AI Strategy for Small Government Contractors
Choose a repeatable task where better retrieval or integration would improve delivery. Define the current baseline, approved information, and a small acceptance test.
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Articles from Sprinklenet on AI governance, AI strategy, enterprise knowledge management, and government contracting.
Choose a repeatable task where better retrieval or integration would improve delivery. Define the current baseline, approved information, and a small acceptance test.
How to evaluate an AI system on invented documents with known correct answers before real records are shared, and what that testing cannot prove.
A sandbox needs an approved data policy, named users, budget limits, restricted tools, and a clear exit path.
Choose one recurring ticket type with a maintained knowledge source and a clear owner.
Consider a policy-research workflow that assembles relevant source passages for a finance reviewer. The reviewer records the applicable guidance, unresolved facts, and decision.
Before building the index, select a representative document set and test extraction, source identifiers, access rules, updates, and removals.
A provider adapter reduces code changes, but it does not make models interchangeable.
For each action, define who may request it, what the reviewer sees, and what the system does after approval or rejection.
Compare the proposed application boundary before the cloud label.
Due diligence should test architecture, security thinking, production experience, and evidence of delivery.
Begin with the tasks users already perform and the decisions they remain responsible for.
A citation should let the reader inspect the passage that supports a claim.
Most weeks I send one short read on enterprise AI: what’s working in real deployments, what’s not, and what I’d do in your seat.
Jamie Thompson, Founder and CEO