Six Concrete Ways to Make Government More Data-Centric

However, the term “data-centric” is incredibly broad and is much easier to consider in theory than to put into practice. Emerging technologies, like generative artificial intelligence (AI), have only made this challenge more complicated as AI and its capability for decision making relies heavily on underlying data. How are governments supposed to think about the impacts of AI if they don’t even know where to start with data?

Governments already face barriers to becoming data-centric, including budgetary constraints, difficulties in upgrading legacy infrastructure and meeting legal data privacy and national security requirements. But lack of clarity on how to get started shouldn’t be an additional obstacle. Understanding how to take the first steps can help overcome these barriers and empower governments to be more forward-thinking when it comes to data integration. Here are six concrete ways governments can become more data-centric, both immediately and in the long term:

1. Align your leadership with your AI and data strategy and vision: Having a clearly defined vision for your AI and data strategy is critical in achieving your ambition and measuring success. New projects or initiatives, especially in government, tend to be executed by specialized experts. However, it’s essential for central decision-makers to also understand the broader vision.
2. Build a strong technology foundation that can adapt to a changing regulatory environment: If an organization does not have a strong foundation of technology infrastructure, the execution of any data goal will fall short. It is imperative for governments to have a solid technology foundation, especially as the public sector is already perceived as lagging behind the private sector in technological advancements. Building this foundation includes performing an inventory of weaknesses and priorities in using data, updating legacy systems, digitizing systems to allow for interoperability and ensuring that major technology integration is compliant with the latest standards.
3. Create systems and programs that support staff AI adoption and proficiency: Technology is a crucial enabler of citizen centricity, but governments cannot provide effective services without a skilled and empowered digital workforce. Oftentimes with digital tools, governments adopt technologies that are agency-specific, and leaders don’t always implement the introduction of new tech with a program to support their staff. Governments must fill these gaps by hiring relevant digital experts in addition to upskilling and reskilling talent and deploying programs that support technology adoption across departments.
4. Create and activate a plan with the long-term goals for your data strategy: During the pandemic, governments became increasingly reliant on technology for many of their public service processes and programs. Despite the large amount of data collected, many governments have failed to utilize this information to its full potential. A few years later, some governments have still not moved forward with digitizing their systems, while others have reverted back to paper and in-person-only structures. That is why having long-term goals, closely tied to a clear business case, is essential. When the momentum around the initiatives begins to fade, the structure does not, and government leaders will continue to push the effort to digitize.
5. Bolster public confidence and trust regarding the use of data and AI: The conversation around privacy is always at the forefront when discussing the collection of data and the possibilities of AI. For any data-driven product or service to be successful, its users need to be confident that their privacy is being protected. This is especially acute in a government setting. By explaining how data will be collected, stored and used, citizens will feel more confident in their government’s use of technology and more open to seeing the benefits of its digital transformation.
6. Encourage continual innovation to help embed change across your teams: Once a government has successfully created a system that can use data and AI automation to help with services, it is important to update these systems and skills constantly. Not only because outdated digital information can be vulnerable to cybercrime, but also because digital transformation tends to inspire change and new innovative ideas that can bring impactful value to citizens.

These actions are essential, but not a complete recipe for governments who are on a mission to become more data-centric. There is no one way into data centricity, no silver bullet to ensure success, but there is a wrong method: Not doing it at all. If governments don’t invest in digital transformation, they will lag behind the private sector and be confined to reacting to events rather than having proactive solutions already in place.

The views reflected in this article are the views of the author and do not necessarily reflect the views of the global EY organization or its member firms.