Policymaking spans a vast range of domains, including health, education, defense, immigration, national security, the environment, social services, taxation, commerce, housing, and economic and monetary policy. With artificial intelligence and generative AI, policymaking can become more data-driven, transparent, and responsive, ultimately enabling smarter governance.
AI algorithms can sift through mountains of data to identify trends and correlations that could influence policy decisions, help improve the understanding of new policy topics, and ease compliance. AI agents can help improve public consultation processes by automatically analyzing feedback from citizens to help gauge public sentiment accurately. Additionally, these technologies could also help simulate the outcomes of different policy options, enabling policymakers to compare scenarios and make better informed decisions.
But what might these new capabilities mean for government workers in the field of policymaking? Let’s explore this through the example of the policy analyst role. Click through the slides below or download the complete PDF.
As the societal, business, and technological landscape continues to evolve, policymaking is likely to see the creation of entirely new roles to serve emerging needs. One such future position could be the space manufacturing policy specialist, a professional that would be responsible for crafting policies that govern space-based production.
What might this brand-new job look like?
Kelsey, a government space manufacturing policy specialist, is preparing for her meeting with ROCKT, a new space manufacturer looking to use repurposed “space junk,” like an old rocket engine, into new components for space activities. The team at ROCKT is seeking Kelsey's guidance on how to establish their operations and comply with current trade and space regulation requirements. AI agents that are running passively in ROCKT’s systems (as part of their regulated status) have already “pre-met” with Kelsey’s AI agents—sharing notes, data, and generating a compliant, cost-effective, and creative proposal.
Before the meeting, Kelsey reviews the proposal along with detailed notes and a presentation that her AI assistant has prepared for the meeting. With a single voice command, she adds a new data visual to the presentation and inserts a list of outstanding questions for ROCKT.