How Platform Engineering Enables AI Transformation
It’s hard to overstate how quickly AI is developing, or how many potential use cases have cropped up at every level of government.
It’s also impossible to forecast the regulatory environment and orders coming down the pike. Artificial intelligence and its use cases change fast, and that makes governing its use at a state and local level a moving target. Some states, including California, Connecticut and Virginia, have laws on the books pertaining to AI, but the vast majority do not. Other states, such as South Carolina, have instituted visions for using AI, but even they remain very much in the pre-implementation phase.
Agility and flexibility are critical to holistically addressing AI’s velocity and uncertainty. Platform engineering provides the developer infrastructure needed to get services and applications from a development environment to a production environment quickly and securely. Accelerating delivery cycles helps resource-strapped agencies adopt AI faster, iterate swiftly as new use cases emerge and pivot as the regulatory landscape shifts.
This all culminates in the ability to get high-quality, stable, scalable and secure digital services in front of constituents in a reasonable timeline.
AI is already being used in a wide range of citizen services. Cambridge, Mass., is using it to gather traffic safety data and automatically adjust traffic signals to reduce emissions and accommodate drivers in real time. Colorado, Maryland and Hawaii are using AI and machine learning to serve up relevant employment opportunities to job seekers.
Many more opportunities exist to use AI for citizen services and ultimately make living in a particular jurisdiction a more pleasant experience. Platform engineering provides the technical foundation to fail fast, fail safe, learn faster and ultimately give people more of what they need and want.
DISCOVER: How synthetic data supports state and local government AI initiatives.
How AI Enhances Platform Engineering
AI is changing everything, and that includes internal application development.
A future in which humans are orchestrating AI agents as part of a DevOps workflow cycle is not far off. Coding assistance and AI-based software testing are already realities in large swaths of the private sector, and these could represent huge opportunities for state and local governments.
For example, AI can reduce the resources and costs typically tied to software development and help agencies work toward what I like to call a rapid AI development (RAID) environment. The idea of using AI to help create AI-powered services can feel unsettling, but in practice, it can help development teams get builds into production more efficiently and effectively. Simply put, sanctioning AI tools as part of your development infrastructure can ultimately enhance platform engineering.
Sanctioning is the operative word. Shadow IT, or shadow AI, represents a very real threat within development teams. The last thing agencies want is unsanctioned AI tools introducing new threats or accidentally injecting unwanted General Public License codes into applications.
By its very nature, platform engineering facilitates greater centralization and governance around internal development. Empowering developers with sanctioned AI-tools can enhance their productivity, while the centralizing principles of platform engineering improve how AI’s use is governed among developers. It’s a great example of AI and platform engineering scratching each other’s backs.
EXPLORE: Six ways generative AI will transform government in 2024.
Policies Are Still the Top Priorities
It’s worth noting that there is no substitute for clear, high-level policies around AI within agencies.
Many cities, states and counties are creating AI centers of excellence to develop guidelines around using AI for citizen services. Jurisdictions that have not done so ought to. There is still a lot of distrust and emotion around AI being abused or overreaching, and policies are key to setting boundaries. After all, it takes a long time to build up trust in a new technology such as AI, and almost no time at all to erode it.
AI isn’t going away. It is a fact of life, and in conjunction with policies, agencies need to lay down a foundation of iterative, rapid response to change. Platform engineering isn’t the only way to do this, but it’s the best way.
