When introducing AI automation in government, directly address job security fears. Frame AI not as a replacement, but as a partner that reduces overwhelming workloads and enables better service. Emphasize that adopting these new tools requires reskilling, shifting the focus to workforce evolution, not elimination.
In siloed government environments, pushing for change fails. The effective strategy is to involve agency leaders directly in the process. By presenting data, establishing a common goal (serving the citizen), and giving them a voice in what gets built, they transition from roadblocks to champions.
In government, digital services are often viewed as IT projects delivered by contractors. A CPO's primary challenge is instilling a culture of product thinking: focusing on customer value, business outcomes, user research, and KPIs, often starting from a point of zero.
In the public sector, the goal is not to outcompete rivals but to improve service delivery. A government CPO's version of competitive research involves talking to counterparts in other states, partnering with civic tech organizations, and learning from innovative vendors to understand best practices.
Unlike many private sector roles, a state CPO serves two distinct customer bases. They build B2C digital services directly for constituents while also developing a B2B platform-as-a-service to be adopted by other state agencies, requiring separate strategies for product marketing and adoption.
Unlike private sector products that target specific demographics, government digital services must cater to an extremely diverse user base, including people with low income, no permanent address, and vast age differences. This necessitates a rigorous, non-assumptive approach to user research and accessibility from the outset.
To navigate the high stakes of public sector AI, classify initiatives into low, medium, and high risk. Begin with 'low-hanging fruit' like automating internal backend processes that don't directly face the public. This builds momentum and internal trust before tackling high-risk, citizen-facing applications.