The success of modern product design often relies on the thoughtful selection of next-generation technologies. However, common systems engineering methodologies tend to treat new technologies as risks to be minimized rather than as opportunities to enhance system capabilities. To bridge this gap, this study presents a new framework called PoLaRis for comprehensive technology infusion concepts assessment based on three parameters: Leap Potential, Learning and Risk. The introduction of Learning as a decision-making criterion complements Risk and Leap Potential, embedding an organizational learning perspective that values the knowledge gained through technology infusion. These three main parameters can be evaluated through expert feedback or a numerical approach. In the numerical approach, rooted in DSM analysis, Risk is quantified based on the maturity of the technology components and a system integration risk metric, while Learning is estimated from the structural complexity of the architectural changes. Leap Potential is quantified using the Technology Leap Potential (TLP) metric, which captures a technology’s contribution to product value from the user’s perspective and applies to both incremental and disruptive innovations. Two case studies were conducted to evaluate three smartwatch concepts featuring an AI power-saving chip and innovative stress detection methods. The first case study relied on 11 expert evaluations, while the second applied the numerical approach. The results showed alignment between expert and numerical assessments, indicating the internal consistency between the selected mathematical measures and expert opinions. Taken together, the Leap–Learning–Risk profiles visualize each option’s benefits and trade-offs, facilitating comparison and informed decision making.