6 fundamentals for AI success for defense contractors

For artificial intelligence (AI)’s ability to create massive new efficiencies, support better and timelier decision-making, reveal and capitalize on new business opportunities, relieve human beings of tedious tasks, and generally accelerate an organization’s growth, the possibilities for employing it inside a government contracting business seem boundless. Agentic AI, generative AI, natural language processing, predictive tools, and machine learning algorithms – they all may have viable use cases within a GovCon firm. As of 2025, according to the latest GAUGE benchmarking report from Unanet and CohnReznick, 54% of GovCon firms are actively using AI, with another 42% open to implementing it.

Today we’re seeing AI help GovCon companies win more business, faster, by uncovering new bid opportunities they may otherwise have overlooked that align with their strategic priorities, and then by providing analysis that helps decision-makers prioritize the right pursuits. Who are your ideal types of customers from a profitability standpoint? Which types of projects are you better off avoiding based on past experience? AI can help answer questions like these. Then it can assist in actual proposal preparation, reducing the time, money, and resources required to respond to requests for proposals (RFPs), enabling firms to cut average RFP time-to-draft by 70% while reducing proposal generation costs, which can run up to six figures, by half. With AI-powered proposal tools doing much of the heavy lifting, your people can focus on the parts of a proposal where a more nuanced human touch can really make a difference.

On the project side, meanwhile, AI can generate real-time insight into project progress, resource utilization, and budget variances, alerting decision-makers to cost trends and potential overruns to support cost-control. AI also can help with compliance by interpreting complex regulatory language, flagging compliance risks such as mismatched or erroneous data, and creating policies and procedures to maintain compliance, then monitoring projects to ensure they’re tracking to those policies and procedures.

Building a foundation to thrive with AI

When it comes to tapping the potential of AI in use cases such as these, the real limiting factors have to do with government contracting firms themselves – specifically, how strong a foundation they build for their intelligent capabilities. Based on my work with GovCon firms and our own internal experience implementing AI, here’s a look at six foundational best practices for getting the most from your AI investments:

1. Treat data as a critical asset. Data can be among an organization’s most valuable assets, right alongside tangibles such as real estate and equipment, and intangibles such as institutional knowledge and intellectual property. Data – internal or external, structured or unstructured, small data sets or large – is the lifeblood of a well-run, profitable organization, for its ability to inform, yield insight, and elevate decision-making. AI thrives on data – the more comprehensive, fresher, more accurate, and relevant your data, the more effective your AI likely will be.
2. Size up the quality of your firm’s data. In the GAUGE Report, slightly more than 50% of GovCon execs indicated they’re “very confident” in the quality and accuracy of their data; 45% said they’re somewhat confident. Firms that lean heavily on data for any reason should be very confident in the quality of their data. That’s especially true for GovCons that are already using, or planning to use, AI. How fresh is the data in your systems, and how trustworthy is it? How readily can it be accessed by people and the analytics tools your firm employs? How large are the gaps in your data? An honest data quality assessment enables you to identify and address any shortcomings. This is a worthwhile exercise, because the better your data, the better the insights and outcomes AI should produce, and thus the more value it should provide back to the business.
3. Integrate your software systems so data can flow easily and securely to your people and the AI capabilities that support them. Having the freshest, most accurate, and complete data means little unless your digital systems are connected within a common ecosystem, enabling information to flow unimpeded, in real time, within and across teams and the entire business. Siloed systems and manual spreadsheets are a real hindrance to an organization’s ability to leverage data and AI. On the other hand, if your organization’s digital systems are fully integrated within a single seamless environment, the potential use cases for AI are many. Develop and maintain a single, secure data lake. The concept here is to create a centralized, secure data repository to serve as the single source of truth for your business, one that’s readily accessible to your AI and analytics tools, and to relevant people across the company. Here’s where to go for any and all information about past and current projects, financials, pursuits, pipeline, customers, prospects, and institutional knowledge.
4. Establish, socialize, and enforce strong data governance practices, processes, and procedures. How do you ensure people enter data into the systems you use to run your business? What types of standardized forms and processes should they be using when they’re entering data into a system? What processes and tools will you use to validate data and ensure data hygiene? What rules and security measures are in place to keep sensitive data safe and ensure it’s handled compliantly? What formats, naming conventions, etc., are applied to the data in your data lake? All this should be detailed within the policies, procedures, best practices, and guidelines comprising a data governance program. Any business that uses AI – and any organization that relies on data to a significant degree – should have a formal data governance program in place. In my experience, the best data governance programs are built with input from leaders across the business – a tiger team approach. Ultimately, the goal is to create a culture of responsible data stewardship inside your organization, where people recognize how valuable data is in their work and to your organization, and they understand and follow prescribed data management processes.
5. Reinforce a data stewardship culture with training and education. To maximize the value of your data and the return on your AI investments, you also need to invest in training and education so people throughout your organization are well-versed in the processes and tools at hand. Build performance management metrics into your data governance program, whereby people know their job performance will be evaluated in part on them following the processes and using the tools, and generally adhering to the data governance program.

With these fundamentals in place, and trustworthy data flowing throughout the digital circulatory system of your business, it’s no longer a question of whether AI can provide value to your government contracting organization, but rather how much value.

About the author: Steve Karp is chief innovation officer for Unanet, a Northern Virginia-based software company that provides enterprise resource planning and customer relationship management solutions for organizations in the government contracting, architecture, engineering, construction, and professional services markets.

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