The idea of statistical convergence had been extended to ideal convergence by \textit{P. Kostyrko} et al. in [Real Anal. Exch. 26, No. 2, 669--685 (2001; Zbl 1021.40001)] with the help of ideals. This approach is much more general as most of the known convergence methods become special cases, but many questions regarding this convergence still remain open as most results involving statistical convergence where the density function has been used explicitly cannot be obtained for general ideals. The article develops and analyzes ideal statistical convergence of sequences of functions in the framework of intuitionistic fuzzy normed spaces (IFNS). The authors introduce pointwise and uniform ideal statistical convergence for function sequences in IFNS. Establish equivalence results, examples, and theorems showing their relation to classical convergence, statistical convergence, and ideal convergence. Prove results such as closure under linear combinations, product, and reciprocal operations. Extend known results (e.g., uniform limit theorem) to the setting of IFNS.