Has your organization experienced any impact (direct or indirect) from the executive orders aimed at government spending? Were you able to do anything to plan ahead for this? What precautionary steps should one be taking?
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Yes, a number of our nonprofit customers (members) have lost significant funding via government spending cuts. I do not think anyone expected the speed at which these cuts came. Many were caught off guard. A few tightened up cashflow in advance of DOGE. Most did not. As a diverse industry, membership organization, we have been focusing on supporting those affected through extending membership terms and in some cases, freezing dues until the dust settles and the heavily government funded nonprofits determine their strategy moving forward.
As a precautionary step, we are trying to get ahead of what the next federal government policy action may be and determine how much financial exposure exists on our top line revenue. Expecting a cut in governmental regulations would certainly impact industries that rely on interpreting, advising, consulting and lobbying government agencies for instance.
We do not do a significant amount of business with the US Federal Government but that is understandable as most of the spending cut pressure has been in areas not targeted for review early (like the activities of USAID). My company is taking the stance that what it does is not associated with waste, fraud and abuse.
We have not experienced impact thus far but do discuss potential impacts as we understand the order.
I haven’t seen direct implementation yet, but I’m already planning for how this will reshape expectations across the ecosystem.
These executive orders and OMB memoranda are aimed at federal agencies, yet they clearly signal what is coming for anyone involved in AI, especially in regulated or public-facing environments. The direction is toward governed, explainable, and transparent AI, and I believe that shift will reach private sector expectations quickly.
Here is what I’m preparing to implement:
• Explainable AI frameworks, so systems can show how they reached conclusions, not just what the output is.
• Multi-agent architectures, allowing for modularity, oversight, and separation of responsibilities.
• Human-in-the-loop and human-on-the-loop oversight layers, especially for high-impact use cases where accountability is critical.
Steps I recommend others consider now:
• Identify which AI uses in your organization would qualify as “high-impact” under federal definitions.
• Create clear documentation of human oversight, even if it is informal today.
• Update your internal procurement criteria, because the public sector is shifting toward partners who prioritize transparency, security, and responsible use.
This is not just a government compliance issue, it is a preview of where enterprise AI governance is heading. Acting now means being ready when these expectations become industry standards.