Contracting in the Age of AI: What You Need to Know

Artificial intelligence (AI) is no longer a futuristic concept in federal procurement - it is an operational reality. What began as small-scale automation pilots has evolved into agency-wide efforts to enhance efficiency, reduce administrative burdens, and improve decision-making across the entire acquisition lifecycle.

• How Federal Agencies Are Using AI Today
• Contracting Lifecycle Transformed by AI
• Procurement of AI: Ethical and Regulatory Considerations
• Generative AI: Promise and Pitfalls
• What Contractors Must Know and Prepare For
• Conclusion: AI Is Here to Stay – Prepare Now
• Frequently Asked Questions: AI and the Future of Federal Contracting

AI’s rapid integration into federal contracting is not incidental. With growing pressure to do more with less, federal agencies have increasingly turned to emerging technologies to streamline their processes. AI, particularly when combined with tools like machine learning (ML) and natural language processing (NLP), offers unprecedented capabilities: from accelerating solicitation reviews to enhancing responsibility determinations and identifying performance risks.

Recognizing the transformative potential of AI, the federal government has taken formal steps to establish a regulatory and ethical framework for its use. The Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence, signed in late 2023, outlines the foundational principles for AI deployment across civilian and defense agencies. While the full scope of implementation is still unfolding, the order reflects a clear institutional commitment to leveraging AI for public-sector efficiency,  without compromising transparency, fairness, or accountability.

As a result, contracting professionals, vendors, and policymakers must now navigate an evolving landscape in which AI is both a tool and a challenge. This article explores how AI is reshaping federal procurement; not in theory, but in real, operational terms, as well as what government contractors and acquisition professionals need to know to stay relevant and compliant.

How Federal Agencies Are Using AI Today

Federal agencies have steadily expanded the use of AI-driven tools to improve procurement operations. What began as experimentation with robotic process automation (RPA) has evolved into a wide range of applications – from contract clause validation to predictive analytics – all aimed at increasing speed, accuracy, and compliance in the acquisition process.

One of the earliest and most notable examples is the Internal Revenue Service (IRS) Clause Review Tool, which leverages AI to analyze solicitations and contracts for missing, outdated, or incorrect provisions. Tasks that previously took several hours are now completed in minutes. Similarly, the IRS DATA Act Bot combines RPA, AI, and natural language processing to clean procurement data, correct coding errors, and ensure compliance with telecommunications security requirements – processing thousands of records in seconds.

The Department of Homeland Security (DHS) has deployed AI to enhance the use of contractor performance data during source selections. Its pilot programs focus on identifying relevant entries in the Contractor Performance Assessment Reporting System (CPARS), helping contracting officials prioritize information critical to award decisions. These initiatives not only save time but also reduce reliance on subjective judgment.

The Department of Defense (DoD) has adopted AI and machine learning to support predictive maintenance, contract portfolio management, and risk mitigation. In one case, the Army’s use of predictive modeling software helped forecast equipment failures and informed contract modifications to prevent delays in mission readiness.

The General Services Administration (GSA), long a leader in federal acquisition innovation, has introduced AI-powered tools to review solicitations for accessibility requirements and assess pre-award vendor responsibility. These systems compile data from multiple sources – including financial records, past performance, and compliance databases – to generate standardized evaluations in a fraction of the time it would take a human specialist.

Across these and other examples, AI has enabled agencies to reduce processing time, enhance data integrity, and improve compliance with statutory and regulatory requirements. While adoption levels vary by agency, the trajectory is clear: AI is becoming an integral part of the acquisition ecosystem, embedded not as a standalone solution but as a layer of intelligence supporting existing workflows.

Contracting Lifecycle Transformed by AI

AI is not just accelerating isolated tasks; it is beginning to reshape the entire federal contracting lifecycle. From market research and solicitation development to contract administration and closeout, intelligent systems are being integrated into every phase of the process.

Pre-award activities have seen some of the most immediate impact. AI-driven responsibility determination tools, like those developed by the Army and the IRS, aggregate and evaluate vendor data from disparate systems to produce standardized assessments. These tools help identify financial instability, compliance risks, and performance deficiencies – all within minutes rather than hours. AI is also being used to review solicitations for regulatory completeness, such as confirming inclusion of Section 508 accessibility clauses.

In the award phase, AI contributes to the structuring and drafting of contract documents. The Defense Department’s collaboration with Trenchant Analytics, for example, aims to build an AI-enabled writing system that can assist contracting professionals in generating requirements documents, solicitations, and calls to industry. While human oversight remains essential, the potential to reduce drafting time and minimize formatting errors is significant.

Post-award, AI supports contract administration through performance monitoring and predictive analytics. The Department of Health and Human Services (HHS) used its Accelerate platform to consolidate data across contracts and identify pricing anomalies, vendor risk patterns, and potential violations. In parallel, AI tools can assist in managing modifications, tracking compliance, and initiating closeout procedures – all of which are prone to delay or error in traditional workflows.

Importantly, the integration of AI also supports protest mitigation. By identifying protest-prone clauses early and standardizing solicitation language, AI systems reduce the likelihood of procedural missteps or perceived unfairness, both of which are common grounds for bid protests. Efforts by the Air Force and other agencies to prototype clause analysis tools reflect this growing use case.

While AI has not yet replaced the need for experienced acquisition professionals, it is increasingly acting as a force multiplier – enabling humans to focus on judgment, strategy, and stakeholder engagement rather than repetitive administrative tasks. The long-term effect is a contracting process that is not only faster but also more transparent, data-informed, and resilient.

Procurement of AI: Ethical and Regulatory Considerations

As agencies move from experimenting with AI to embedding it in operational systems, the government’s approach to acquiring AI technologies has matured. This shift brings a range of ethical and regulatory requirements that contractors must be prepared to meet – from ensuring algorithmic transparency to managing cybersecurity risks.

AI procurement now goes far beyond feature sets and performance specs. It requires careful attention to legal, operational, and reputational considerations. To support consistency across agencies, both the Department of Defense and the General Services Administration have introduced frameworks that help acquisition professionals evaluate AI from a governance standpoint.

The table below highlights key procurement considerations for AI technologies in the federal space:

Category	Expectation	Examples / Implications
Ethics	Responsible and human-centred design	Avoidance of bias, fairness in decision-making
Explainability	Ability to understand how decisions are made	Required for audit trails and FOIA responsiveness
Security	Protection of sensitive data and compliance with FedRAMP or agency-specific rules	Handling PII, integration with secure networks
Supply Chain Risk	Transparency in third-party components and training data sources	Compliance with Section 889 and NIST SP 800-161
Human Oversight	Retention of decision authority by humans	“Human-in-the-loop” mandated for critical decisions
Testing and Auditing	Demonstrable performance under various conditions	Stress testing, bias evaluation, and post-award assessments

Contracting officers are beginning to include clauses that require vendors to document these factors, either in technical volumes or compliance exhibits. Some solicitations now demand disclosure of AI model provenance and evidence of internal governance policies.

To navigate these expectations, vendors should collaborate with both technical and acquisition experts early in the procurement cycle. This includes ensuring their solutions meet the 2023 Executive Order on Safe, Secure, and Trustworthy AI, which establishes a foundation for responsible development and acquisition practices across the federal government.

Ultimately, contractors that can document ethical design, anticipate regulatory obligations, and clearly articulate the safeguards built into their AI solutions will be far better positioned to succeed in this evolving market.

Generative AI: Promise and Pitfalls

While traditional AI in federal procurement focuses on automation and structured decision support, generative AI introduces an entirely new set of opportunities – and risks. These models, including large language models (LLMs) like GPT, are capable of producing text, code, and even synthetic data in response to natural language prompts. The potential to use such tools in contracting is significant, but the path to implementation remains cautious.

In early pilot efforts, generative AI has been explored for drafting contract language, preparing performance assessments, and even supporting technical proposal reviews. The Defense Department’s CDAO (Chief Digital and Artificial Intelligence Office), for example, has partnered with private-sector firms to develop AI-assisted contract writing systems. These tools aim to produce consistent, compliant, and tailored documents – reducing drafting time and clerical errors while maintaining standardised formatting.

Generative AI has also shown value in creating sample datasets to train other systems or test government software applications. In the cybersecurity realm, it can help simulate threats based on historical patterns, aiding federal agencies in anticipating and mitigating risks to procurement systems. Likewise, it may be used in pattern recognition, anomaly detection, and fraud prevention – supporting contract integrity and financial oversight.

However, the risks of generative AI are distinct. Unlike narrow AI tools built on predefined rules or structured data, generative systems are known for hallucinations;  producing incorrect or fabricated outputs that appear credible. In a regulatory context like federal contracting, where precision is critical and language carries legal weight, such errors can have serious consequences.

Furthermore, generative models are often trained on large, publicly available datasets that may carry inherent biases, outdated norms, or irrelevant context. Without rigorous fine-tuning, there is a high risk that AI-generated contract language could be non-compliant or misleading. Agencies must therefore adopt strict validation processes and ensure that generative outputs are reviewed by qualified human experts.

The federal government acknowledges these concerns. The Executive Order on AI calls for robust guardrails around high-impact AI applications, especially those used in decision-making or legal drafting. Agencies are also encouraged to apply procurement requirements that ensure transparency, explainability, and human-in-the-loop oversight for any generative AI tool under contract.

In short, generative AI may eventually become a powerful assistant to contracting professionals, while not yet being ready to operate independently. Its use must be supervised, auditable, and constrained by policy. When applied thoughtfully, it can support speed and consistency. When misapplied, it can introduce compliance failures, legal risk, and reputational damage. Understanding that balance will be essential as adoption continues to expand.

What Contractors Must Know and Prepare For

As federal agencies expand their use of AI in procurement – both as buyers and users – government contractors must evolve their strategies. AI is not simply a trend in back-office optimization. It is becoming a defining element of how contracting is conducted, evaluated, and governed.

To remain competitive and compliant, contractors should focus on five key areas:

1. AI Readiness and Transparency
   Contractors offering AI-enabled solutions must be prepared to demonstrate:
   • The origin and quality of training data
   • Mechanisms for bias detection and correction
   • Explainability and auditability features
   • Human-in-the-loop controls where required
2. Accuracy of Public Procurement Data
   Automated systems increasingly rely on databases like SAM.gov, CPARS, and FPDS. Ensure that your:
   • Entity registration is current and complete
   • Past performance entries are accurate and consistent
   • NAICS codes and PSCs reflect your current offerings
3. Internal AI Adoption
   Even if you don’t sell AI, using it internally offers operational advantages:
   • Automate proposal writing, compliance checks, and reporting
   • Use predictive analytics for pricing or performance forecasting
   • Streamline contract management and modifications
4. Regulatory Awareness
   Stay informed about evolving rules such as:
   • AI-specific clauses in solicitations
   • Updates to FAR, DFARS, and agency-specific supplements
   • Guidance stemming from the 2023 Executive Order on AI
5. Strategic Positioning
   Long-term success will depend on:
   • Training staff to understand AI’s role in procurement
   • Aligning offerings with agency AI objectives
   • Demonstrating value in a data-driven acquisition environment

At this stage of transformation, being passive is no longer an option. Contractors that embrace AI thoughtfully and strategically, will be better positioned to navigate a procurement landscape that increasingly values speed, accuracy, and compliance through technology.

Conclusion: AI Is Here to Stay – Prepare Now

The integration of artificial intelligence into federal procurement is not a passing trend – it marks a structural transformation of the acquisition environment. From clause review bots to generative contract drafting tools, AI is no longer confined to research pilots. It is influencing how solicitations are written, how vendors are evaluated, and how performance is monitored. Contracting is not simply facing change – it is operating within it.

To navigate this evolving landscape, collaboration is essential. Contracting officers, program managers, policy analysts, and legal teams must work alongside data scientists and technologists to ensure AI systems are implemented effectively, ethically, while staying in compliance with federal requirements. This multidisciplinary approach is what enables agencies to gain real operational value from AI without compromising accountability.

At Price Reporter, we have spent nearly two decades helping over 1,000 GSA contractors adapt to the shifting demands of the federal marketplace. As AI continues to reshape procurement processes and expectations, our expertise in GSA contract acquisition, management, compliance, and automation ensures that our clients stay ahead. Whether you are preparing to compete in an AI-enhanced acquisition environment or seeking to integrate AI capabilities into your own business model, we provide the insight and infrastructure needed to succeed.

Frequently Asked Questions: AI and the Future of Federal Contracting

How is AI currently being used in federal procurement?

Federal agencies are using AI to streamline and improve various stages of the contracting process. Applications range from reviewing solicitations and evaluating vendor responsibility to monitoring contract performance and detecting compliance risks. Tools such as the IRS Clause Review Tool and DHS’s CPARS analytics pilot are already delivering measurable efficiency gains.

What types of AI are relevant to government contracting?

Both traditional AI and generative AI play important roles. Traditional AI, including machine learning and rule-based automation, is commonly used for tasks like classification, scoring, and predictive analytics. Generative AI is more experimental, while at the same time being tested for tasks such as drafting contract clauses and summarizing performance data.

Are there ethical or legal risks associated with using AI in contracting?

Yes, ethical and legal risks are significant concerns. AI systems must be free from bias, explainable in their logic, and secure in their handling of sensitive data. That is why agencies and vendors alike are expected to comply with ethical standards set out by the Department of Defense, the GSA Center of Excellence, and the 2023 Executive Order on AI.

How can government contractors prepare for AI-enabled procurement processes?

Contractors should start by ensuring that their public data profiles are accurate, as many AI tools rely on external databases. Internally, they should explore how AI can support proposal preparation, compliance monitoring, and performance analytics. Finally, they must understand the new regulatory expectations and be ready to demonstrate transparency, security, and accountability in any AI-related offering.

Will AI replace contracting professionals in the federal space?

No, AI is not expected to replace human contracting professionals. Instead, it serves as a decision-support tool that enhances speed, consistency, and data accuracy. Human judgment remains essential for interpretation, ethical oversight, and legal accountability in government procurement.