Most small business GovCons are already using AI across their business. They are now in the process of attempting to adopt these tools successfully, and successful adoption comes down to two things: RoTs (return on token spend) and security.
Why are these the two primary evaluation drivers?
Tokenmaxxing came and went because the spend far exceeded the output. Token spend should be controlled just like any other budget, and blind AI usage is a great way to destroy your margins.
AI audits will only become more common, and one bad move can cost you an opportunity or damage your business's relationship with an agency.
When looking at how to adopt AI for GovCon capture, there are three options:
Build a process around a frontier model, connecting an LLM to your business systems and creating agents and prompts.
Build your own tool using an AI coding tool (and hiring a software engineer)
Invest in a purpose-built solution that leverages the frontier models but is tailored for finding opportunities, managing GovCon relationships, and generating proposals.
This session breaks down the prompt, build, or buy decision for GovCon BD. We will walk through each option with live demonstrations, from evaluating it to the actual steps of implementing it. Then we will show the likely return of each across the three stages of a government bid: finding, qualifying, and writing. Throughout, we come back to the two questions that decide whether AI is working for you: can you account for where your data goes, and does the spend come back as won work?