Are Digital Twins

Short answer: yes — but they’ve moved from novelty to practical, uneven adoption. Digital twins, progressive assurance (a structured, staged approach to quality and handover) and AI are all major conversation topics in AEC today — increasingly driven by real projects, vendor products and new contracting approaches — yet uptake varies by sector, project size and organizational maturity. Below, we explain where each stands in 2024–25, what’s actually happening on projects, and the practical barriers firms still face.

Digital Twins: From Concept to Critical Infrastructure

Digital twins are no longer just marketing copy; governments and large owners are harnessing them to improve decision-making, operations and whole-life value. Recent industry analysis highlights their ability to accelerate and improve complex infrastructure and facility decisions, and to deliver measurable ROI when tied directly to operational needs (asset management, maintenance, energy, or transport optimisation). McKinsey & Company+1

What’s happening now:

  • Owners of large or critical assets (transit, data centres, hospitals, campuses) are commissioning digital twins that connect BIM, IoT sensors, and operational data — aimed at predictive maintenance, energy optimisation and scenario simulation. Digital Construction Hub
  • Software vendors (Autodesk Tandem, Bentley iTwin, Azure Digital Twins and others) are shipping more dashboarding, data-validation and ops-focused features to make twins useful beyond handover.
  • Case studies and academic reviews show digital twins work best when built for clear use cases (not “build everything” experiments). Technical success is usually tied to governance, data quality and stakeholder alignment. ScienceDirect+1

Bottom line: digital twins are hot where owners can justify operational savings or risk reduction, and they’re maturing from R&D projects to business cases — but broad, small-project adoption remains limited.

Progressive Assurance: Proactive Risk Management, Gaining Traction as Part of Delivery

“Progressive assurance” — the idea of staged, ongoing assurance checkpoints across design and delivery to reduce nonconformance and rework — is being adopted in quality management and increasingly referenced alongside progressive design-build delivery approaches. Industry guidance and project teams are formalising assurance points to improve handover readiness and reduce surprises at practical completion. Shirley Parsons+1

What’s happening now:

  • Contracting bodies and insurers are publishing documents and guidance that support progressive (staged) design–build and clearer assurance milestones so owners and contractors share risk and visibility earlier. aiacontracts.com+1
  • On projects using digital workflows, progressive assurance is often implemented via dashboards, data completeness checks and automated QA rules that gate progress to the next stages. That makes assurance practical rather than purely audit-based.

Bottom line: progressive assurance is not a flashy technology but a pragmatic shift in delivery mindset — it complements digital twins and BIM by turning data checks into contractual checkpoints.

AI: The Engine Behind Smarter Workflows, Cautious Rollout

AI is everywhere in AEC conversations — from design automation, clash detection and quantity take-offs to safety monitoring and predictive maintenance — but adoption is mixed. Recent industry surveys show many firms experimenting with or running pilots; a significant share report little to no implementation yet, reflecting uncertainty around integration, skills and clear ROI. RICS+1

What’s happening now:

  • Practical AI use cases on-site: video analytics for PPE and hazard detection, automated progress monitoring from cameras and photogrammetry, and NLP to extract data from specs and RFIs. Vendors are productizing these into usable features (safety cameras, automated reporting).
  • Design-side AI (generative design, code compliance checking, cost estimation) is being trialled by larger firms and software vendors; many smaller firms still rely on human expertise supported by point tools. BuiltWorlds
  • Challenges: data silos, lack of common standards, limited in-house AI skills, legal/regulatory concerns about automated decisions and liability, plus demand for explainability and auditing of AI outputs. RICS

Bottom line: AI is hot in headlines and pilot decks; its real, scaled impact depends on firms solving integration, governance and workforce-readiness problems.

Cross-cutting Realities and Challenges

  1. Data & interoperability depend on clean, connected data. Twins, assurance gates and AI all fail or underdeliver with poor data governance. Taylor & Francis Online
  2. Value-led use cases — the most successful implementations tie tech to a clear owner problem (lower OPEX, avoid rework, prevent downtime). McKinsey-level ROI arguments are influencing public-sector pilots. McKinsey & Company
  3. People & contracts — new contracting forms (progressive design-build, staged handover) and new roles (data managers, digital delivery leads) are emerging to make tech work in practice. aiacontracts.com
  4. Uneven adoption — large owners, infrastructure and specialist sectors lead; small builders and many SME consultants lag.

Practical Advice for Firms and Project Teams

  • Start with a single, measurable use case (e.g., reduce O&M cost on HVAC via a twin; reduce site incidents using AI cameras). Build instrumentation and data pipes for that use case first. McKinsey & Company
  • Bake progressive assurance into contractual milestones: define data completeness gates, QA rules and handover outputs up front. Shirley Parsons+1
  • Focus on data quality, responsibilities and a simple integration layer (APIs, common formats) before buying “advanced” AI. Taylor & Francis Online
  • Invest in a small multidisciplinary team (project manager + data engineer + domain SME) to run pilots, measure outcomes and scale what works.

Innovation is moving fast. The question isn’t whether these technologies are still relevant — it’s whether you’re ready to harness them. At Draftech, we believe your project deserves more than just support. It deserves a partner who understands the landscape and can guide you through it.

Draftech — Your Project, Our Expertise.

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