In a little over two months, winter will descend on the Indo-Gangetic Plain, and with it, the familiar smog. For over three crore people in Delhi-NCR, this means tracking the Graded Response Action Plan (GRAP) directives of the Commission for Air Quality Management in National Capital Region and Adjoining Areas (CAQM), and planning their activities. The CAQM will rely on the Air Quality Early Warning System’s (AQEWS) forecasts to decide which stage of GRAP to impose.

The AQEWS is remarkably accurate. According to a study by the Council on Energy, Environment and Water (CEEW), it can predict days with air quality index (AQI) of 300 and above with over 80% accuracy. A series of crises — the Great Smog of 2016, the pollution episodes of 2017, the deadly dust storms of 2018 — gave birth to this system. Today, seven other cities beyond Delhi have their own AQEWS: Pune, Bengaluru, Hyderabad, Ahmedabad, Kolkata, Mumbai, and Jaipur.

Crises gave us a generation of digital air quality management tools. The current spring of artificial intelligence (AI) offers newer, better ones. But we must tread with caution. How these AI-enabled systems are designed, used, and funded will determine whether they become a long-term paradigm shift or end up in the graveyard of obsolete technology.

Also Read | Delhi-NCR chokes as AQI levels cross 400, hits ‘severe’ category

First, adopt AI-driven air quality decision support systems (AQDSS) and incorporate end-user feedback from day one. Air quality data comes from monitoring stations, models and........

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