Pillar 5: Strengthening the Government Workforce

This is the fifth and final blog in a series highlighting key insights from the IBM Center's Special Report, Five Pillars of Effective Government.

The strength of any government lies fundamentally in the capability, dedication, and effectiveness of its workforce. Public servants are the essential infrastructure through which democratic institutions function, policies are implemented, and critical services reach the American people. Yet today's government workforce faces unprecedented complexities: a significant decline in employment since January 2025—and disruptions from prolonged shutdowns that have eroded employee engagement to historic lows. These immediate crises compound longer-term pressures: rapidly evolving technologies, shifting workforce demographics, increasingly complex mission requirements, and growing public expectations for efficient, responsive service delivery.[1] These pressures converge when many personnel systems remain anchored to mid-20th century assumptions about work, careers, and organizational structures.

Interconnected dimensions of workforce modernization involves reimagining the future of work in government, revitalizing hiring processes, modernizing compensation systems, establishing meaningful accountability, driving greater productivity, and developing leadership for a new era. Each dimension presents both challenges and opportunities, and together they form a comprehensive framework for building a government workforce capable of meeting 21st century demands.

The nature of work itself is undergoing significant transformation, and government must adapt or risk falling further behind. Traditional models of work organization—characterized by fixed physical locations, rigid hierarchies, and stable job descriptions—are giving way to more fluid, technology. Research enabled approaches on cloud computing demonstrates how federal agencies have created hybrid ecosystems that distribute data across multiple computing environments, enabling employees to access critical systems from diverse locations—on the ground, afloat at sea, and even in extreme conditions.[2]

This technological infrastructure enables distributed teams that transcend geographic boundaries, allowing agencies to tap talent regardless of location while providing employees with flexibility essential for attracting and retaining skilled workers. Beyond enabling remote work, artificial intelligence and emerging technologies are reshaping what work needs to be done, who can do it, and how it gets accomplished.

Artificial intelligence and emerging technologies are reshaping what work needs to be done, who can do it, and how it gets accomplished. According to IBM Center research, generative AI can transform analytical results into formats that improve explain-ability by converting complicated data into understandable content.[3] These technologies leverage AI not to replace human judgment but to augment it—automating routine tasks, enhancing decision-making with data-driven insights, and freeing skilled professionals to focus on higher-value work requiring creativity, critical thinking, and interpersonal skills. As one expert notes, generative AI "functions as a vital collaborator by offering strengths that complement human abilities."[4]

Yet realizing these benefits requires corresponding investments in workforce development. As organizational roles evolve, “government agencies need to address the ever-growing information technology skills gap in their workforce by reskilling employees."[5] Employees require not just technical training in specific tools, but cultivation of adaptive mindsets and continuous learning capabilities. Research demonstrates that "technology-oriented training programs enable individuals to learn new skills about systems and applications to solve problems in new or evolving organizational roles."[6] Equipping employees with competencies in cloud computing, cybersecurity, data analytics, and AI literacy is no longer optional—these capabilities are becoming foundational to effective public service across virtually all domains.

Perhaps no aspect of government workforce management generates more frustration than the hiring process. The current lengthy hiring process represents a major barrier to attracting talent, confusing applicants who struggle to navigate complex application requirements, hiring managers who lack authority and flexibility to make timely decisions, and even human resources specialists who must interpret countless pages of regulations and agency-specific policies.

Research points to successful examples from agencies and governments that have simplified application processes, leveraged digital platforms, and implemented skills-based hiring practices to address these challenges. Key innovations include simplifying application processes to focus on essential qualifications rather than extensive documentation, leveraging digital platforms to improve candidate experience and accelerating review timelines, and implementing skills-based hiring that emphasizes demonstrable capabilities over traditional credentials.

The shift toward skills-based hiring represents a particularly promising avenue for workforce strengthening. Rather than defaulting to degree requirements that may screen out qualified candidates, agencies can assess generalized competencies—critical thinking, problem-solving, collaboration, communication, adaptability, and resilience—alongside domain-specific expertise. This approach broadens the talent pool, promotes equity and inclusion, and better aligns selection with actual job requirements.

Even when agencies successfully navigate the hiring process, outdated compensation systems represent another critical area where outdated structures undermine workforce effectiveness. The ability to attract and retain skilled professionals increasingly depends on competitive compensation, yet the General Schedule system—which governs pay for most federal employees—was designed in a different era and has not kept pace with 21st century government missions.

Under current systems, most pay increases are awarded primarily for time in service, minimizing the connection between compensation and performance. This position-centric approach, predicated on stable work requirements and predictable career ladders, misaligns with the dynamic reality agencies face: shifting missions, evolving work roles, changing skill requirements, and volatile labor markets.

The challenge is identifying how compensation can be restructured to incentivize quality work, attract top talent, and reward contributions to mission outcomes. Performance-related incentives might link to individual achievements, team results, or departmental progress, reflecting that valuable contributions often result from collaboration rather than isolated individual effort. Research on innovation demonstrates that when agencies have flexibility to reward innovation and results, and when leaders and managers provide pathways for organizations to succeed and work together effectively,[7] they can drive meaningful improvements in service delivery and organizational effectiveness.

However, compensation reform must extend beyond base pay to encompass total rewards. Non-cash benefits increasingly matter to workers: flexible work arrangements, remote and hybrid options, professional development opportunities, and work-life balance initiatives often weigh heavily in employment decisions, particularly for younger workers and those with caregiving responsibilities. Alternative pay systems already exist within government. Some agencies operate under different authorities that permit greater pay flexibility. Comparing outcomes across these systems can reveal strengths and weaknesses, identify best practices, and inform broader reform efforts.

Accountability in the government workforce presents a paradoxical challenge. Government workers often report that poor performers are not dealt with effectively—a perception that signals a problem exists, though its extent is not well-defined. While evidence suggests government workers generally perform well, those who do not often avoid meaningful consequences.

Government can strengthen accountability through three reinforcing approaches: expecting excellence as the norm rather than the exception, establishing clear performance standards linked to mission outcomes, and taking timely action when performance falls short. Performance measurement systems and accountability mechanisms become particularly crucial during periods of workforce change or reduction, when agencies must engage their remaining personnel effectively while maintaining service levels.

Accountability systems must address both ends of the performance spectrum. For high performers, recognition and reward mechanisms should be meaningful and timely, providing incentives for continued excellence and creating models for others. For poor performers, intervention should be swift and constructive, offering support for improvement while establishing clear consequences if standards are not met. The current reality—where both high and low performers receive similar treatment—demoralizes strong employees, enables continued poor performance, and ultimately undermines mission effectiveness.

Beyond hiring, compensating, and holding employees accountable, governments at all levels face resource constraints that demand maximizing productivity from available workforce capacity. This challenge requires thinking about what work truly needs government employees to perform versus what might be accomplished through partnerships with commercial or nonprofit sectors. It necessitates strategic investments in training and development to build and maintain a high-performing workforce.

Research emphasizes that effective technology-oriented training requires transfer of knowledge to actual workplace applications. The government workforce needs proficiency in using modern digital platforms, data analysis tools, and technologies to enhance productivity and engagement. According to IBM Center studies, "effective technology-oriented training involves a transfer of technical, functional, and contextual knowledge to the workplace after training."[8] Organizations must move beyond simply providing training to ensure that newly acquired skills translate into improved job performance and organizational outcomes.

Better integration of government employees with contractors offers one pathway to maintaining capacity and expertise, particularly in rapidly evolving fields like cybersecurity where demand for specialized skills far exceeds supply. However, this approach requires robust contract oversight to ensure effective outcomes, maintain accountability, and protect against inappropriate delegation of inherently governmental functions.

Innovative staffing models provide additional options for maintaining surge capacity and accessing specialized expertise. Programs like FEMA's disaster reserves, the National Guard's dual civilian-military structure, the U.S. Digital Corps for technology talent, and the International Science Reserve demonstrate diverse approaches to supplementing full-time employees with flexible capacity that can be mobilized when needed. Similarly, the Census Bureau, FEMA, and NOAA have demonstrated how agencies can plan for transformed field work by creating systems accessible in diverse and challenging operational environments.[9] These models merit systematic study to understand when and how they work effectively, what costs and benefits they entail, and how they might be adapted across different agency contexts.

The complexity of contemporary government operations and missions demands leadership capabilities that extend well beyond traditional management skills. Leaders must navigate rapid change, orchestrate cross-team and cross-agency collaboration, align diverse stakeholders around common purposes, balance statutory requirements with administrative priorities, shape organizational cultures that attract talent, encourage innovation, and maintain public trust.

Effective government leadership in the 21st century requires balancing competing demands across multiple dimensions: accountability with appropriate risk-taking, institutional stability with necessary change, hierarchical authority with collaborative networks, and immediate operational demands with longer-term preparation. Leaders must be equally comfortable with data analytics and human dynamics, technological systems and interpersonal relationships, strategic planning and adaptive improvisation.

The most effective approaches combine multiple modalities: structured learning to build conceptual frameworks and analytical capabilities; mentorship and coaching to provide personalized guidance and support; rotational assignments to broaden perspective and build networks; and action learning where emerging leaders tackle real organizational challenges under experienced guidance. Research from the IBM Center on Preparing the Next Generation of Federal Leaders demonstrates that leadership capability directly influences organizational capacity to leverage resources effectively and drive meaningful innovation.[10] As one study found, significant federal funding provides leaders with unique opportunities to collaborate and promote innovation,[11] but only when those leaders possess the skills to capitalize on such opportunities.

Among these balancing acts, the emerging technological landscape presents particular leadership challenges. As generative AI becomes more prevalent in government operations, leaders must understand not only the technology's capabilities but also its limitations and ethical implications. Research indicates that "in order to implement generative AI solutions effectively, government agencies must address key questions"[12] about problem-solving applications, data governance frameworks, and scaling strategies. Leaders who can navigate these complex technological, ethical, and operational considerations will be better positioned to guide their organizations through digital transformation while maintaining public trust.

The path forward demands both immediate actions and sustained commitment. Some reforms can begin quickly: simplifying application processes, expanding skills-based hiring, piloting alternative compensation approaches in agencies with existing flexibility, and investing in leadership development. Other changes require longer-term efforts: modernizing HR technology systems, securing legislative authority for pay reform, building robust performance measurement capabilities, and transforming organizational cultures.

Evidence-based research plays a crucial role in this transformation. By identifying what works, understanding why it works, and illuminating pathways for adaptation across different contexts, systematic investigation can guide practical reform efforts. The IBM Center's research portfolio demonstrates the value of systematic inquiry into workforce challenges—from understanding how to reskill employees for technology-oriented roles, to examining how leadership and resources can accelerate innovation, to exploring how emerging technologies like generative AI and cloud computing can enhance government capabilities.

Ultimately, strengthening the government workforce is not an end but rather a means to an essential end: effective governance that serves the American people. Every dimension of workforce modernization—from recruiting outstanding talent to developing adaptive leaders, from incentivizing excellence to driving greater productivity—contributes to government's capacity to fulfill its fundamental obligations. In an era of rapid change and mounting challenges, investing in the government workforce is investing in public service capacity and infrastructure, and ultimately, in the future of effective governance.

Footnotes 

[1] U.S. Bureau of Labor Statistics, The Employment Situation—August 2025, September 5, 2025, accessed December 17, 2025, 3, https://www.bls.gov/news.release/pdf/empsit.pdf.

[2] Amanda Starling Gould, Mobilizing Cloud Computing for Public Service (Washington, DC: The Partnership for Public Service and IBM Center for The Business of Government, 2023), 4, https://www.businessofgovernment.com/sites/default/files/Mobilizing%20Cloud%20Computing%20for%20Public%20Service.pdf.

[3] Alexander Richter, Navigating Generative AI in Government (Washington, D.C.: IBM Center for The Business of Government, 2024), 8, https://www.businessofgovernment.org/sites/default/files/Navigating%20Generative%20AI%20in%20Government.pdf.

[4] Richter, Navigating Generative AI in Government, 8.

[5] Stacie Petter and Laurie Giddens, Reskilling the Workforce with Technology-Oriented Training (Washington, DC: IBM Center for The Business of Government, 2021), 4, https://www.businessofgovernment.org/sites/default/files/Reskilling%20the%20Workforce%20with%20Technology-Oriented%20Training.pdf.

[6] Petter and Gidden, Reskilling the Workforce with Technology-Oriented Training, (Washington, D.C.: IBM Center for The Business of Government, 2021), 9, https://businessofgovernment.org/sites/default/files/Reskilling%20the%20Workforce%20with%20Technology-Oriented%20Training.pdf.

[7] Jane Wiseman, Accelerating Government Innovation with Leadership and Stimulus Funding (Washington, DC: IBM Center for The Business of Government, 2022), 4. https://www.businessofgovernment.org/sites/default/files/Accelerating%20Government%20Innovation%20with%20Leadership%20and%20Stimulus%20Funding.pdf

[8] Petter and Giddens, Reskilling the Workforce, 13.

[9] Amanda Starling Gould, Mobilizing Cloud Computing for Public Service, 8.

[10] Gordon Abner, Jenny Knowles Morrison, James L. Perry, and Bill Valdez, Preparing the Next Generation of Federal Leaders: Agency-Based Leadership Development Programs (Washington, DC: IBM Center for The Business of Government, 2019), 32, https://www.businessofgovernment.org/sites/default/files/Preparing%20the%20Next%20Generation%20of%20Federal%20Leaders.pdf.

[11] Wiseman, Accelerating Government Innovation, 12.

[12] Richter, Navigating Generative AI, 9.