The Blind Spot
In recent years, federal, state and local governments have launched a wave of initiatives to manage artificial intelligence (AI) responsibly. New memorandums from the White House Office of Management and Budget, the NIST AI Risk Management Framework, and agency-specific strategies all stress governance, transparency and accountability. Yet while leaders debate enterprise frameworks and oversight councils, AI is often entering agencies through a far less visible door: shadow procurement.
This problem doesn’t look like traditional shadow IT. Instead, it takes the form of a program manager buying AI-powered SaaS with a purchase card, a team expensing pilot credits from a major cloud provider or a contractor spinning up an unreviewed chatbot under the umbrella of a larger task order. Because these transactions are small, often well below procurement review thresholds, they evade normal acquisition oversight and security vetting.
But small does not mean safe. Even a single unvetted tool can touch sensitive data, introduce bias or set precedents that ripple across entire workflows. Shadow procurement quietly shapes how mission-critical systems evolve, often without enterprise knowledge or alignment.
Why It Matters
Risk concentration. AI systems can process sensitive health, financial or security data. If unvetted tools are used, data could leak through vendor models, third-party integrations or insecure cloud instances. What appears to be a minor pilot can become a major exposure if it handles personally identifiable information (PII) or mission-sensitive content.
Compliance exposure. Procurement laws, Section 508 accessibility requirements and privacy regulations are designed to ensure fairness, equity and protection. Shadow procurement bypasses these safeguards. A chatbot that fails accessibility standards, for instance, can exclude people with disabilities while still shaping citizen services.
Strategic misalignment. When teams procure their own AI tools independently, the result is duplication, fragmentation and wasted investment. These tools often fail to integrate with enterprise systems or run counter to agency-wide architecture. What starts as local innovation can quickly erode strategic coherence and create silos that are costly to unwind.
For executives, the challenge is not just technical, it’s reputational. If oversight bodies, the media or citizens discover that AI tools were adopted without review, leaders risk losing credibility. In today’s environment, where trust is already fragile, even the appearance of lax governance can have outsized consequences.
Real-World Signals
The risks of shadow procurement are not hypothetical. In 2023, a state agency discovered that employees were using unapproved generative AI tools to summarize case files. The tools worked well enough for early drafts, but they also exposed sensitive client data to third-party servers. What began as a small, well-intentioned experiment triggered an expensive investigation and retraining program.
Meanwhile, in the federal space, OMB’s M-25-22: Driving Efficient Acquisition of Artificial Intelligence in Government acknowledges the need for better AI acquisition practices, yet micro-purchases still largely fly under the radar. Without clear guardrails, these purchases accumulate into what amounts to a hidden AI portfolio.
Globally, regulators are beginning to anticipate this problem. The EU AI Act requires lifecycle documentation, monitoring, and oversight for AI systems, regardless of scale. This signals that micro-purchases won’t remain invisible forever, compliance obligations will eventually extend to them.
Executive Moves for the Next 90 Days
Closing this gap does not require halting innovation. It requires visibility, guardrails, and rapid but responsible clearance.
- Inventory micro-AI spend. Direct finance and acquisition teams to run expense, grant and P-card data against a list of known AI vendors. This creates a baseline of where AI is already entering the organization informally.
- Define guardrails. Establish a “safe list” of pre-cleared tools that can be used for low-risk experimentation, alongside prohibited categories (such as tools that process sensitive data without encryption). Clear red and green zones make decision-making easier for frontline staff.
- Launch rapid clearance. Agencies should stand up a fast-track lane for small pilots. A two-day review process with lightweight contracts allows innovation to continue while ensuring that critical security and compliance checks occur.
- Engage consulting partners. Consulting firms can help build dashboards that merge finance, acquisition, and security feeds to expose shadow spend. They can also create training modules for program managers, showing how to align small purchases with enterprise policy.
Building a Culture of Responsible Experimentation
Shadow procurement is, at its heart, a symptom of a deeper cultural tension: the need for speed versus the need for control. Program managers turn to micro-purchases because they want to move quickly and test tools without waiting months for approval. This instinct is not wrong, agencies need experimentation to stay relevant.
The solution is not to punish or restrict innovators but to give them safe pathways. Leaders should communicate that innovation is welcome, but it must occur within defined lanes that protect data, equity, and compliance. A culture that rewards responsible experimentation will reduce the temptation to bypass processes altogether.
Conclusion
Shadow procurement isn’t just a finance issue, it’s an enterprise resilience risk. Every unvetted purchase adds complexity, increases exposure, and chips away at alignment. But with deliberate steps, from inventorying spend to launching rapid clearance processes, agencies can turn a hidden liability into a managed asset.
Consulting firms are uniquely positioned to help by designing cross-functional dashboards, creating pre-clearance frameworks and embedding best practices across acquisition and security functions. Agencies that move now will not only prevent compliance surprises but also foster a healthier balance between innovation and oversight.
In the AI era, resilience is not just about what you buy, but how you buy it, and whether the enterprise is prepared to own the consequences.
Dr. Rhonda Farrell is a transformation advisor with decades of experience driving impactful change and strategic growth for DoD, IC, Joint, and commercial agencies and organizations. She has a robust background in digital transformation, organizational development, and process improvement, offering a unique perspective that combines technical expertise with a deep understanding of business dynamics. As a strategy and innovation leader, she aligns with CIO, CTO, CDO, CISO, and Chief of Staff initiatives to identify strategic gaps, realign missions, and re-engineer organizations. Based in Baltimore and a proud US Marine Corps veteran, she brings a disciplined, resilient, and mission-focused approach to her work, enabling organizations to pivot and innovate successfully.
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