A digital ecosystem is a collection of networked information technology resources that can function as an integrated entity. The dominant ecosystems today were created by large tech companies, such as Amazon, Google, Microsoft, and Apple, using hyperscale platforms. The underlying computing technology is dominated by mobile and cloud providers that spend billions of dollars per year for software, networks, processors, accelerators, memory, and storage, strongly influencing what is commercially available. The result is that T&E organizations are increasingly dependent on this ecosystem with diminishing influence over it. The dominant applications today are data-driven and artificial intelligence-based. To function in this ecosystem and assimilate the massive amounts of test data to facilitate knowledge discovery, T&E organizations must adapt people, processes, tools, and policy. In addition, many of the systems to be tested, for example, autonomous and semi-autonomous vehicles, are part of a digital ecosystem themselves and contain artificial intelligence elements. We must understand how to test at scale, how to assess data in place without transport to a central repository, how to adapt our organizations and processes to accommodate the inevitable incorporation (and sustainment) of machine learning test tools, and how to recruit, motivate, and retain a highly skilled workforce including scientists, engineers, technicians, and mechanics.