Nanotechnology based electrochemical estimation of kaempferol: the challenges, future perspectives and artificial intelligence

Abstract This article describes electroanalytical methods developed over the last 25 years for kaempferol (an important molecule) detection, with a main emphasis on voltammetric techniques like cyclic voltammetry, differential pulse voltammetry, and square wave voltammetry. Extensive research describes how electrode surface alterations (using metal nanoparticles, carbon nanomaterials, metal–organic frameworks, and conductive polymers) enhance electron transfer kinetics and analytical performance. These nanostructured devices enabled low‐level detection limits, i.e., nano‐ to picomolar concentrations, even in complex biological and environmental matrices, foods, and pharmaceuticals. Despite these improvements, challenges like electrode fouling, matrix interference, overlapping oxidation signals from structurally similar flavonoids, and low portability continue to be barriers to real‐world sample applications. Furthermore, this review highlights emergent solutions, comprising miniaturized and paper‐based devices, molecularly imprinted sensors, and smartphone‐integrated platforms. Special attention is given to the rising role of artificial intelligence and machine learning in electrochemical sensing, where chemometric and deep‐learning methods advance the signal processing, solve overlapping peaks, decrease human‐induced errors, and permit multi‐analyte analyses. Briefly, this review proves that the combination of nanotechnology and artificial intelligence is capable of transforming the electrochemical kaempferol determination from laboratory methods to portable, robust, and intelligent sensing systems for clinical diagnosis, food safety, and pharmaceutical analyses. © 2026 Society of Chemical Industry (SCI).