This study extends the concept of energy in fuzzy soft sets and neutrosophic soft sets by introducing energy computation for intuitionistic fuzzy soft sets. We define upper and lower energy in this context and develop a decision-making framework based on eigenvalues of corresponding matrices. The intuitionistic fuzzy soft set is represented as a structured matrix which is processed through specific norm-based and product-based operations to quantify decision stability. Compared to existing models, the proposed approach offers a systematic way to evaluate alternatives using eigenvalue-based energy computation. By incorporating membership and non-membership degrees without additional indeterminacy, it provides a more computationally efficient alternative to neutrosophic soft set energy models. The resulting energy values serve as key indicators in decision evaluation, allowing for a more structured ranking of alternatives. Through case studies, we demonstrate the practical application of the method in multi-criteria decision-making. A comparative analysis with the neutrosophic soft set energy model confirms that our approach maintains decision accuracy while improving computational efficiency. This makes it particularly suitable for large-scale decision problems such as project selection and strategic planning, where stability and interpretability are essential.