Nonprofit builds routing system for approved AI
“Simply blocking AI tools is not a sustainable solution,” says Boris Kolev, global head of technology at JA Worldwide, a global educational nonprofit with almost 5,000 employees that serves more than 20 million people a year.
For JA Worldwide in particular, the problem was exacerbated by the fact that there was no approved solution until three months ago. As a result, employees got into the habit of using personal AI platforms.
“It was totally uncontrolled,” Kolev says. “Everyone who wanted to explore AI was using public models.”
At the beginning, people didn’t worry about what they shared and uploaded. “We tried to implement some policies, like ‘don’t upload corporate information.’ But it was hard to know what people were doing.”
Plus, AI was being embedded everywhere. On Windows. In people’s phones. “A user cannot avoid it,” says Kolev.
Then, earlier this year, the organization built a routing system, with enterprise-safe versions of Claude and ChatGPT running in private environments on AWS and Azure, in addition to some open-source models.
“Our colleagues can choose which model to use,” he says. “And sometimes they do a prompt two different times and choose which one works better.”
The system went into production in June, after a couple of months of testing and development.
“Now, after all the policies and rules are implemented, we have our own closed AI system, hosted on our own servers, so no risk of leaking corporate data,” he says. “But still, some projects are using public models, and we are trying to solve this problem.”
Another hitch: individual employees were often invested in the personal AI tools they’d grown comfortable with and reluctant to change to the corporate tools.
“Employees were saying, ‘I have so much history. It knows me, I cannot just switch,’” Kolev says.
And employees still have all the AI tools that come with their devices.
“This is hard to manage, and it’s getting even harder,” he says. There are monitoring and blocking tools available, but they’re too expensive. “We’re a nonprofit, and for us it’s almost impossible to afford monitoring tools. So we do a lot of educational sessions.”
The organization is also trying to make the sanctioned tools more appealing. That includes a mechanism to import the history and context from other platforms, he says. “And we’re trying to convince them that our tool works better and has more functionality, so we’re adding MCPs.”
MCP — model context protocol — allows an AI system to access data and tools directly. That includes connecting to corporate email and calendars, SharePoint, Monday.com, CRM, and all the other software that employees use for work, he says.
Kolev says that it’s a mistake to assume that employees use shadow AI because they don’t respect IT policies. It’s because IT didn’t move quickly enough to meet their needs.
“They find the AI faster than you can produce tools and governance and rules,” he says. “So my advice is that you start with simple rules that employees can understand, provide sanctioned tools, and continuously adapt governance.”
Holding employees accountable
According to an April survey of more than 1,200 employees conducted by Wakefield Research on behalf of PagerDuty, 66% of employees have used unsanctioned AI tools — and of those, 48% faced formal consequences, such as a warning or disciplinary action.
Holding people accountable is critical to a successful AI use policy, says Carnegie Mellon’s Butkovic. “We have to speak definitely about this in organizations,” he says. “If this behavior cannot be tolerated, then it shouldn’t be tolerated.”
Allowing the use of unsanctioned AI doesn’t just create risks but also opens up an organization to legal liability if the AI agents, acting on behalf of employees, harmed other companies or individuals.
“There could be consequential actions,” he says. Even if the employee responsible gets fired, “external parties that have been affected are still going to sue the company.”
The organization needs to be able to show that it has policies in place and enforces them when employees deliberately circumvent the policies.
“If you as an employee make a good-faith effort to comply with the policy, we’ll show you latitude if you’re not malicious,” Butkovic says. “But if you’re actively circumventing the system of controls in your organizations, that’s the case where there have to be swift and profound consequences.”