The real estate sector in India has not traditionally been viewed as digitally progressive. Tata Realty & Infrastructure Ltd. (TRIL) is challenging that perception through a structured digital transformation journey that began in 2020. In an interview with Express Computer, Girish Hadkar, Chief Information and Digital Officer at Tata Realty & Infrastructure, outlined how the organization is aligning core systems modernization with AI adoption and long-term sustainability goals.
A unit of Tata Sons, TRIL develops commercial real estate, residential projects, and infrastructure assets including roads, bridges and ropeways. Its transformation strategy reflects a deliberate move from fragmented systems toward an integrated, enterprise-wide digital architecture.
Why Clean Core Was TRIL’s First Strategic Move
Construction and real estate enterprises often struggle with fragmented project systems, siloed financial data, and limited cross-functional visibility between leasing, operations and finance. This fragmentation typically inhibits enterprise-wide transparency and slows decision velocity.
TRIL prioritized core standardization as a prerequisite for scalable AI adoption across business operations.
“We began by strengthening our core. SAP S/4HANA, Salesforce CRM, and our Azure analytics platform form the digital backbone of the company. Without that foundation, you can’t scale AI, IoT, or advanced analytics meaningfully,” Hadkar said.
The company implemented Magic XPI as a middleware integration layer to orchestrate data flows across systems. The architecture reflects a clean core strategy, with a standardized transactional backbone and an extensible innovation layer that enables experimentation without destabilizing enterprise systems.
“One track keeps our core rock-solid and up-to-date, and another aggressively explores emerging technologies. That agility has made us early movers in areas like integrated construction cloud platforms and IoT-enabled campuses,” Hadkar said.
How AI and Integration Improved Leasing Performance
With a harmonized core in place, TRIL extended intelligence into customer-facing and operational workflows, connecting peripheral applications into a unified enterprise data model.
TRIL integrated Salesforce into its core SAP Real Estate environment to establish a unified tenant data model, enabling enterprise-wide transparency across leasing, billing and reporting. The tighter integration shortened lead-to-lease cycle times while delivering real-time pipeline visibility, according to Hadkar.
With embedded dashboards drawing from a unified data model, teams gained real-time operational visibility, reducing manual reconciliation and accelerating decision times.
The company also developed a virtual assistant powered by Salesforce Agentforce AI for relationship managers.
“It can summarize 50–70 inbound emails per day, retrieve booking or payment information through natural language queries, and even draft responses,” Hadkar said. “Our RMs resolve queries faster, and we’ve already seen an improvement in NPS feedback.”
By embedding AI into its marketing workflows, TRIL moved from broad-based outreach to precision user targeting. Drawing on unified customer data, the AI recommendation engine delivers contextual property suggestions that increase engagement and shorten conversion times across the leasing funnel. For instance, prospective buyers browsing the system are showcased content relevant to their buying capacity – residential buyers are shown homes, and commercial buyers are shown retail and office spaces.
“Visitors who engaged with AI-driven recommendations showed noticeably higher conversion rates than those receiving generic property lists,” Hadkar added.
How Digital Twins Support TRIL’s 2045 Carbon Neutrality Goal
In alignment with the Tata Group’s climate commitments, TRIL aims to achieve net carbon neutrality across its operations by 2045.
To support this objective, the company has deployed IoT sensors across commercial properties to monitor energy consumption, occupancy patterns, air quality and asset performance in real time. The resulting data feeds into centralized dashboards that allow facilities teams to optimize energy usage and shift from reactive to predictive maintenance models.
TRIL has also piloted digital twin capabilities within select campuses, creating dynamic 3D models linked to live operational data. These digital twins provide enterprise-wide visibility into building performance, enabling scenario modeling for energy optimization, asset lifecycle planning and sustainability tracking.
By integrating environmental data streams into its broader analytics architecture, TRIL is positioning ESG performance as an operational metric embedded within enterprise systems rather than a standalone reporting exercise.
Expected Path and Current Maturity
According to Hadkar, as of 2026 TRIL is in the scale-and-optimize phase of its transformation, building on the clean core foundation established since 2020. With SAP S/4HANA and CRM integration largely stabilized, the focus has shifted toward embedding AI into operational workflows while preserving architectural discipline.
Over the next six months, the roadmap centers on expanding digital twin deployments across additional campuses, formalizing AI governance controls, and further integrating sustainability metrics into financial planning and asset management processes. This near-term phase is designed to convert successful pilots into repeatable, enterprise-wide capabilities, Hadkar said.
Long term, TRIL’s stated objective of achieving net carbon neutrality by 2045 provides the strategic horizon for its digital investments. The maturity path therefore links ERP modernization today with AI-enabled optimization in the medium term and fully operationalized, system-embedded sustainability as the 2045 end state.
What This Means for ERP Insiders
Clean core determines transformation scalability. Enterprises that modernize and standardize their transactional backbone before layering AI or IoT reduce structural risk and avoid compounding technical debt. For large organizations, architectural discipline ultimately determines whether innovation scales or stalls.
Integrated data unlocks measurable AI performance. AI only delivers sustained enterprise value when embedded into workflows supported by unified data models across CRM, ERP and analytics platforms. For complex organizations, integration is what converts intelligent pilots into operating model advantage.
Sustainability becomes strategic when embedded in systems. When environmental data is integrated into core enterprise analytics, ESG shifts from compliance reporting to operational performance management. Large asset-heavy enterprises can align carbon targets with financial planning and asset strategy only when sustainability is architected into the digital backbone.
