Stop Searching for Government Contracting Opportunities

Since 2023, I’ve trained people in various ways to use AI in their work.

But one of the most sought-after topics is “How do I find opportunities faster?”

I’ve taught people how to use procurement and funding websites to find government contracts, grants, and other opportunities.

The range includes small business owners, educational institutions, capture and proposal professionals, growth teams, and government contractors, with revenue ranging from pre-revenue to hundreds of millions of dollars.

The organizations may look very different, but I keep seeing the same problem.

A lot of the work is still manual.

Someone searches SAM.gov. Someone reviews the results. Someone tries to determine whether an opportunity is a fit. Someone researches it. Someone decides whether it is worth pursuing.

Organizations with dedicated teams, technology, and AI tools get stuck doing things the way they have always done them.

I know because my approach has evolved.

When I first started teaching this in 2023, the technology wasn't where it is today.

One approach I used was to download the CSV file containing active SAM.gov opportunities and treat it almost like a database.

We could create search criteria, filter the data, identify potential matches, and build infrastructure around that process.

As I experimented with different approaches. I built Custom GPTs and Projects that could do more of the work for you.

But that introduced another constraint: the data and the knowledge were less flexible and portable.

I realized my approach was flawed.

Finding and qualifying opportunities isn't one job.

There are multiple jobs hiding inside that process.

I started down the path of building a web app called AI Scout, built to identify the best contracting and grants listings to pursue.

Today, I approach the problem differently. I work with an AI team.

This is the mindset shift.

You aren't trying to automate a few searches.

You're building infrastructure that combines human and non-human workers to generate revenue.

Maybe your objective is to win a certain number of contracts.

Maybe you want to enter a new market.

Maybe you want to find recompetes.

Maybe you're targeting specific agencies, contract vehicles, capabilities, customers, or types of work.

Once you know the outcome, you can determine what work needs to be done to achieve it.

That's where AI Team becomes useful.

If you don't have the budget to hire all the people you need or can't find enough people to create the velocity you need, the question becomes:

How can I create the capacity required to reach my desired result?

I operate eight AI Teams with 45 Digital Employees internally.

I've learned to think about each Digital Employee much like someone I'm bringing into the company.

That helps prevent over-engineering.

You don't need to sit down and build one enormous automation that handles your entire capture process.

Break the work into jobs.

Then build the infrastructure around those jobs.

Your original process may be simple.

A human employee's job doesn't remain the same forever.

They learn. They gain expertise. You give them new responsibilities. Your business changes. New requirements appear.

Your AI infrastructure should evolve the same way.

Whether you're doing this for yourself, integrating AI into your organization's capture work, building the capability internally, or learning how to provide this as a service to someone else, the foundation is the same.

Here is a seven-step system you can use to get started.

Don't start with SAM.gov.

Start with your business.

What kinds of opportunities are you trying to win?

Your criteria could include:

You're creating an opportunity profile.

This gives the Digital Employees a clear role.

Without that context, faster searching is new work for you.

SAM.gov may be one source, but it doesn't have to be your entire opportunity-monitoring system.

Depending on what you're pursuing, you might monitor:

This is another area where my thinking evolved.

The data needed to make a decision isn't limited to a procurement listing or RFP. My earlier framework already separated procurement and RFP data from organizational assets, customer insights, trusted third-party sources, and human intelligence.

The more sophisticated your operation becomes, the more sources and signals you may need to incorporate.

Finding an opportunity does not mean you should pursue it.

Your next job is screening.

Take what you've found and compare it against the criteria you established.

Does it fit your capabilities?

Are you eligible?

Do you have relevant experience?

Is it within the contract size you're targeting?

Does it align with your strategy?

Can you satisfy the mandatory requirements?

Do you have enough time?

The objective here is simple:

Remove obvious mismatches.

Because you're allocating resources whether you realize it or not.

Every hour someone spends investigating, capturing, pricing, writing, reviewing, or managing an opportunity has a cost.

The opportunities that survive screening aren't necessarily equal.

You need a way to prioritize them.

You might score opportunities based on:

Fit: How well does this match what you do?

Value: Is the potential value worth the resources required?

Timeline: Do you have enough time to pursue it properly?

Strategic Value: Does this advance an important customer, capability, vehicle, or market?

Signal Strength: How much evidence do you have that this is worth further attention?

Your exact scoring system will evolve.

That's the point.

You're building a foundation that can become more sophisticated as you learn.

Now you can spend more resources on the opportunities that passed your initial filters.

You may want to know:

This is where a list converts into opportunity intelligence.

AI can create velocity around collecting, organizing, analyzing, and presenting the information.

It doesn't eliminate the human responsible for deciding what the organization should pursue.

Sometimes the answer isn't simply "bid" or "don't bid".

You might find a good opportunity and realize you need someone else.

Opportunity monitoring can lead into partner and teaming intelligence.

The question becomes:

What do we need to assemble to compete for this opportunity?

Finding an opportunity isn't the outcome.

Someone needs to do something with it.

Decide who receives qualified opportunities and what information they need to make a decision.

Then track what happens:

Found → Screened → Qualified → Prioritized → Pursued/Passed → Submitted → Won/Lost

Now you have a feedback loop.

Maybe certain searches consistently produce bad opportunities.

Change them.

Maybe one agency produces better opportunities.

Increase its priority.

Maybe your strategy changes.

Update the criteria.

Maybe you win new work that gives you additional past performance and opens an entirely new category of opportunities.

Update the system.

This is why I think about this as infrastructure rather than an automation.

The infrastructure evolves as you do.

You don't have to build the entire system before you can start using this approach.

Want to try it?

I built an AI Capture Team in ChatGPT that can help you find, assess, and prioritize government contracting opportunities based on your business.

Try the AI Capture Team in ChatGPT

One of the most common things I hear from people trying to find opportunities is that it takes too long.

That's a resource gap.

AI Teams give us a new way to close it.

The earlier version of my approach required preparing data sources, a knowledge base, workflows and actions, then building logic around those pieces. Find & Win More SAM.GOV Opportunities

Those fundamentals haven't disappeared.

What's changed is what we can build with them.

Today, I can create AI Teams with Digital Employees responsible for different jobs, organize those employees inside AI Teams, schedule recurring work, connect them to information and tools, and keep humans in the loop for judgment, strategy, relationships, and approval.

And I'm not tied to one AI tool.

The infrastructure the roles, responsibilities, knowledge, criteria, workflows, and logic is what matters.

The AI surface is interchangeable.

Your strategy will change.

Your target customers will change. Your capabilities will change. New information will come in.

You'll learn from wins and losses. New legislation, budgets, programs, relationships, and market events may change where you look for opportunity.

Build AI Teams that can change with you.

Don't automate how you search for opportunities today. Build the infrastructure that helps you continuously find and pursue the right opportunities tomorrow.

Build it yourself or put the team to work.

Start with the AI Capture Team Plugin in ChatGPT.

Use it to find, assess, and prioritize opportunities, then expand the infrastructure as your needs evolve.

Try the AI Capture Team Plugin

Marvin