Artificial intelligence is steadily reshaping how buildings are designed, planned, and delivered, but its real impact lies beyond headlines and hype. In the AEC industry, AI is increasingly embedded in everyday workflows, influencing decisions across design, construction, and project management. Drawing from his experience at the intersection of education and industry, Harkunwar Singh, CEO and Co-Founder of Novatr offers a grounded view of where AI is genuinely improving efficiency and where expectations remain overstated. In conversation with Asma Rafat, Senior Correspondent, Realty+, he also examines how evolving technologies are changing professional skill requirements and why adaptability matters more than tool expertise.
AI is rapidly entering every stage of the AEC workflow. From your perspective, where is it already making the most meaningful impact today, and where is the hype running ahead of reality?
Harkunwar Singh: AI is already delivering tangible impact in data-intensive and repetitive workflows such as clash detection, quantity estimation, scheduling optimisation, and early-stage design simulations. According to Autodesk’s 2025 Design & Make Report, over 76% of AEC industry leaders are increasing their investment in AI, reflecting real adoption across design, planning, and construction management.
Where the hype runs ahead of reality is in expectations of fully autonomous design or construction. AEC projects remain highly contextual, regulated, and risk-driven. AI today works best as a decision-support layer, helping professionals make faster and better-informed choices—but not replacing human accountability or judgement.
One of Novatr’s core goals is closing the gap between education and industry. How is AI changing the skills that architects and construction professionals now need, compared to even five years ago?
Harkunwar Singh: Five years ago, the focus for architects and construction professionals was largely on mastering specific software tools. Today, AI has fundamentally shifted the requirement toward adaptability, systems thinking, and data-driven decision-making.
AI is automating many routine tasks, which means professionals are now expected to interpret outputs, validate insights, and apply judgement across design, planning, and execution. Industry research, including the World Economic Forum’s Future of Jobs reports, consistently shows growing demand for skills like analytical thinking, active learning, and cross-disciplinary collaboration.
For Novatr, this reinforces the need to bridge education and industry by moving beyond tool-based training and focusing on job-ready, transferable skills—skills that remain relevant even as technologies continue to evolve.
In design and planning, AI promises speed, optimisation, and data-driven decisions. How do you ensure these tools support human judgement and creativity rather than replace them?
Harkunwar Singh: In design and planning, the risk is not that AI will replace creativity, but that it may be used without sufficient judgement. To prevent that, AI must be positioned as a support system, not a decision-maker.
From an education standpoint, this means training professionals to clearly define intent, constraints, and success criteria before using AI tools.
When learning emphasises critical thinking over output, AI actually expands creative capacity. It frees designers from repetitive work and gives them more time to focus on ideas, problem framing, and design intent—where human creativity is irreplaceable.
Construction execution has traditionally been slower to adopt new technologies. How are AI-led tools being used on-site today, and what barriers still prevent wider adoption?
Harkunwar Singh: On-site, AI is being used for progress tracking, safety monitoring, quality checks, and schedule risk prediction, mainly through computer vision and sensor-driven tools.
Wider adoption is held back less by technology and more by skills gaps, fragmented workflows, and resistance to change in high-risk site environments. From an upskilling perspective, adoption improves when AI tools are translated into practical, role-specific capabilities that site teams can trust and use confidently.
With AI tools evolving faster than formal curricula, how should architecture and construction education adapt to remain relevant without becoming overly tool-dependent?
Harkunwar Singh: Architecture and construction education must move away from fixed, tool-based curricula toward foundational and adaptable learning models. The focus should be on teaching principles such as computational thinking, data interpretation, and workflow understanding rather than specific tools.
By adopting modular, industry-aligned programs that evolve continuously, education can stay relevant while ensuring learners develop long-term capabilities, not short-term tool dependency.
Looking ahead, do you see AI creating more specialised roles within the AEC industry, or pushing professionals to become broader, hybrid thinkers who combine design, data, and execution skills?
Harkunwar Singh: AI will create some new specialised roles, but the larger shift will be toward hybrid professionals. As AI handles narrower technical tasks, the most valuable professionals will be those who can connect design intent, data insights, and execution realities.
From an education standpoint, this means preparing learners to think across disciplines rather than operate in silos. The future AEC workforce will be defined less by job titles and more by the ability to integrate skills across the project lifecycle.
