Generative AI Is Entering Decision Support at Wastewater Plants

A Constant Assistant Beside the Operator

The SCADA, IoT and data lake infrastructure that has spread across wastewater treatment plants over the last three years is enabling a new application layer: large language model (LLM) based operator assistants fed with process knowledge. Multiple pilots in Europe, Japan and the United States are showing that generative AI is producing concrete value as a decision support tool in plant operations.

What Questions Does It Answer

Early use cases for the assistant layer cluster around questions like:

• "Why has dissolved oxygen in the aeration tank dropped over the last 30 minutes?"
• "What is the optimal recycle ratio for total nitrogen at this influent load?"
• "Transmembrane pressure on the membrane module is over the threshold, what are the likely root causes?"
• "Given the next 24-hour rainfall forecast, is the equivalent buffer capacity sufficient?"
• "Which three abnormal parameters should be tracked at shift change?"

How Process Knowledge Is Connected

Where the assistant layer creates value is that the language model is not running on its own. The models are connected to the plant's process simulation software (BioWin, GPS-X and similar), the SCADA historian and standard operating procedures through tool access. When a question comes in, the model retrieves the relevant data source and prepares the answer with raw data; this approach is known as retrieval-augmented generation (RAG) and significantly reduces hallucination risk.

Documented Benefits

Measurable benefits reported from pilot plants:

• 30 percent reduction in knowledge transfer time at shift handover
• 25 percent decrease in anomaly response time
• 40 percent acceleration in junior operator training time
• Clear improvement in adherence to standard procedures

Limits and Risks

Generative AI calls for careful adoption in the sector, with several boundaries underlined:

• Assistant layer position rather than autonomous decisions (operator authority is preserved)
• No AI authority over safety-critical actions (shutdown, bypass)
• Data governance: contractual controls for transferring plant operating data to the model provider
• Hallucination verification protocol and audit trail

A Path for Turkey

For large plant operators and EPC firms in Turkey, a three-step starting plan stands out: cleaning SCADA history into structured data, digitising procedure documents, and running the first pilot with open-source models (Llama, Mistral) in a closed environment. This approach addresses data sovereignty concerns and builds a critical tool for medium-term operational excellence.

Market Shape

Sector SCADA providers (Siemens, Schneider, Rockwell), specialised software firms (Dynamita, Hach) and the major cloud providers (AWS, Azure, Google Cloud) are all positioning themselves in this new segment. Over the next three years, the global AI-driven decision support market in the water sector is expected to reach the 8 billion USD band, growing 35 percent annually.