley Systems, Incorporated
  • 6.4.3 Esri
  • 6.4.4 Dassault Systemes SE
  • 6.4.5 Trimble Inc.
  • 6.4.6 Microsoft Corporation
  • 6.4.7 NVIDIA Corporation
  • 6.4.8 Archistar Pty Ltd.
  • 6.4.9 TestFit, Inc.
  • 6.4.10 Digital Blue Foam Pte Ltd.
  • 6.4.11 UrbanFootprint, Inc.
  • 6.4.12 Hypar, Inc.
  • 6.4.13 Graphisoft SE
  • 6.4.14 Hexagon AB
  • 6.4.15 Finch
  • 6.4.16 Maket Technologies Inc.
  • 6.4.17 Snaptrude Inc.
  • 6.4.18 cove.tool

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-Space and Unmet-Need Assessment