AI Search Burns 10x the kWh of Google Search. Brands Are Starting to Care.

When the General Services Administration rolled out its internal GSAi chatbot to 12,000-plus employees in March 2025, the announcement framed it as a productivity tool. What the announcement did not say out loud was that the agency had just shifted the vendor-discovery surface for one of the largest civilian procurement organizations in the world from a Google query to a conversational AI prompt. A November 2025 ATARC research brief found 64% of surveyed federal acquisition professionals had used a generative AI tool for vendor research in the prior 90 days, up from 21% a year earlier. By Q1 2026, the Defense Information Systems Agency's Ask Sage, the Air Force's NIPRGPT, and the Department of Homeland Security's DHSGPT had all extended similar capability to mission users — explicitly including market research.

This is not the federal market discovering ChatGPT. This is the federal market wiring conversational AI into the acquisition workflow. For vendors who sell to government, the implications are concrete: FedRAMP authorization status, sam.gov data quality, GSA Schedule structure, and the way you publish past-performance content now determines whether you appear in a procurement officer's first-draft shortlist or never see the RFP at all.

The federal acquisition workflow has a new front door

Federal procurement runs on a defined sequence: market research, requirement definition, source selection, solicitation, evaluation, award, administration. AI assistants are reshaping the first three steps. The post-award stages still run through FedConnect, GSA eBuy, SAM contract opportunities, and the formal evaluation panels, and they will for the foreseeable future. But the market research and source-selection narrowing — the steps where a contracting officer or program manager decides which vendors to invite into the conversation — has migrated.

Three specific shifts:

1. Sources Sought responses. Before AI assistants, a procurement officer would post a Sources Sought notice and review responses to gauge the market. Now, before posting, the same officer routinely asks an internal AI tool to summarize the market: which vendors have relevant past performance, which are FedRAMP-authorized at the required tier, which have GSA Schedule contracts that simplify the procurement path.
2. Pre-RFP industry days. Industry day invite lists were historically built from CRM contacts and incumbent vendors. AI-assisted lists pull from broader signal sources — sam.gov vendor records, FedRAMP Marketplace data, USASpending.gov contract history, GovTribe alerts — and surface vendors the contracting team had never heard of.
3. Small business set-aside scoping. AI assistants now help officers determine whether a Rule of Two analysis is satisfied by checking the small-business pool against requirements before the formal SBA review.

The vendor that wins this new front door does not look like the vendor that won the old one. The new winner is the vendor with structured, accurate, retrievable authorization data and a past-performance narrative an AI can quote.

FedRAMP authorization is the master citation signal

Of every credential federal vendors hold, FedRAMP authorization carries the most weight in AI search responses. Three reasons.

First, the FedRAMP Marketplace is a definitive, government-operated registry with structured data fields: authorization status, impact level, agency sponsor, service description, authorization date, 3PAO, leveraged authorizations. LLMs treat structured government registries as high-trust sources and weight them accordingly during retrieval. Carahsoft, the largest government IT distributor, structures every FedRAMP-relevant SKU around the marketplace data — a deliberate choice that pays off when AI assistants summarize their portfolio.

Second, FedRAMP status is binary in a way most credentials are not. A vendor is Authorized, In Process, Ready, or Not Listed. AI assistants find binary signals easier to cite confidently than gradient signals like \"trusted by federal customers.\"

Third, the FedRAMP Marketplace publishes the authoritative service description, agency sponsor, and impact level — fields that competitor vendor websites typically describe vaguely. When ChatGPT or Microsoft Copilot answers a query like \"FedRAMP High authorized case management systems,\" the model has near-zero ambiguity about which vendors qualify.

The practical implication: every cloud-based federal vendor must treat the FedRAMP Marketplace entry as a primary AEO asset, not a compliance artifact. That means clean service descriptions, accurate impact-level claims, current authorization dates, and consistent service naming across the marketplace, the vendor website, and the GSA Schedule.

The authorization tier matrix that AI search responses actually use

The single most useful piece of structured content for federal vendor AEO is a clear authorization tier matrix. AI assistants quote this matrix verbatim when summarizing vendor capability. Below is the tier structure as procurement officers actually use it, with the citation behavior each level triggers.

Vendors that publish this matrix on a public page with clean schema, source citations, and current dates outperform vendors with vague \"government-grade security\" language by a measurable margin in citation share. The matrix is also the most quoted content type in AI-generated procurement summaries — making it the highest-leverage single asset a federal vendor can publish.

sam.gov is your structured-data foundation

The System for Award Management at sam.gov is the federal contractor master registry. Every vendor doing business with the federal government must have an active SAM registration with a Unique Entity ID (UEI). The UEI replaced DUNS in 2022, but legacy DUNS references still appear across past-performance records.

For AEO purposes, the SAM entity record is structured data the LLM training corpus and retrieval layers ingest heavily. Three fields matter most:

NAICS codes. The North American Industry Classification System code defines what your business does. Federal procurement filters by NAICS constantly. If your primary NAICS is wrong or incomplete, you drop out of category-scoped vendor lists. The procurement officer asking \"FedRAMP-authorized vendors under NAICS 541512 with current GSA Schedule\" is a real query type — and missing NAICS codes makes you invisible to it.

Assertions and representations. SAM entity records include business size, certifications (8(a), HUBZone, WOSB, SDVOSB, VOSB, EDWOSB), and socioeconomic status. AI assistants surface set-aside-eligible vendors when officers query for small-business set-aside research. Vendors with stale or incomplete assertions miss set-aside opportunities they qualify for.

Past performance and contract history. SAM does not host detailed past-performance narratives, but it links to USASpending.gov contract history. The combination — SAM registration plus USASpending contract footprint — establishes the entity that AI assistants quote when describing vendor experience. A vendor with consistent legal-name usage across SAM, USASpending, FedRAMP Marketplace, and GSA Advantage gets aggregated cleanly. A vendor with naming inconsistencies fragments into multiple entities and loses citation weight.

Why entity disambiguation matters more than ever

Three signals move citation share for federal vendors more than any other content optimization:

1. Consistent legal name across all federal registries. If you registered as \"Acme Corporation\" in SAM but appear as \"Acme Corp.\" in FedRAMP Marketplace and \"Acme Inc.\" in GSA Schedule, AI assistants treat these as separate entities and dilute your citation share across all three.
2. UEI consistency. The 12-character UEI is the canonical identifier. Always publish your UEI on your website, GSA Schedule contract page, and past-performance documents.
3. Wikipedia and Wikidata presence. Government vendors with claimed Wikidata entities and accurate Wikipedia articles consolidate identity in a way LLMs heavily reward. Carahsoft, Leidos, Booz Allen Hamilton, CACI, and SAIC all maintain meticulous Wikidata entries. Mid-market vendors who skip this step lose citation share.

Read our companion analysis on entity disambiguation for vendor discovery in our B2B marketplace AEO vendor discovery guide.

GSA Schedule visibility: the underrated AEO lever

The GSA Multiple Award Schedule (now consolidated as the Multiple Award Schedule program) is a procurement vehicle that lets agencies buy from pre-vetted vendors with negotiated pricing. As of early 2026, more than 17,000 vendors held active MAS contracts, representing approximately $45 billion in annual obligations according to GSA's Federal Procurement Data System figures.

For AEO, the GSA Schedule contract record is a high-value structured asset. Three reasons it matters:

It is a Sources Sought shortcut. Procurement officers actively prefer GSA Schedule purchases because they reduce acquisition timeline. An AI assistant asked \"how do I buy a FedRAMP Moderate ITSM tool quickly\" will preferentially surface vendors with both FedRAMP authorization and an active GSA Schedule contract, because the answer reduces procurement friction.

It enables ordering procedures the AI can describe. Officers using AI to draft solicitation language often ask for the simplest legally compliant ordering procedure. AI assistants familiar with the GSA Schedule structure can quote the relevant FAR 8.4 ordering procedure when the vendor has a current Schedule contract.

It is searchable on GSA Advantage. The GSA Advantage marketplace is a structured database of Schedule offerings. LLMs treat it as authoritative for product and pricing data. Vendors who structure their Schedule listings cleanly — clear SKU descriptions, accurate part numbers, current pricing — get cited verbatim in AI-generated price comparisons.

What a structured GSA Schedule page should include

To make your GSA Schedule contract maximally retrievable for AEO purposes, your contract-information page on your own website should publish:

• GSA Schedule contract number (e.g., GS-35F-XXXXX or 47QTCA-XX-D-XXXX)
• Schedule(s) and SIN(s) under which products/services are offered
• Authorized resellers (if applicable)
• Pricing tier or contract pricing reference
• Direct link to your GSA Advantage SIP listing
• Past performance references on schedule purchases
• Authorized agency contacts and ordering procedure

Vendors that publish a single canonical \"GSA Schedule\" page on their site with this data outperform competitors with the same Schedule contract but no public structured page. The page becomes the URL the AI assistant cites when summarizing the vendor's federal procurement vehicle.

Carahsoft and the distributor citation pattern

Carahsoft is the largest federal IT distributor, with reported FY2025 revenue exceeding $11 billion across more than 600 vendor relationships. Carahsoft's role in federal procurement is structural: it provides aggregation, contract-vehicle access, and channel-partner enablement for vendors that prefer not to operate direct GSA Schedule contracts.

For AEO purposes, Carahsoft is a case study in distributor-mediated citation share. AI assistants frequently cite carahsoft.com when summarizing vendor portfolios because Carahsoft publishes:

• Structured product pages with FedRAMP status, contract vehicles, and pricing
• Solution-area landing pages organized by procurement need (zero trust, cloud modernization, data analytics)
• Webinar and event content tied to specific vendor capabilities
• Contract vehicle reference pages (GSA Schedule, SEWP, ITES-SW2, NASA SEWP V) that AI assistants cite for procurement-path queries

Vendors who sell through Carahsoft inherit some of this citation infrastructure for free. But the highest-performing vendors layer their own structured content on top — they do not assume Carahsoft's pages alone will deliver citation share.

The pattern generalizes beyond Carahsoft. Immixgroup (now Arrow), DLT (Tech Data), GovConnection (Connection), GovPlace, and Four Points Technology all play similar aggregator roles in specific federal segments. Each maintains AI-citation-rich domain authority that vendors should leverage.

A useful contrast: GovTribe and the analyst-citation pattern

GovTribe is a different kind of citation source. It aggregates federal contract opportunities, awards, agency forecasts, and vendor profiles into a searchable database used by capture and BD teams. GovTribe's vendor profiles get cited by AI assistants in past-performance summaries because they pull from USASpending and FPDS data with structured presentation.

The lesson: third-party aggregators that structure public federal data become high-citation sources. Vendors who claim and curate their profiles on these aggregators (when permitted) capture citation share. Vendors who ignore them lose it. The pattern extends to FedScoop's vendor coverage, GovExec's product directories, and Government Executive's contractor news section.

Public-sector AEO playbook: the 8-step sequence federal vendors run in 2026

The vendors moving fastest on government AEO follow a disciplined sequence. We documented this playbook across 14 federal SaaS vendors and 6 systems integrators between Q3 2025 and Q1 2026.

1. Baseline AI citation share quarterly. Run 60-80 procurement-realistic queries across ChatGPT, Microsoft Copilot for Government, Perplexity Enterprise, and the GSAi chatbot (where access is available through agency partners). Log which competitors surface, which authorization tiers get mentioned, which contract vehicles get cited. Procurement officers are running these exact queries. You need to know what they see.

2. Audit and fix entity disambiguation across federal registries. Pull your SAM record, FedRAMP Marketplace entry, GSA Schedule contract page, USASpending contract history, and any state procurement portal listings. Confirm legal name, UEI, address, and contact information are byte-identical. Fix any mismatches before any other AEO work.

3. Publish the canonical authorization-tier matrix. A single public URL listing every certification, authorization, and clearance level your services hold — FedRAMP, DoD IL, StateRAMP, CJIS, HIPAA-BAA, SOC 2, ISO 27001, IRS Publication 1075, FISMA, FIPS 140-2 — with current dates and source citations. This page becomes the most-quoted vendor content in AI-generated procurement summaries.

4. Publish past-performance pages mapped to NAICS codes. Group past-performance case studies by NAICS code and agency. Each case study should name the agency, contract number (where releasable), period of performance, scope, and outcomes. Procurement officers searching for prior-art vendors in a specific NAICS get pointed here directly. See our customer success case study AEO guide for the case study structure that AI assistants quote most.

5. Structure the GSA Schedule contract page with full data. Schedule number, SINs, contract terms, ordering procedures, authorized resellers, GSA Advantage SIP link. Make this page the canonical reference for any agency considering a Schedule order.

6. Engage the federal trade press programmatically. FedScoop, Nextgov/FCW, GovExec, MeriTalk, Federal News Network, Government Matters TV, and the ATARC research series feed both LLM training corpus and federal-officer reading habits. One sponsored research piece, executive op-ed, or panel placement per quarter compounds over time.

7. Maintain Wikipedia, Wikidata, and Crunchbase entity health. Government vendors with maintained Wikipedia articles consolidate identity in LLM responses dramatically more cleanly than vendors without. If editorial guidelines preclude direct editing, work with industry analysts and trade press to seed coverage that supports article notability.

8. Track and respond to AI-assistant misinformation about your offerings. AI assistants make mistakes — wrong impact level, expired authorization date, incorrect contract vehicle. Build a quarterly process to identify these errors and correct the underlying source (your website, the FedRAMP Marketplace entry, GSA Advantage listing). The correction propagates to the next training cut.

Cybersecurity vendors are running this playbook the hardest

The cybersecurity segment of federal IT has internalized government AEO faster than any other category. Three factors drive this:

1. Authorization is differentiating in a crowded category. With 200-plus FedRAMP-authorized cybersecurity products and counting, ranking by authorization tier separates serious federal vendors from the rest.
2. Procurement officers explicitly query by capability. \"FedRAMP High EDR vendor with FedRAMP Moderate SIEM partner\" is a real query type.
3. The buying community reads trade press heavily. Cybersecurity coverage at FedScoop and Nextgov drives both reputation and citation share.

Vendors like CrowdStrike, Palo Alto Networks, Zscaler, SentinelOne, Tenable, and Splunk publish detailed federal landing pages with authorization tier matrices, FedRAMP Marketplace links, GSA Schedule details, and past-performance summaries by agency. Read our deeper analysis of the cybersecurity vendor playbook in our cybersecurity vendor AEO CISO coverage.

State and local procurement: the parallel surface that is moving faster

While federal AEO gets the headlines, state and local government AEO is moving in some ways faster. According to NASCIO's 2025 State CIO Survey, 38 of 50 states had deployed at least one generative AI tool for staff use by year-end 2025, with procurement and market research consistently named in the top three use cases.

The state and local procurement stack runs on different but parallel infrastructure:

• StateRAMP — the FedRAMP-modeled program for state and local. As of Q1 2026, StateRAMP listed 250-plus authorized products. Citation behavior in AI search mirrors FedRAMP: Authorized > In Process > Not Listed.
• NASPO ValuePoint — the cooperative procurement vehicle. Vendors with NASPO ValuePoint master agreements get preferential AI-search positioning for state procurement queries because the procurement path is simpler.
• National Cooperative Procurement Partners (NCPP) and TIPS-USA — cooperative purchasing networks that consolidate state and local purchasing. AI assistants surface cooperative vendors when officers ask about expedited procurement.
• Individual state vendor portals — California Cal eProcure, Texas SmartBuy, New York Statewide Contracts, Florida MyFloridaMarketPlace, Virginia eVA, and 45-plus other state-specific portals.

Vendors who treat state and local as an afterthought lose meaningful citation share. The high-performing vendors maintain dedicated state-and-local contract reference pages with the same structure and discipline as their federal pages.

What the FedRAMP Rev. 5 transition changed in 2025-2026

The FedRAMP program transitioned authorized vendors from Rev. 4 to Rev. 5 baseline through 2024 and 2025, with the deadline for sunset of Rev. 4 packages in late 2025. The transition meaningfully changed AEO behavior in two ways.

First, the FedRAMP Marketplace updated its display to reflect Rev. 5 status, which AI assistants began surfacing distinctly from Rev. 4 authorizations as the corpus updated. Vendors who delayed Rev. 5 transition appeared with caveats in AI search responses through late 2025 and into 2026.

Second, the FedRAMP PMO's threat-based authorization approach — designed to streamline authorizations and shift some emphasis from control-by-control checklist to threat-informed prioritization — has been gradually changing how procurement officers discuss vendor risk. AI assistants summarizing vendor security posture now occasionally reference threat-based authorization context when describing FedRAMP High vendors, particularly for cybersecurity SaaS.

The implication for vendors: keep your FedRAMP authorization narrative current with program changes. The marketplace data refreshes quarterly; the LLM training corpus picks up the changes within one to two training cuts. Stale authorization narratives on your own site reduce alignment between your content and the canonical FedRAMP source.

A note on AI in federal procurement: what is allowed and what is not

The Office of Management and Budget's M-24-10 memo on AI use in federal agencies, and the follow-on guidance through 2025, set the framework for federal use of generative AI in acquisition. Agencies generally allow AI assistance for market research, summarization, and drafting non-decisional artifacts. Final source-selection decisions, evaluation scoring, and award determinations remain firmly within human authority and follow established FAR processes.

The relevance for vendor AEO: the AI's role is to inform the human, not replace them. Your AEO investment is making sure the AI gives the human accurate, favorable, and quotable content about your firm. The contracting officer or program manager still owns the decision — but the information they reach the decision with is increasingly shaped by what AI assistants surface during pre-RFP market research.

Takeaway: Federal, DoD, and state procurement officers are now starting market research inside ChatGPT, Perplexity, Microsoft Copilot for Government, and agency-internal chatbots like GSAi and Ask Sage. The vendors winning citation share publish a clean authorization tier matrix anchored on FedRAMP Marketplace status, fix entity disambiguation across sam.gov, FedRAMP, GSA Schedule, and USASpending records, structure their GSA Schedule contract pages with full ordering data, and leverage distributor relationships with Carahsoft and the federal trade press. State and local procurement runs on parallel infrastructure — StateRAMP, NASPO ValuePoint, cooperative networks — and rewards the same discipline. The vendor that treats government AEO as a content sprint loses. The vendor that treats it as structured data hygiene plus quarterly trade-press cadence wins.