The establishment of the widely publicized DOGE (Department of Government Efficiency) highlights the new administration’s focus on improving efficiency in government operations and, as a result, impacts companies supporting those operations. DOGE’s goal is to push the sector toward technology modernization and consolidation and increased productivity. This shift is poised to transform both the government sector itself and the organizations that work to support it – especially government contractors (GovCons).
This has created an urgent need for effective AI-driven solutions among government contractors – both those they build for the government mission, as well as use within their own back-office – that can help accelerate innovation, more rapidly deliver cost-effective solutions, and demonstrate value and mission alignment to government customers, with the goal of remaining competitive in the months and years to come. However, to make sure the transformation reaches the goals that the Trump administration has set out to achieve, the GovCon sector must balance technology implemented by capability with regulatory compliance. Ensuring the deployment of new AI-enabled tools in alignment with foundational security and compliance standards remains critical regardless of the capability.
The Application of AI in GovCon Back-offices
While AI is playing a rapidly growing role in contractor solutions to support government missions (both civilian and defense), AI is also revolutionizing aspects of the GovCon back-office, from opportunity identification through contract execution, aiding contractors in delivery of more cost-effective and value-driven solutions. AI, as used here, goes beyond generative AI such as ChatGPT and Large Language Models (LLMs) – it also encompasses domain-trained agentic workflows and MCP (Model Context Protocol) that, for example, can help extract necessary information from enterprise document repositories or leverage open-source information for competitive analysis.
Identifying and pursuing new contract opportunities is one of the most essential processes that AI is helping automate and make substantially more efficient. AI-driven agents and algorithms help identify federal opportunities that tightly match contractors’ capabilities and past performance, as well as aid with forecasting procurement trends and needs.
Another process where AI can help government contractors transform is proposal development. AI can draft proposals according to specific requirements in a much shorter time frame, so companies can increase their “shots on goal.” In the past, this would require hours and hours of research, meetings and reviews to get to a pink team draft. Now, in minutes, AI solutions can provide technical volume drafts tailored to company capabilities and past performance. But, as Spiderman’s Peter Parker said, “With great power, comes great responsibility.” Human expert oversight and revisions are essential. AI can’t replace contractor expertise, but it does eliminate tedious information-gathering and accelerates compliance reviews. The point is to automate redundant and boring tasks with AI, enabling a contractor’s critical personnel to focus instead on demonstrating their discriminating expertise and capabilities more effectively in a proposal, with a keen focus on value and mission alignment.
Once a contract is awarded, AI can assist with executing and managing the new contract. Automating post-award processes can significantly reduce a contractor’s administrative burden while also improving customer satisfaction. In this rapidly evolving world of DOGE, contract execution, management and closeout are critical, and efficiency is key to company performance.
AI-powered data extraction and summarization capabilities streamline cumbersome intake processes for new contract awards and contract modifications and aid in rapidly responding to data calls from internal and external stakeholders. AI agents can also lend a hand in analyzing and flagging contract risk, monitoring for compliance, and making sure the contract is on the right track and its execution aligns with the agreement. This removes redundant tasks from contract managers and keeps them focused on the tasks that require human intervention. All of this helps GovCons more effectively deliver innovative, cost-effective solutions and demonstrate continuous value to their government customers, who in turn are better equipped to make a case for the imperative of that contractor’s services to their mission.
Implementing AI throughout all stages of the government contracting lifecycle can make a tremendous difference for contractors, provided the AI agents and tools leverage government-specific data and enterprise document repositories to ensure accurate, trustworthy AI outputs. In addition, choosing an AI platform that includes both pre- and post-award capabilities is critical to streamlining cross-departmental collaboration and increasing back-office optimization for GovCons. Like the tech consolidation happening in the government today, enterprises need to look inward and leverage technology solutions to enhance efficiency and remain competitive.
The Compliance and Security Challenge
Doing business with the government requires a high level of regulation and compliance, which means that any AI implementation needs to comply with numerous requirements. Balancing innovation and regulatory compliance can present a challenge. Government contractors working with sensitive data related to the government, whether Federal Contracting Information (FCI) or Controlled Unclassified Information (CUI), are obligated to ensure the technology they use adheres to a variety of standards, depending on the type and designation: NIST 800-171 r3, FedRAMP (NIST 800-53 r5) and Cybersecurity Maturity Model Certification (CMMC), to name just a few. Contractors are also responsible for maintaining the highest level of security to minimize the risk of sensitive government data exposure when using AI.
Although possible, adopting AI technologies while remaining compliant is a fine balance. To mitigate possible cybersecurity and privacy risks associated with AI, government contractors must judge whether they build or buy their solutions and evaluate these options, incorporating AI across Security, Data Protection and Availability metrics. They should employ security best practices in their own responsibility areas and adopt solutions built for the government industry.
Some best practices include:
- Architect or select models with cybersecurity best practices in mind, including data at rest, data in transit and native FIPS encryption. Solutions should implement strict access control policies that dictate who can access what data.
- Choose models hosted by providers that grant enhanced data terms dictating where and how data will be leveraged – for example, ensuring that all processing will be done within the United States or that data will not be used for enhancing foundational models. This helps make sure there is no data leakage to the foundational model provider, such as OpenAI or Anthropic, controlling sensitive data.
- Understand how your users will interact with the AI solutions and understand the guardrails and testing in place to only present them with the data appropriate to the use case. Solutions should control inappropriate, illicit, or biased responses. Also, since AI solutions typically incorporate non-deterministic LLMs, ensure these solutions control the consistency and faithfulness of the responses to users, which is incredibly important in building trust in these solutions.
- Confirm that solutions are hosted on FedRAMP approved platforms, such as AWS GovCloud or Azure, to ensure secure deployments. These platforms carry FedRAMP certification but there is a catch: they typically offer a shared responsibility model for data protection for the cloud solution providers (CSPs) that build on top of their platform and the eventual users of the end SaaS solutions. Make sure these platforms provide Customer Responsibility Matrices (CRMs) so that you understand your data responsibility when using their solution. The solutions should also be architected in a way that allows dedicated customer-segregated data repositories that provide an additional level of security.
- Consider providers that review and adopt both managed and self-hosted open-source AI models. This approach allows providers to capitalize on the latest technological advancements while maintaining a higher level of security. While the GovCon sector may be slower to adopt specific models due to stringent regulations, a hybrid approach can help cut that time in half. It’s the best of both worlds.
- Open-Source models, like popular open-source libraries, provide companies with powerful foundations on which to build great solutions. However, be sure to understand the provider’s supply chain risk management plan and vulnerability assessment model. Proper governance on when to patch these libraries and models, model end of life evaluation and usage rights tracking are all key considerations to avoid performance or security issues.
- Properly manage and patch threats, which is a continuous job that solution providers must provide for submission to the FedRAMP PMO. FedRAMP compliance is difficult to achieve but the more important aspect is a properly developed and executed Continuous Monitoring plan. FedRAMP 20x, as proposed by the FedRAMP PMO, will help move the industry forward to more results-based cybersecurity rather than hundreds of pages of documentation, so proper telemetry and automation solutions are key.
- Lastly, companies that choose to build AI solutions must do all of the above, while also supporting the ever-changing model and technology landscape. Keep on top of issues such as model deprecation (every 3-6 months), model drift and drastic cost deviations from model providers or hardware dependencies.
The Delicate Balance
The government sector, together with GovCon, are faced with both uncertainty and opportunity right now. The challenge of increasing overall efficiency and modernizing technology comes at a time of unprecedented technological innovation in the form of AI, equipping organizations with powerful tools poised to make a significant impact. At the same time, AI adoption, especially in these highly regulated spaces, requires a deliberate strategy that ensures compliance and security are both prioritized. AI’s future in government contracting isn’t just about driving efficiency and innovation. It’s about trust, compliance, and more effectively supporting the goals of the customer’s mission.
AI technology and its capabilities are constantly evolving. So, it’s crucial to map out a plan but also to stay on top of the changes and make timely adjustments to security and compliance procedures and protocols as new tools and features are introduced. Remaining both open to innovation and vigilant will ensure government contractors navigate uncertainty and emerge stronger and more resilient for the future.
