The modern public finance workforce: Developing future-ready talent

 

An approaching talent cliff is on a collision course with technology shifts in public-sector finance offices. Across the U.S., retirements are accelerating, and recruitment pipelines are thin, with younger professionals less likely to remain in one organization for long periods. Meanwhile, pressure to provide faster reporting, stronger transparency, and deeper analytics continues to increase in a new era shaped by digital tools and AI-influenced workflows.

For public CFOs and controllers, the challenge is keeping complex financial and operational systems running smoothly with a smaller, more tech-savvy workforce. And AI readiness has become increasingly important even as public sector office leaders face a decline in workers who understand the institution’s history, processes, and legacy systems. This guide from BDO USA explores why public sector finance offices are especially exposed right now and what leaders can do to lower risk, build resilience, and prepare their organizations for the future.

The Talent Cliff in Public Finance

Many finance leaders are seeing the same pattern unfold: A long-tenured controller retires, a grants specialist leaves for the private sector, a payroll manager announces plans to step down after decades in service. Suddenly, tasks that once flowed smoothly become erratic. In many cases, finance departments discover that critical processes live primarily in someone’s memory rather than in documented procedures.

The challenge is demographic as much as operational. A large segment of public finance professionals entered into government service in the 1980s and 1990s. These professionals are now retiring in large numbers, often faster than replacements can be recruited and trained.

At the same time, competition for talent has intensified. Private-sector firms and consulting organizations often offer higher compensation, flexible work arrangements, and faster career mobility. Remote work has expanded the competitive landscape, allowing professionals to work nationally rather than locally. The result is that many governments are competing not just with neighboring jurisdictions, but with diverse employers across the country.

The need for new skills compounds the loss of talented workers with institutional knowledge. Public finance teams will always need people well-versed in traditional accounting and controls. Now, staff must understand AI-supported processes while applying professional judgment to mitigate automation risks.

The implications extend well beyond staffing inconvenience. When experienced staff leave or retire, governments risk:

• Delays in financial reporting and audit completion
• Increased audit findings or compliance challenges
• Weakening internal controls
• Loss of historical knowledge behind funding structures and accounting decisions
• Operational disruption in budgeting, grant management, and treasury functions
• Reduced readiness to evaluate, govern, and adopt AI-assisted finance tools responsibly

The risk is not only today’s disruption but tomorrow’s declining organizational capability.

Finance offices aren’t simply losing employees; they’re losing decades of operational memory and the knowledge base needed to confidently modernize with AI tools.

The Future Skill Profile

Replacing staff is not simply a matter of hiring new accountants. The job itself has changed. Historically, finance professionals were expected to record transactions, establish compliance, and produce accurate reports. Today, modern finance professionals must still master core technical areas like governmental accounting, budgeting, and grant compliance. However, technical competence alone is no longer sufficient. Finance teams are increasingly expected to serve as strategic advisors, translating data into insights that guide policy and operational decisions.

AI considerably raises the bar. As finance functions adopt AI-assisted reconciliations, forecasting tools, workflow automation, and decision-support platforms, public finance leaders need people who can question outputs, understand data limitations, preserve controls, and explain how technology affects financial decisions.

Finance leaders increasingly need staff who can:

Translate Data Into Insight

Leaders and elected officials now expect dashboards, forecasts, and performance analysis, not just historical financial statements. Staff must be comfortable working with data tools, analytics platforms, and AI-generated outputs, while knowing when human review is required.

Communicate Financial Impacts Clearly

Finance teams must explain complex funding, budget, and policy impacts to nonfinancial stakeholders. Communication skills are now as important as technical accuracy, particularly when AI-assisted analysis must be translated into practical decisions.

Manage Projects and Change

Successful management of ERP system implementations, compliance initiatives, grant programs, and AI-enabled workflows requires professionals who can manage project timelines, coordinate with stakeholders, and support organizational change.

Navigate Technology, Automation, and AI Governance

Automation tools, AI-assisted reconciliations, and workflow systems are reshaping routine accounting tasks. Finance staff must understand how to use these tools while maintaining appropriate controls. AI governance guidelines may also cover generating documentation, procedures for review, and segregation of duties.

Understand Operational and Policy Context

Finance increasingly intersects with policy and program decisions. Staff must understand how operational changes affect financial outcomes and where AI or automation may change the timing, quality, or interpretation of financial information.

The professionals who thrive combine accounting knowledge with technology fluency, analytical thinking, and collaborative leadership.

Assessing Workforce Risk

Before solving workforce challenges, finance leaders must understand where vulnerabilities lie. Many organizations are often surprised when they conduct even a basic workforce risk assessment.

Conducting a Talent Gap Analysis

A practical starting point is mapping current staff capabilities against future needs. Leaders should ask:

• Which functions rely heavily on a single individual?
• Where do we lack backup or cross-training?
• Which skills will be critical in five years but are scarce today?
• Which processes are likely candidates for automation or AI assistance?
• Do we have the skills to validate AI outputs, document decisions, and maintain controls?

This exercise often reveals an unexpected concentration of knowledge and a gap between current finance roles and the skills required for future-ready operations.

Identifying Roles Most at Risk

Some roles carry disproportionate operational risk, including:

• Grant compliance specialists
• Enterprise resource planning (ERP) system administrators
• Financial reporting leaders
• Treasury and debt management personnel
• Payroll and benefits specialists
• Data, automation, and AI-enabled reporting owners

If these individuals leave tomorrow, could operations continue smoothly? Could the organization still explain key assumptions, validate system-generated outputs, and maintain audit-ready documentation?

Building Knowledge Transfer Mechanisms

Too often, processes are learned informally and never documented.

Governments should prioritize:

• Documenting key procedures
• Cross-training staff
• Job rotation opportunities
• Standardizing workflows
• Developing transition plans before departures occur
• Documenting data definitions, system dependencies, and review controls for AI-assisted processes

Institutional knowledge must become embedded in systems and processes rather than remaining dependent on individual employees.

Succession Planning as an Ongoing Process

Effective succession planning is continuous. However, succession planning frequently begins only after someone announces retirement. By then, valuable transfer time is already lost. It’s important for finance, human resources, and technology leaders to work together. Workforce planning cannot occur in isolation from hiring policies, career pathways, and compensation frameworks, or the organization’s broader AI and digital strategy.

For public finance leaders, succession planning can include:

• Mentoring relationships that allow emerging professionals to absorb not only technical knowledge but also organizational context.
• Shadowing arrangements that expose staff to responsibilities before transitions occur.
• Rotational assignments that broaden experience and reduce dependency on single individuals. Emerging leaders benefit from exposure to budgeting, reporting, treasury, grants management, and data governance functions.

Succession planning is not about replacing individuals; it is about preserving organizational capability and preparing the next generation of finance talent to work in a more technology-enabled environment.

Recruitment and Retention: Competing Differently

Public sector employers cannot always compete on salary alone. But they can compete in other powerful ways.

Many professionals seek meaningful work, flexibility, and growth opportunities. Governments can strengthen recruitment by emphasizing mission impact: how finance professionals directly support community services and public outcomes.

Flexible and hybrid work arrangements increasingly influence career decisions. Jurisdictions that modernize workplace expectations often expand their talent pools significantly.

The pipeline challenge also creates an opportunity. Instead of trying to fill yesterday’s job descriptions, public finance leaders can recruit for the work finance teams need to perform today: data analysis, systems fluence, technology governance, change management, and the judgment to use AI responsibly.

Partnerships with universities and fellowship programs help introduce students to public finance careers early, before private-sector opportunities dominate their choices. These programs can also highlight emerging career paths that combine public service with technology, data, and analytics.

Retention, meanwhile, depends heavily on development. Professionals stay where they see opportunities to gain experience and advancement. Employees rarely leave only for compensation; they leave when they cannot see their future in the organization or cannot build the skills needed to remain relevant as the work changes.

Building a Learning Culture

Future-ready finance organizations treat learning as part of the job, not an occasional activity. This includes ongoing professional education, technology training, and support for certifications. It also involves encouraging curiosity and innovation rather than rewarding only routine execution.

For AI readiness, learning must be practical and role-based. Finance staff need to understand where AI can support efficiency, where it introduces risk, how outputs should be reviewed, and what controls are needed before AI-assisted processes can be trusted.

Cross-department collaboration helps finance staff better understand operational realities, while operations staff appreciate financial constraints better. Collaboration with IT, HR, legal, and procurement is also essential as finance teams evaluate new tools, vendors, and data-use considerations.

Organizations that invest in learning build adaptability, one of the most valuable capabilities in today’s environment.

Public-sector employers can’t always win on salary, but they can win on purpose, flexibility, growth, and the chance to build future-ready skills in service of the public good.

From Crisis to Capability

The workforce challenge facing public finance is real, but it is also an opportunity. Organizations that approach workforce development strategically can emerge stronger, more resilient, and better equipped to serve their communities. Finance leaders who invest in knowledge transfer, leadership development, recruitment modernization, and continuous learning build teams capable of navigating complexity and change.

The need for AI readiness gives that work new urgency. Public finance departments cannot prepare for AI simply by buying tools. They need people who understand the work, the data, the controls, and the public trust responsibilities that come with managing public resources.

Workforce development is not an administrative task; it is a strategic investment in financial stewardship. The future of public finance depends not only on funding and technology, but on the people entrusted to manage public resources wisely and adapt responsibly as the work evolves.

Public Finance Competency Model

The Public Finance Competency Model is a structured “health check” of your finance team’s capability, continuity risk, and AI readiness.

Use this model to assess your team’s current strengths and priority gaps.

Rate each competency 1-4:

1 = Awareness
2 = Working
3 = Proficient
4 = Expert

Have each team member (or the finance leadership team) rate the listed competencies, then flag any single point of concern where only one person can perform a critical task. Once ratings are complete, focus action where it matters most. For any competency scored 1-2, assign a backup for cross-training, define a short development step (training, shadowing, documented procedure, rotation), and set a target proficiency level by the next budget cycle to strengthen resilience, audit readiness, future-ready capacity, and AI readiness.

1. Technical (Public Finance Core)

• Governmental accounting and reporting (e.g., fund accounting, Governmental Accounting Standards Board implementation)
• Budget development and monitoring
• Grant compliance and reporting requirements
• Internal controls and audit readiness (including documentation)

2. Analytical (Decision Support)

• Data analysis and interpretation (trend/variance drivers)
• Forecasting and scenario modeling (revenues, staffing, capital)
• Performance measurement and KPI design
• Communicating insights through dashboards or concise summaries
• Reviewing and explaining AI-assisted analysis before decisions are made

3. Leadership (Execution and Influence)

• Clear communication with nonfinancial stakeholders
• Cross-functional collaboration (programs, HR, IT, procurement)
• Project management (deadlines, dependencies, stakeholder alignment)
• Change leadership (process redesign, adoption, training)
• Responsible AI adoption and role-based change management

4. Digital (Modern Finance Operations)

• ERP/reporting tool proficiency (queries, workflows, controls awareness)
• Automation awareness (Robotic process automation/AI-assisted reconciliations, workflow tools)
• Data governance basics (data quality, definitions, access discipline)
• Cybersecurity and segregation-of-duties awareness in digital environments
• AI literacy, including prompt awareness, output validation, human review, and documentation expectations

Next step: For any competency rated 1-2, identify (i) a backup person to cross-train, (ii) a short development action, and (iii) a target proficiency level for the next budget cycle. Where AI or automation may affect the competency, also identify the control, documentation, and review expectations required before the process is changed.

This story was produced by BDO USA and reviewed and distributed by Stacker.