The gen AI mandate for IT

Business teams are no longer just dabbling with ChatGPT prompts—they’re racing to develop and deploy generative AI applications that can deliver bottom-line results.  

No team feels more pressure to keep pace than IT. While it has long been ground zero for tech deployment in the workplace—serving not just as early adopters but technology gatekeepers for all other teams—IT organizations are playing catch-up in terms of operating with a clear mission to support business objectives. 

“IT tends to be inwardly focused, and always has been historically,” says Kenneth Gonzalez, head of analyst relations at Freshworks and a longtime advisor and analyst in the IT technology marketplace. Gen AI applications, he says, could help many IT orgs to “get their head out of the bunker” and take a big step forward.

“Gen AI is making available new tools that can deliver the right set of outcomes for IT, without having to get wrapped up with a lot of internal issues they've been focused on for decades.” The technology, he adds, can accelerate one of IT’s core mandates: ”getting other teams what they need in order to execute their mission-essential tasks.”

With limited budgets and with other teams such as marketing, accounting, and finance deploying their own gen AI apps, IT leaders must think carefully about the best use cases that can yield high-value returns.

A new report from Gartner, for example, identifies 20 use cases for generative AI in IT organizations, ranking each by a range of factors for feasibility and value.

Here are several that landed in each category:

“Likely wins” 

Higher feasibility, higher value

• Code generation

• Budgeting and spend analysis

• Data quality management

“Calculated risks”

Higher value, lower feasibility

• Threat analysis

• Process automation

• Synthetic data

“Marginal gains”

Higher feasibility, lower value

• Policy and document generation

• Code explanation

• Unstructured data processing

While industry type and size of organization are key factors in determining the right use cases to invest in, a number of gen AI applications hold big promise, especially for IT teams aspiring (or being forced) to emerge from “the bunker.” Gonzalez considers several—budget analysis, test case support, and unstructured data processing—as smart plays.

1. Budget and spending analysis

The application: IT teams can use large language models to detect and analyze spending patterns, identify cost-optimization opportunities, and generate personalized budget recommendations. 

The business rationale: IT organizations are not usually known for strategic spending discipline and often resort to what Gonzalez calls “peanut butter spread”: distributing capital and operating expenditures according to the loudest demands. Gen AI could provide IT teams with a full view into operational and support costs and deliver recommendations “that would pass muster with a CFO,” says Gonzalez.

2. Test case generation

The application: In lieu of having IT ops staffers write scripts to verify features and functions of new software (or even use automated scripts), gen AI can write those scripts dynamically and deliver immediate results.

The business rationale: As Gonzalez explains, allowing gen AI to handle test case generation would be “far better, faster, and cheaper” than a traditional labor-intensive manual process. It also gives IT ops teams a valuable tool to reduce risk (and technical debt) “to show that whatever is being implemented is actually functioning properly.

3. Unstructured data processing

The application: The vast majority of all business data is unstructured. Gen AI can analyze and organize unstructured data from myriad sources—including documents, video, audio, meeting minutes, customer interactions, even Internet of Things sensor data—and start making it possible to unlock hidden business value. 

The business rationale: “Many IT teams would like to get their hands on unstructured data and understand what they can do with it so it doesn't stay locked inside of files and file systems,” says Gonzalez. 

While the mandate to generate value for the business is nothing new to IT leaders, it’s also true that we’re two decades into the cloud era and many IT outfits remain stuck in legacy mode. Gen AI, Gonzalez argues, may be the jolt they need to finally step into the future.

“It may be what it takes to burst the bubble and get them to look outside and attend to what's most important.”