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can’t.’ It’s got to be continual.”
Such a solution would require a new data layer that spans countless existing systems and highly automated hand- offs from one system to the next. But it’s not as far-fetched as it might sound,
multiple participants said.
One executive shared how he had
connected 22 systems and used robot- ic process automation to take a busi- ness process from 110 days to “what I publicly said would be 10 days but actually can be as fast as one hour.” RPA extracted and rationalized the data from the legacy systems, allow- ing the new AI-powered process to be spun up while leaving those existing systems in place. “So to me that’s not really blue sky,” he said.
That approach could be applied to a range of other missions. Net- work and user data is already being mined to identify potential risks, but one participant said the process for verifying and sharing threats with the
U.S. Computer Emergency Readiness Team is ripe for automation.
The acquisition process has similar potential, another participant said. “If I can reach into my contract writing data and do an analysis of it, leverag- ing machine learning or RPA, now I can get a range of the terms and con- ditions that exist and the prices paid. I can get an understanding of what I’m buying. That’s very powerful.”
Even basic knowledge manage- ment could benefit, a third participant said. “You can’t secure what you don’t know you have. I have stuff in Google Drive, stuff in my shared drive, my local drive. None of it’s named any- thing. There is no naming convention. How do I make that into a national format so I can say who gets access to that data?”
Regardless of the use case, the group agreed, data is the key compo- nent. “Whether you call it RPA or AI,” one participant said, agencies must
accept that “humans can’t process through the data. If you have five cents to spend, spend it on analytics first.”
Overcoming the obstacles
Pursuing any of those use cases, however, requires more than scrub- bing data and having some dollars to spend. Participants agreed that data governance is crucial, though there was some debate over whether two much or too little poses a bigger risk.
“Honestly, if you don’t have a good governance layer to start that with, someone may turn to techies and fall in love with the tool, but the tool becomes the problem, not the answer,” one executive said. “Figure out what is the information we’re try- ing to protect and how you’re going to try to protect it. And now that I’ve got that, what tools are available to make that work?”
But another participant said start- ing with policy “is a terrible step to
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