How AI is transforming water assets: Hariharan V, Global CIO, VA Tech WABAG
In asset-heavy industries, digital transformation is often mistaken for software modernization. For VA Tech WABAG, the real shift is happening much closer to the ground—inside pumps, membranes, and treatment plants that operate for decades under tight regulatory and environmental constraints.
Under the leadership of Hariharan V, Global CIO, VA Tech WABAG’s technology agenda is increasingly shaped by one question: how can AI materially improve the reliability, efficiency, and economics of water infrastructure?
Building the digital foundation for AI-led operations
Before AI can deliver value, the fundamentals must be right. WABAG’s recent digital initiatives have focused on securing sensitive information, enabling global collaboration, and modernizing core applications that support long-cycle infrastructure projects. “Protecting company’s sensitive information from security threats and give confidence to our business and stakeholders a safe working environment,” says Hariharan.
In parallel, the company has invested in scalable communication and collaboration platforms to support teams and customers spread across geographies. Core applications have been upgraded and integrated with scalable infrastructure so that project documentation and operational knowledge remain secure while being accessible to authorized users worldwide.
This foundation is critical, not only for execution efficiency but also for enabling advanced analytics and AI models that depend on high-quality, trusted data.
Moving IT from support to strategic enabler
WABAG’s operating footprint spans water, energy, and industrial infrastructure—domains where IT has traditionally played a secondary role. That paradigm has shifted.
The company has deliberately repositioned technology as a core business enabler, supporting its evolution from an engineering contractor to a water technology company. IT now underpins differentiation in bids, operational margins, and long-term service models.
“IT is no longer just a ‘back-office’ support tool; but is the primary engine for revenue growth, operational margins, and market differentiation,” states Hariharan.
This shift has also changed how digital investments are evaluated—less by system uptime, and more by asset performance, lifecycle costs, and service outcomes.
AI becomes the nervous system of water assets
AI is central to this transformation. At WABAG, it is no longer treated as a bolt-on capability, but as an operational layer embedded into plant performance and asset management. “In WABAG, AI is being transitioned from a high-tech ‘add-on’ to the central nervous system of their water treatment assets.”
Through a partnership with Pani Energy, WABAG uses the Pani ZED platform to create real-time digital twins of treatment plants. These models continuously simulate plant behavior, analyze historical and live data, and predict failures before they occur.
This enables a shift from reactive maintenance to predictive and preventive operations—improving uptime, reducing unplanned outages, and lowering operating costs. AI models can anticipate issues such as membrane fouling, pump degradation, or motor failure well before they impact service delivery.
From engineering projects to intelligent, autonomous assets
The impact of AI extends beyond operations into how projects are designed and delivered. Instead of static engineering drawings, WABAG increasingly relies on digital twins and simulation models early in the design phase to optimize energy usage, chemical consumption, and long-term operability.
Over time, this intelligence is expected to support more autonomous plant operations, where AI-driven control systems can recommend or implement real-time adjustments based on changing input conditions. The result is infrastructure that not only runs more efficiently, but continuously learns and improves.
This shift also opens the door to new service models. Predictive intelligence allows WABAG to move toward outcome-based contracts, where performance guarantees replace reactive repair models—creating a software-enabled service layer on top of physical infrastructure.
“VA Tech Wabag’s transition from a pure-play engineering firm to a ‘Digital Water Service Provider’ is one of the most significant pivots in the industry,” says Hariharan.
AI as a long-term strategic differentiator
For WABAG, AI is not about short-term efficiency gains. It is about redefining how water infrastructure is built, operated, and sustained over decades. By embedding intelligence into assets and aligning IT, OT, and data strategies, the company is creating a model where digital transformation directly translates into operational resilience and measurable outcomes.