Submitted by Board Member, Ryan Heimer

Technology Policy, Democratic Institutions, and the Future of Public Administration 

The relationship between government and technology has entered a new phase. In earlier eras, public administration often treated technology as a supporting function that has been important for efficiency, recordkeeping, and communication, but secondary to the central tasks of policy design, budgeting, and implementation. That distinction is becoming increasingly untenable. Artificial intelligence, semiconductor supply chains, digital platforms, cloud infrastructure, and data governance now shape not only how governments operate, but also how they exercise authority, maintain legitimacy, and deliver public value. 

Recent works on technology and governance including Chris Miller’s Chip War, Jennifer Pahlka’s Recoding America, and Alexander C. Karp and Nicholas W. Zamiska’s The Technological Republic. They offer a particularly useful framework for understanding this transformation. Although these works approach the subject from different vantage points (geopolitical competition, bureaucratic reform, and national strategy) they converge on a shared conclusion: the ability of governments to understand and manage technology is increasingly inseparable from the broader question of effective governance. 

My hope is the outline within these texts, when read alongside contemporary AI policy efforts such as the Build American AI initiative, the White House National Policy Framework for Artificial Intelligence, and research on municipal AI readiness, point toward a major shift in the field of public administration. Technology policy is no longer a specialized issue confined to technical agencies or information technology offices. Rather, it is becoming central to democratic governance itself. Public administrators must therefore develop not only traditional competencies in management and policy analysis, but also the institutional, strategic, and ethical capacity to govern in an increasingly technological society. 

Technology as a Question of State Capacity 

Chris Miller’s Chip War provides the broadest strategic context for understanding why technology has become so important to governance. Miller’s central contribution is to show that semiconductors are not simply commercial products; they are a form of strategic infrastructure underpinning economic power, military capability, and technological leadership. Modern economies depend on chips to power everything from smartphones and automobiles to artificial intelligence systems and advanced defense platforms. As a result, semiconductor production and supply chains have become a core arena of geopolitical competition. 

For public administration, the significance of this argument lies in its implications for state capacity. Governments have historically treated infrastructure such as roads, ports, water systems, and electric grids. Now foundational to national development and public welfare. Chip War suggests that advanced technological production now occupies a similarly foundational role. The ability to access and sustain semiconductor capacity is increasingly tied to economic resilience, innovation potential, and national security. 

This insight is especially important because it broadens how public administrators must think about technology. The issue is no longer simply whether agencies possess updated software or modern information systems. Rather, it is whether the state as a whole possesses the institutional and strategic capacity to operate in an environment where technological dependencies shape policy outcomes. In this sense, Miller reframes technology not as a narrow policy area but as an essential component of modern statecraft. 

Institutional Failure and the Administrative Problem 

If Chip War explains why technology matters strategically, Jennifer Pahlka’s Recoding America explains why governments often fail to use it effectively. Pahlka’s analysis is less concerned with geopolitical rivalry than with the ordinary functioning of the administrative state. Her central claim is that many public-sector technology failures are not caused by a lack of ambition or public purpose, but by institutional arrangements that make effective digital implementation difficult. 

In Pahlka’s account, government technology projects frequently fail because they are constrained by outdated procurement systems, fragmented authority, rigid compliance structures, and an overreliance on large external contractors. These institutional features tend to reward procedural caution over practical usability, producing systems that are expensive, slow to deploy, and often poorly matched to the actual needs of citizens and frontline workers. The result is not merely inefficiency, but a deeper disconnect between public purpose and administrative execution. 

This argument is particularly important for public administration because it locates technological failure within the core structures of governance. The problem is not simply that governments need better tools; it is that they often lack organizational forms capable of building, managing, and adapting those tools effectively. Pahlka therefore shifts the debate from innovation in the abstract to institutional design in practice. 

Her proposed solution is equally significant. Rather than continuing to treat technology as a service to be outsourced, governments must cultivate internal technical expertise, embrace iterative design, and build closer working relationships between policy professionals and technologists. For public administrators, this implies that effective governance increasingly depends on the ability to connect administrative processes with digital realities. 

Democratic Governance and Technological Power 

Alexander Karp and Nicholas Zamiska’s The Technological Republic extends this discussion by placing technological development within the larger question of democratic power. Their argument is that democratic societies cannot remain effective, secure, or competitive if the government becomes detached from technological innovation. In an era defined by artificial 

intelligence, advanced computing, and strategic rivalry, the relationship between public institutions and technological development becomes a central political question. What distinguishes The Technological Republic from the other works is its emphasis on the broader constitutional and civic stakes of technological governance. Karp and Zamiska suggest that democratic states must do more than regulate innovation after the fact. They must actively shape the conditions under which innovation occurs, ensuring that technological advancement strengthens rather than undermines democratic institutions. 

This argument carries considerable weight for public administration. Public institutions are not merely neutral managers of social complexity; they are the mechanisms through which democratic societies organize collective action. If governments withdraw from technological development or fail to understand its implications, they risk ceding strategic power to private actors, foreign competitors, or institutional systems that operate beyond meaningful public accountability. 

In this respect, The Technological Republic revives an older tradition of thinking about the state, not as a passive regulator, but as a strategic partner in national development. Its relevance to public administration lies in the reminder that governance requires institutional ambition as well as managerial competence. 

Artificial Intelligence and the Expansion of Governance Responsibilities 

The arguments advanced in these three books are reinforced by the rapid emergence of artificial intelligence as a major policy domain. AI is no longer simply a matter of private-sector innovation or consumer technology. It now occupies a central place in debates over economic growth, infrastructure investment, national defense, labor markets, public service delivery, and democratic accountability. 

Initiatives such as Build American AI reflect this shift by emphasizing the need for coordinated investment in domestic AI research, semiconductor production, computing infrastructure, and workforce development. The underlying premise is that AI leadership will not emerge automatically from market forces alone. It requires intentional public investment and strategic coordination across institutions. 

For public administration, this development is significant because it expands the scope of governance responsibilities. Artificial intelligence touches multiple domains traditionally associated with public management: procurement, workforce training, infrastructure planning, intergovernmental coordination, and public accountability. It also introduces new governance questions concerning transparency, algorithmic bias, privacy, and oversight. In short, AI governance is not reducible to technical regulation. It is a multidimensional administrative challenge that cuts across the core functions of modern government. 

The White House Framework and National Administrative Capacity 

The White House National Policy Framework for Artificial Intelligence further illustrates the extent to which AI is becoming embedded within the machinery of governance. The framework presents artificial intelligence as both a strategic technology and a foundational driver of future economic growth, public service modernization, and national security. It accordingly emphasizes four major priorities: strengthening American AI leadership, building infrastructure and capacity, modernizing government use and procurement, and ensuring responsible and trustworthy AI. 

The first priority, strengthening American AI leadership, underscores the need for sustained federal investment in research, advanced computing, semiconductor production, and strategic collaboration among government, universities, and private industry. This priority reflects the growing recognition that technological leadership is not self-sustaining; it depends on deliberate policy choices and long-term institutional commitment. 

The second priority, building infrastructure and capacity, highlights the material foundations of AI systems. Artificial intelligence depends on data centers, broadband, cloud resources, energy systems, and talent pipelines. In this sense, AI policy is also infrastructure policy. The federal government’s emphasis on physical and digital capacity reinforces the broader lesson of Chip War: technological power rests on concrete systems of production, supply, and support. 

The third priority, modernizing government use and procurement, is particularly relevant to the field of public administration. The framework recognizes that agencies must improve their ability to acquire, govern, and deploy AI tools effectively. Streamlined procurement, clearer guidance, stronger internal expertise, and more agile institutional systems are necessary if AI is to become a useful tool of governance rather than another source of bureaucratic failure. This emphasis closely aligns with Pahlka’s critique in Recoding America: governments cannot modernize merely by declaring technology a priority; they must also reform the institutional processes through which technology is adopted and managed. 

The fourth priority, ensuring responsible and trustworthy AI, points to the ethical and democratic dimensions of technological governance. Transparency, accountability, privacy, fairness, and human oversight are not peripheral concerns. They are central to whether citizens will trust the systems public institutions adopt. As AI becomes more deeply embedded in public decision-making, maintaining public legitimacy will require more than technical efficiency. It will require strong governance safeguards and a continuing commitment to democratic values. Taken together, these priorities show that AI policy is now inseparable from broader 

questions of national administrative capacity. Investments in infrastructure, reforms in procurement, and safeguards for trust and accountability all point toward the same conclusion: governments must modernize institutionally if they expect to govern effectively in an AI-driven environment. 

The Local Dimension: Community AI Readiness 

Although national strategy is essential, the consequences of technological transformation are often felt most directly at the local level. This is where research on community AI readiness becomes especially important. The National Academy of Public Administration’s report Bringing AI to Main Street argues that AI should not be viewed solely as a national competitiveness issue or as a private-sector innovation trend. Rather, its effects will be experienced in communities, where local governments, civic organizations, educational institutions, and regional economies must adapt to technological change. 

The Academy’s central concept is community AI readiness, which it defines as a community’s capacity to adopt, adapt to, and benefit from AI technologies through investments in digital infrastructure, workforce training, education, data governance, and local policy. This concept is especially valuable for public administration because it reframes AI adoption as a question of institutional and civic preparedness, not merely technological availability. Communities do not benefit from artificial intelligence simply because the technology exists. They benefit when public institutions create the conditions that make adoption possible, useful, and equitable. 

This insight adds an important practical layer to the broader arguments advanced in Chip War, Recoding America, and The Technological Republic. If Chip War demonstrates why technological capacity matters strategically, and Recoding America explains why public institutions often struggle to modernize, then the NAPA report shows where much of this challenge will actually unfold: in cities, counties, and regions that must translate abstract technological change into concrete public outcomes. Local government thus becomes not a peripheral actor, but a central arena in which the future of AI governance will be tested. 

The report is also significant because it emphasizes that AI adoption must be approached through iterative design rather than static planning. AI is not a static technology, and therefore the infrastructure, policies, and communications supporting it cannot remain static either. This argument closely parallels Jennifer Pahlka’s critique in Recoding America. Both perspectives suggest that governments will struggle if they continue treating technology adoption as a one-time procurement exercise rather than an ongoing process of adaptation, learning, and redesign. 

Equally important is the Academy’s focus on community engagement and performance measurement. The report recommends public engagement, asset mapping, and regularly updated metrics as tools for identifying readiness gaps, informing decisions, and building trust. For public administration, this reinforces the idea that AI governance must be participatory as well as data-informed. Efficiency alone is not enough; legitimacy also depends on whether communities understand, trust, and help shape the systems being implemented. 

The NAPA report further highlights the extent to which Al governance depends on foundational infrastructure and workforce capacity. Its discussion of broadband, fiber networks, cloud computing, data centers, energy supply, and workforce reskilling makes clear that AI policy is inseparable from broader investments in public capacity. In this respect, the report supports the broader argument of this essay: technological governance is not simply about software or digital tools. It is about whether institutions possess the infrastructure, talent, and organizational systems necessary to convert innovation into public value. 

Finally, the Academy emphasizes that local AI adoption must be grounded in transparency, fairness, accountability, and human-centered decision-making. Its case examples and governance recommendations point to the importance of ethical frameworks, vendor oversight, evaluation processes, and public-facing accountability mechanisms. This is especially significant for public administrators because it makes clear that AI readiness is not merely a technical matter. It is also a matter of democratic legitimacy. Communities that pursue innovation without trust, oversight, or ethical safeguards may improve administrative efficiency while undermining the public values they are meant to serve. 

For these reasons, the concept of community AI readiness adds a vital local and administrative dimension to current debates over technology policy. It reminds scholars and practitioners alike that the future of AI governance will not be determined only in federal strategy documents, research labs, or corporate boardrooms. It will also be determined in the practical work of local institution-building: expanding infrastructure, preparing workers, engaging residents, strengthening data governance, and ensuring that technological change serves the broader public good. 

Implications for the Field of Public Administration 

Taken together, these works suggest that public administration is undergoing a significant transformation. Traditional competencies such as budgeting, personnel management, policy analysis, and program evaluation remain indispensable. However, they are no longer sufficient on their own. The governance challenges associated with semiconductors, digital infrastructure, artificial intelligence, and public-sector modernization require a broader and more technologically informed conception of administrative competence. 

This does not mean that every public administrator must become a technologist. It does mean, however, that future administrators will need to develop a working understanding of digital systems, procurement strategy, infrastructure dependencies, data governance, and the ethical implications of technological deployment. They must be capable of translating between policy goals and technical realities, between public values and institutional design, and between democratic accountability and administrative innovation. 

The NAPA framework reinforces this point by showing that public administrators must increasingly think in terms of readiness, not simply adoption. Readiness includes not only whether institutions can purchase or deploy a system, but whether they have the infrastructure, workforce skills, governance standards, and public legitimacy needed to make that system effective. In this sense, the public administrator of the future is not just a manager of programs, but a builder of institutional capacity in an environment shaped by rapid technological change. Equally important, these works point to the continued value of cross-sector collaboration. 

Many of the most consequential technological advances in American history emerged through partnerships among government, academia, and private industry. That pattern remains relevant today. Effective technological governance will depend not only on what governments do internally, but also on how they structure relationships with researchers, firms, civic organizations, and local communities. In this sense, the public administrator of the future increasingly resembles a strategic integrator. Someone who can navigate institutions, technologies, and democratic values simultaneously. 

Conclusion 

Artificial intelligence and related technologies are reshaping the context in which public institutions operate. They are altering the material foundations of economic growth, the structures of strategic competition, the design of administrative systems, and the expectations citizens place on government. The central lesson of Chip War, Recoding America, The Technological Republic, contemporary AI policy initiatives, and NAPA’s work on community AI readiness is that technology is no longer an auxiliary issue in governance. It is becoming one of the principal means through which governance itself is exercised. 

For the field of public administration, this represents a structural shift. The central challenge is no longer simply whether the government can adopt new tools, but whether public institutions can develop the capacity, flexibility, and ethical discipline necessary to govern technological change in ways consistent with democratic values. Ultimately, governing in the age of artificial intelligence is not just about machines, data, or software. It is about institutional capability. It is about whether democratic governments can adapt quickly enough, intelligently enough, and responsibly enough to remain effective stewards of the public good in a technological age.