The Evolving Data Landscape In State Governments

With the massive increase in AI, ML, automation, and advanced analytics adoption over the last few years it’s no surprise that state and local governments are paying more attention to these technologies. No longer are governments able to sit idle while technology advances. Instead, government agencies are transforming into data-driven organizations in order to continue to better respond to the rapid advancements and better serve their constituents. One state that is leading the way is North Dakota, investing in building its information technology capabilities to improve the customer experience and enable data-driven decision making.

Ravi Krishnan, Chief Data Officer, State of North Dakota

Ravi Krishnan

At the upcoming AI in Government event on April 21, 2022, Ravi Krishnan, the newly named Chief Data Officer in the State of North Dakota will be joined with CDOs from Maryland and Virginia to share the changing data landscape for state governments.

In this role as North Dakota’s CDO, Ravi pulls from his over two decades of experience in the data management space, having led large transformation efforts in the private sector. His prior experience includes serving as the head of analytics and decisioning transformation at TransUnion, head of data strategy at Discover and consultant to several Fortune 500 companies. In this Forbes interview, Ravi shares his insights into how he’s seeing AI, data, and automation impacting the state.

What are some innovative ways you’re leveraging data and AI to benefit your agency?

Ravi Krishnan: We’re in the early stages of our data transformation journey at the state of North Dakota. This involves putting together a formal data strategy, strengthening the data management organization through hiring, and executing strategic programs. We leverage a mix of on-prem and cloud databases, reporting and advanced analytics tools to add value to state agencies. While much of our focus is on descriptive and exploratory statistics, we’re also looking to provide data-driven predictive analytics services to meet customer needs.

How are you leveraging automation at all to help on your journey to AI?

Ravi Krishnan: We’re investing in Robotic Process Automation (RPA) and have identified a list of business processes which could benefit from reduced manual intervention. We’re hoping to expand our pilot programs to improve business outcomes and increase productivity across the state.

How do you identify which problem area(s) to start with for your automation and cognitive technology projects?

Ravi Krishnan: The most important criteria is business impact, defined both in terms of costs and time saved. Closely following that is the availability of subject matter experts who can help map business processes and work with the technology teams to implement. Getting commitment from people is a big challenge because we have state business to run at the same time. Finally, we want to make sure that we have a good mix of different state agencies we work with so that ideas can be cross pollinated, and synergies can be accomplished across processes that touch more than one agency.

What are some of the unique opportunities the public sector has when it comes to data and AI?

Ravi Krishnan: The public sector is a treasure chest of data that can be leveraged for good. Imagine having all the individual and business level data of the state available for analytics! While the private sector has cost pressure and is constantly looking to monetize user data through anonymization and sales, the public sector does not have these limitations. In a former life in the private sector, I was exposed to areas such as marketing analytics, usage-based insurance, and credit predictions. Each of these depended on purchasing third-party data to validate things like addresses, phone numbers etc. which is often very expensive. Part of the reason is that consumers don’t always provide private enterprises with their latest data. When they interact with us for government services, they do provide their data more frequently and I’d argue more accurately. An example is annual vehicle registration where identifying data is captured.

What are some use cases you can share where you successfully have applied AI?

Ravi Krishnan: While we haven’t yet had a formal AI implementation, we’re close to making AI capabilities available on our cloud platform. One of the first use cases we’d look to implement would revolve around predicting student learning outcomes based on a range of data we have access to as part of our programs. There are also large programs in the pipeline related to health services, autonomous systems (drones) and the department of transportation. Each of these will need to be evaluated for use cases and could benefit from smart use of AI services.

Can you share some of the challenges when it comes to AI and ML in the public sector?

Ravi Krishnan: There are a couple of areas. One is around the concept of data literacy and bringing awareness of all the possibilities with AI/ML to our agencies. Often opportunities are missed because of dots not having been connected during project scoping. We are instituting formal training programs for data literacy to address this challenge. The other challenge is hiring and retaining talent. The public sector attracts people that are motivated by the ability to make an impact. We would like to hire those that are interested in making the world a better place and give them a great technology environment to work in.

How do analytics, automation, and AI work together at your agency?

Ravi Krishnan: As discussed previously, we’re in the process of redefining how we organize data management work to bring value to the state. North Dakota's data division is also unique in that we have a large group of developers who develop and maintain a suite of applications for state agencies. We’re exploring synergies between application development, data management, automation, and AI/ML. While we have a lot of business as usual (BAU) tasks we’re preparing to get these domains more tightly connected.

How are you navigating privacy, trust, and security concerns around the use of AI?

Ravi Krishnan: Great question! We were recently in conversations with our state senators who expressed their concerns around ensuring ethical use of AI technologies. While we’re still in the early stages of our journey we need to invest the time and energy to create data governance policies that will address many of the common pitfalls in this area. The other thing to keep in mind is the legal aspect of combining data from different agencies, which isn’t always very easy to overcome. Responsible use of AI (or AI for good) has tremendous potential within state government, and we’ll take the time to do it right.

What are you doing to develop an AI ready workforce?

Ravi Krishnan: We have a highly engaged technology workforce that is always interested in learning and growing. Several of our employees have spent their entire careers here and yet have the drive and enthusiasm for continuous development. Over time we’d like to help more of our staff transition into areas such as data science, automation, and cloud through formal training, certification, and mentorship programs. Part of our transformation will modernize most of our legacy applications with some remaining on-premises and others moving to the cloud. All these transformation efforts will require a future-ready workforce that is trained and ready for what lies ahead!

What AI technologies are you most looking forward to in the coming years?

Ravi Krishnan: Computer vision is one that I think has great applicability to state government. Many of our documents could easily be safely digitized, stored and available for search. While guidelines will need to be developed in this area, computer vision holds great promise in the areas of law enforcement, image and text recognition, finance, autonomous vehicles, and geospatial systems. NLP is another area that we could exploit for better customer experiences through intelligent chatbots and interactive voice responses.

I remember taking a class on AI in the late 90’s and learned a programming language called LISP. Little did I know that the world would be revolving around advancements in this field!

Ravi Krishnan, CDO of North Dakota, will be sharing additional insights along with other state CDOs including Patrick McLoughlin, CDO of Maryland, and Marcus Thorton, Interim CDO of Virginia, at the upcoming AI in Government event on April 21, 2022.