The Public Sector Is Behind in Its AI Knowledge. Here’s Why That Needs to Change
Eleanor Hecks is a senior HR and business writer at Designerly Magazine. After growing up with parents who both worked in the public sector, Eleanor is passionate about specifically applying her insights to those in the government and education professions. You can connect with her on LinkedIn or follow Designerly on X for business and design insights.
The public and private sectors have different foundational expectations for artificial intelligence (AI) knowledge. Many secrets are behind closed, proprietary doors. Meanwhile, public-facing enterprises responsible for educating the populace could use more details. Why is this happening, and what can the public sector do to change it?
Why Has the Public Sector Fallen Behind?
Public sector companies and agencies in health care, transportation, education and beyond must gain AI literacy. However, they lag for systemic, financial and practical reasons.
Money
Budget constraints are one of the most notable. Private businesses have consistent funding sources, whereas public bodies have to rally harder for financial support. Private corporations don’t have to deal with AI’s political undercurrent or public perception influencing how much time and resources go into AI training and development.
In contrast, the public sector must rely on its constituents to undergo innovation. Even though incorporating AI would save money by reducing immigration backlogs or optimizing tax policies, many are still slow to adopt.
Slowness in Innovation
The public sector is highly risk-averse because adopting new tech signifies change. Bureaucratic systems, administrative teams and stakeholders may resist implementing something new when the old ways are effective.
Even if these systems did implement AI, lengthy timelines to approve and incorporate AI systems could take months or years, depending on the sector. It is why AI knowledge is slow to trickle into the public sector. If the desire to install it isn’t unanimous, the community loses time gaining exposure to it.
Expertise Gaps
Finances and mindset are a few reasons why corporations and rising professionals lack AI education. AI is a novel tool requiring skills nobody has used before. If banks, hospitals or schools aren’t interacting with AI systems, they won’t shepherd responsible AI stewardship to upcoming generations of thinkers and workers.
Data Silos
The public sector also suffers because of its legacy systems. If a nonprofit still relies on decades-old hardware, it won’t be able to deploy AI seamlessly. A related problem is the depth of the public sector’s data silos.
Public data is inaccessible and inconsistent. An algorithm works best with high data integrity and density. With so many of the public sector’s resources on paper and in legacy equipment, it would take years of dedicated effort to translate that into a format an AI could use.
AI knowledge must penetrate communities deeper than it currently does if society wants to leverage it for good.
ELEANOR HECKS
Why Change Is Necessary
When used responsibly, AI could provide countless advantages for society. The public sector could democratize and normalize it by promoting useful interactivity and accountability. They need to do this because public services need improvements.
AI tools could rapidly check in patients coming into the emergency room or urgent care, reducing wait times. A generative AI kiosk at the door to a city hall could listen to a person’s query and point them to the right office and contact for their unique problem, saving them time from wandering around the halls.
These tools also align with most people’s desires to use AI versus employ traditional avenues — for example, nearly 90% of users would rather use a chatbot than have to take the time to fill out a form. The attentiveness to user preferences develops a positive relationship with citizens, increasing their trust in public services.
The longer an AI model operates, the more it knows how to help its community. It could gather information about constituents and help city councils and stakeholders make data-driven decisions. The model could influence upcoming policies to be more comprehensive to people’s needs and even allocate resources during an emergency.
How to Get There
The lack of AI governance is an overarching concern, and it could be a leading reason why it’s not more widespread. Only 52% of public sector entities in a survey claimed to have a generative AI policy in place, which doesn’t even include other AI forms. Therefore, the best way to spread AI and increase knowledge is to make it policy-driven.
Expanded education and training will flourish, especially if government funding is backing it. These resources will upskill the workforce and create aspiring AI thought leaders in public spaces. They could also influence school curricula, inspiring students to study data science or AI model engineering.
Legislative action will also encourage more profound collaborations between communities, private companies and the public sector. Joining forces is crucial for ensuring everyone’s values and priorities are consistent, particularly with volatile and ever-changing technology like AI.
AI’s Impact on the Public Sector
AI knowledge must penetrate communities deeper than it currently does if society wants to leverage it for good. The technology will only have an optimal impact if skilled minds operate the systems, and the public sector must go out of its way to learn and apply it mindfully and creatively. When it does, people’s relationships with AI will change into something more productive and positive.
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