Integrating AI in the World’s Least Digitised Industry

While many industries are adopting artificial intelligence at a rapid pace, the built-environment sector continues to trail behind.

The RICS artificial intelligence in construction report 2025 offers a global snapshot of how the sector is approaching AI adoption. The study draws on insights from over 2,200 professionals worldwide, spanning geographies and disciplines across the construction value chain.

The findings reveal that AI adoption across the sector remains at an early stage. Nearly 45% of organisations report no use of AI whatsoever. Just under 12% say AI is used regularly within specific workflows, and fewer than 1% have embedded AI across multiple business processes.

Organisational readiness mirrors this slow uptake. While interest in AI is growing, most firms have yet to move beyond the exploratory stage. Only around 20% are engaged in strategic planning or proof-of-concept pilots, and very few have committed dedicated budgets or defined implementation roadmaps. The result is a clear gap between intent and execution.

In a conversation with AIM, Biswajeet Mahapatra, Principal Analyst at Forrester, explains that construction lags because of its structural complexity. “The construction industry is the least digitised in AI adoption because work is highly fragmented, project-based and executed in unpredictable physical environments where data is unstructured, inconsistent, and hard to capture at scale.”

Unlike manufacturing or software development, construction relies on temporary teams, manual processes and legacy contracting models. Low margins further constrain investment in digital systems. 

Outcomes depend heavily on human judgement, site conditions, and coordination across many small vendors, factors that make standardisation and AI-driven automation far more difficult.

As global capability centres (GCCs) evolve from back-office support units to value creators, Nemetschek Group is sharpening its India strategy. It is anchoring growth around AI-led product engineering and deep domain expertise in architecture, engineering, and construction (AEC).

Speaking to AIM, Sanjay Kumar Singh, Managing Director of Nemetschek Group’s GCC in India, says the company sees the country as central to its global transformation journey, both as a technology hub and an emerging market.

“I joined Nemetschek at a very interesting time. The industry is transforming, the company is transforming, and Nemetschek has big plans for India—both commercially and from a GCC point of view.”

From Acquisition to Strategic GCC

Despite widespread concerns that AI will reduce headcount, Nemetschek continues to expand its India operations.

“Construction is one of the least digitised industries—less digitised than fishing. If you want disruption here, you need thinkers and innovators. This is not business as usual,” Singh adds.

The talent strategy blends technical expertise—GenAI, DevOps, UI and C# engineers—with domain experts such as civil and structural engineers.

Nemetschek’s presence in India began nearly 12 years ago, when it began with a local company that was subsequently acquired by the German AEC software major. Today, the GCC operates out of Hyderabad and Bengaluru, with a headcount of around 180-190 employees.

The expansion roadmap is ambitious.“By 2026, we expect to reach around 350 employees, and within two to three years, about 500,” Singh mentions.

The GCC is structured across two broad pillars: shared services (IT, HR, finance, SOPs) and core R&D. The strategic shift is happening within R&D.

“We are moving from product- or brand-specific teams to centres of excellence—creating capabilities around AI that can serve any product or brand across the group,” he explains

Embedding AI Natively Into Workflows

Rather than launching standalone chatbot-style GenAI tools, Nemetschek is focusing on embedding native AI directly into the workflows used by architects, civil engineers, and construction professionals.

“Earlier, everyone was writing wrappers around LLMs and calling them chatbots. That phase is over. We want to embed AI natively—inside the design and modelling experience,” Singh adds.

The objective is to ensure productivity gains that matter in a traditionally under-digitised industry.

“If an architect can complete the same work in half the time, that is meaningful impact. It’s not about retrieving stored information—it’s about changing how work gets done.”

Nemetschek is also exploring agentic AI, where multiple AI agents work together through an orchestration layer.

“We are moving from LLM wrappers to RAG and now towards agentic AI. These agents work in tandem to give architects suggestions that otherwise would take a lot of time,” Singh highlights.

While agent development is still underway, teams in Europe, Hyderabad, and Bengaluru are collaborating closely. The company is also strengthening its GenAI centre of excellence in India.

Digital twins form another cornerstone of Nemetschek’s technology stack, with India teams already contributing significantly.

While Europe remains Nemetschek’s most mature market, India is firmly on the company’s radar.

Though adoption of Building Information Modelling in India is still evolving, Singh believes structural shifts, project delays, cost overruns, and labour shortages will accelerate technology uptake.

The company is also investing in long-term ecosystem development, partnering with academic institutions such as IIT Madras, RV College of Architecture, and institutes across Maharashtra to offer licenses and training to build industry-ready talent.

Hyderabad and Bengaluru: A Deliberate Dual Strategy

Nemetschek’s presence in both Hyderabad and Bengaluru is a deliberate choice.

“Cloud and platform talent is easier to find in Hyderabad. GenAI hiring has been easier in Bengaluru. If you have to pick two locations in India, these have to be the two,” he says.

As the GCC matures, 2026 is expected to be a defining year.

“You need critical mass to make centres of excellence work. Hiring the right talent—without lowering the bar—is our biggest priority,” Singh believes.

In an industry often characterised as slow to digitise, Nemetschek is betting that embedded, workflow-driven AI—backed by domain expertise and scale—can help bridge the gap between experimentation and transformation.