With the passage of the Moving Ahead for Progress in the 21st Century Act, commonly known as MAP-21, there has been increased focus and attention to asset management programs in transportation agencies and the development of risk-based asset management plans. These plans document the transportation assets being managed by the agency, summarize current and planned performance expectations, and outline the investment plans that the agency will make to meet performance targets. Although MAP-21 requires the plans to include only pavements and bridges on the National Highway System, state transportation agencies are encouraged to include all infrastructure assets within the right-of-way corridor in their plan. With all this focus on asset management some agencies may draw the conclusion that pavement management is less important than it has been in the past. Is there any truth to that conclusion? Is there a future for pavement management beyond data collection activities? This paper addresses these questions by demonstrating the expanding role for pavement management in supporting an agency's asset management initiatives and the importance of developing pavement management tools that are used for more than gathering and reporting pavement conditions. The authors illustrate the importance of pavement management analysis results to develop key components of an asset management plan. For instance, the paper illustrates how pavement management outputs are critical to being able to: a) conduct a life-cycle analysis showing the cost-effectiveness of different treatment strategies, b) evaluate trade-offs when making investment options across asset types, and c) identify and manage risks that might impact the agency's ability to achieve its goals. The paper concludes with recommendations for enhancements to existing pavement management systems that are needed to better support the asset management environment in which most transportation agencies operate. Specifically, the paper discusses the importance of integrating pavement management data with other asset data, incorporating the performance of preservation activities in prediction models, and capturing the impact of capital investments on future maintenance costs to truly evaluate the whole life costs of a given option.