Today, generative AI is generating a lot of interest in how it impacts consumer business and applications, however the public sector stands to gain efficiencies in their enterprise operations when applied in the right use cases, according to Google ML, AI and Generative AI Practice Lead, Amina al Sherif.
Al Sherif joined StateScoop’s virtual IT Mod Summit to discuss the impact generative AI has across many areas in IT operations, including streamlining code development, improving data management and accomplishing a variety of other IT operations workflows.
Improving IT operations
Al Sherif emphasized the growing need among organizations to view generative AI through the lens of a “platform revolution,” so from a production perspective it isn’t about building a chat bot, rather you can build a search capability to review all IT documentation or network maps.
“Generative AI is very powerful, and frankly, it’s the biggest strength in the coding realm to automate things that normally would have required a team of Python or Java [developers] to put in the pipeline,” explained al Sherif. She asserts that generative AI can facilitate code development and augment the code review process, so it is ready for production quickly and well-integrated into the rest of the code base.
She cited an example of using generative AI to optimize and review TerraForm by HashiCorp deployments — an infrastructure-as-a-code tool used to manage cloud infrastructure — and its use in pointing out instances of inefficiencies or duplicative resource deployments.
Additionally, generative AI is applicable as a tool to improve areas such as database management, data cleansing, network health checks and automated dashboard creation that have to be done on a daily basis to reflect how the network is performing and sensors are performing.
The ‘data problem’
As a platform approach, generative AI can be designed to perform end-to-end functions and break down data silos as well as communication silos, said Al Sherif, which can help organizations get a better understanding of their data,
“A lot of CIOs, and IT departments by default, deal with the data problem,” according to Al Sherif, which can encompass not knowing where the databases are located, their health status or the status of data cleansing.
She explained that as a platform performing end-to-end functions, generative AI can solve a larger range of operational issues, such as:
- Compressing files automatically when they have not been touched or used in a long time.
- Forming data cleansing pipelines and eliminating (for example but not limited to) instances of nulls and corrupt values.
- Generating daily checklists that IT employees must regularly follow.
- Setting reminders for specialized tasks in security or assurance to make knowledge more accessible and break down communications silos across teams.
Finding appropriate checks and balances
Lastly, Al Sherif encouraged public sector leaders to find a balance between risk aversion and embracing innovation so that they are not falling behind the adoption curve.
“Regulation is going to be needed in both government and education [sectors]…and I think there are very good frameworks put together, and kind of layered on top of that innovation capability, to make sure that innovation is happening in a safe way,” she explained.
“But you need to allow your engineers to grow and experiment with these technologies and avoid doing things like putting total bans on the technology, or even pauses on the technology,” she explained, as a way to retain talented individuals and a younger workforce who are motivated to implement more modern technologies.
You can also join the discussion in Washington, D.C. at the Google Public Sector Forum on October 17, 2023.