As artificial intelligence becomes integral to government, leaders must cultivate a new set of skills and competencies within their teams. This guide goes over how focusing on individual capabilities like data literacy, critical thinking, and ethical reasoning can empower employees to work effectively with AI. At the same time, leaders must develop integrated competencies such as strategic foresight and trustworthy AI oversight to guide responsible adoption and build a culture of continuous learning.
This lesson is a preview from Graduate School USA's AI for Government Leadership & Management course.
The rise of artificial intelligence in government is reshaping not just how agencies operate, but also the very skills and competencies required of public servants. Leading in this new environment is less about being a technical expert and more about fostering a new workforce mindset. To successfully navigate this transformation, government leaders must cultivate a blend of individual skills and integrated leadership behaviors that empower teams to use AI responsibly and effectively.
Preparing your workforce for an AI-rich future involves more than just implementing new software. It requires a deliberate investment in human capabilities. By focusing on developing data literacy, critical thinking, and ethical reasoning, leaders can build teams that are agile, insightful, and prepared to uphold public trust. This article explores the essential skills and competencies that will define the next generation of government leadership.
Essential Individual Skills for the AI Era
Before leaders can develop broad organizational competencies, they must ensure their teams possess the fundamental skills needed to work alongside AI. These individual capabilities are the building blocks of an AI-ready workforce.
Data Literacy
In a data-driven environment, the ability to understand, question, and interpret data outputs is crucial. Data literacy is not just about reading dashboards; it’s about comprehending how AI models generate their outputs and recognizing when data might be biased or incomplete. A data-literate employee can look at an AI-generated report and ask intelligent questions about its conclusions, ensuring that decisions are based on sound information.
Critical Thinking
AI can provide powerful recommendations, but it lacks real-world context and judgment. Critical thinking is the skill of applying structured reasoning to assess those recommendations and challenge their underlying assumptions. A public servant with strong critical thinking skills will naturally ask, "What data supports this prediction?" or "Does this conclusion make sense in our specific situation?" This human-centric evaluation is a vital safeguard against over-reliance on automated systems.
Change Agility
The world of AI is constantly evolving, and government agencies must be able to adapt quickly. Change agility is the comfort level with rapid adaptation and continuous learning in a dynamic digital landscape. This skill manifests in employees who are open to implementing new AI-powered workflows, iterating on policy guidance as technology changes, and effectively communicating uncertainty to stakeholders.
Ethical Reasoning
The use of AI in government carries significant ethical weight. Ethical reasoning is the ability to apply principles of fairness, accountability, transparency, and privacy to decisions. Before implementing an automated system, an employee with this skill will evaluate potential harms, privacy tradeoffs, and equity impacts. This proactive ethical consideration is fundamental to maintaining public trust and ensuring AI serves the community equitably.
Integrated Leadership Competencies for AI Governance
Beyond individual skills, effective AI leadership requires integrated competencies that shape organizational culture and strategy. These behaviors translate individual capabilities into a cohesive approach to AI governance and oversight.
Strategic Foresight
A forward-thinking leader must anticipate how AI and automation will reshape their agency's mission, workforce roles, and policies over the long term. This competency, which aligns with OPM’s Future-Focused Mindset, involves looking beyond immediate applications to plan for future challenges and opportunities. Strategic foresight allows leaders to proactively design the workforce and systems needed for tomorrow.
Governance & Risk Management
As agencies adopt AI, they need structures and policies to ensure its safe and responsible deployment. The competency of governance and risk management involves establishing oversight bodies, like an AI Governance Board, and creating clear policies for AI use. This reflects requirements found in OMB M-24-10 and the NIST AI Risk Management Framework, ensuring that innovation happens within a secure and accountable structure.
Digital Collaboration & Communication
AI solutions often require collaboration across technical, policy, and operational teams. Leaders must be able to work effectively across these boundaries, translating complex AI insights for non-technical audiences. This competency is essential for building consensus, securing buy-in from diverse stakeholders, and ensuring everyone understands the purpose and function of new AI tools.
Trustworthy AI Oversight
Building on the principles of ethical reasoning, this competency involves creating practical systems for transparency and accountability. Leaders must implement human-in-the-loop review processes and ensure that AI systems can be audited. This commitment to trustworthy oversight, drawn from guidance like EO 14110, proves to the public and to employees that AI is being used as a tool for empowerment, not surveillance.
Fostering a Culture of Continuous Learning
The skills and competencies for the AI era are not static. Technology will continue to evolve, and so must the workforce. The final and perhaps most crucial leadership competency is fostering Continuous Learning & Curiosity. Leaders must champion an environment where employees are encouraged to pursue ongoing development in emerging technologies, ethics, and policy.
Start by offering training that builds foundational data literacy and critical thinking skills. Encourage teams to experiment with approved AI tools in low-risk scenarios. Create forums for employees to share what they’ve learned and discuss the challenges they face. By modeling curiosity and a commitment to lifelong learning, you can build a resilient, adaptable, and innovative workforce ready to meet the future.
