How AEC Firms Manage RFP Volume: Insights from QorusDoc's 10th Annual Proposal Management Benchmark

Proposal management is a core growth engine for AEC firms, yet systematic data on performance, bottlenecks, and automation adoption has been scarce. The 10th Annual Proposal Management Survey by QorusDocs fills that gap with sector-level benchmarks and cross-industry comparisons.

For leaders responsible for winning RFP-driven work, these figures provide a rare empirical grounding rather than anecdotal intuition.

We chose to highlight this report for three reasons:

1. It quantifies constraints that AEC leaders experience daily. The data shows that AEC firms pursue high-value RFPs with large, distributed teams, yet many still cannot complete a significant portion of incoming pursuits due to capacity limits. That creates measurable revenue exposure.

2. It situates AI adoption in operational reality. AI now appears in most proposal workflows and delivers measurable efficiency gains, but the data indicates that current usage does not yet translate into improved win outcomes.

3. It benchmarks performance across measurable dimensions. The survey provides figures on volume, win rates, contributor networks, tooling reliance, and content governance practices that AEC leaders can use as reference points for internal assessment across the broader proposal technology ecosystem.

This report moves the conversation about proposal operations from subjective feeling-based decisions to evidence-based analysis. We believe AEC leaders will find its insights essential for diagnosing capacity constraints, evaluating current practices, and prioritizing improvements that align with organizational growth imperatives.

The AEC Team Capacity Problem

AEC leaders often attribute proposal strain to cyclical demand, but the data indicate a structural constraint.

The benchmark report places AEC among sectors pursuing high-value RFPs, frequently in the $1M–$5M range and above. At the same time, most organizations report that they cannot complete 10–19% of incoming RFPs due to time or resource limits. When average opportunity values reach seven figures, incomplete coverage creates measurable exposure.

Proposal Coordination and SME Bottlenecks

AEC responses rely on broad contributor networks. Nearly two-thirds of respondents involve 11 or more people in RFP responses, and a significant share involve more than 20.

SME delays rank as the top reported challenge, followed by time spent locating and maintaining content. These figures identify coordination and information governance as the primary bottlenecks.

As contributor counts rise, review cycles lengthen and scheduling conflicts increase. Volume growth amplifies these effects. Drafting acceleration improves task efficiency, but orchestration discipline determines submission capacity. Firms must manage coordination as a system, not as a series of document edits.

AI Delivers Operational Gains, Not Yet Commercial Gains

AI adoption now spans most proposal workflows, and organizations most frequently apply AI to research, drafting, and quality checks.

AEC firms report meaningful improvements in drafting efficiency and staff time allocation, but fewer firms associate AI use with higher win rates or measurable revenue increases.

This pattern reflects usage maturity. Teams apply AI to accelerate execution, but far fewer integrate it into qualification logic, risk assessment, and structured evidence governance, which increasingly defines the difference between traditional tools and AI-native proposal engines. Without those extensions, efficiency gains do not translate into stronger competitive outcomes.

(Learn from QorusDoc's CEO, Ray Meiring, about winning RFPs)

Mature Organizations Instrument Proposal Operations

High-performing AEC firms treat proposal operations as revenue infrastructure. They measure contributor load, review cycle duration, and qualification accuracy. They embed AI into intake triage and structured content governance, and they create visible ownership across contributors and enforce disciplined workflows.

These practices increase submission reliability and improve alignment between effort and opportunity value. But each team’s submission capacity depends on orchestration discipline.

The stargazy Perspective

The benchmark data reinforces a pattern stargazy sees across proposal-driven sectors, not only AEC. Growth rarely fails because proposal teams cannot process the volume of qualified RFPs. High-value pursuits require large contributor networks, structured review cycles, and reliable content governance. Without orchestration discipline, proposal teams become the throughput bottleneck in otherwise strong revenue engines. For AEC firm leaders, the implication for you is straightforward! You must treat proposal operations as revenue infrastructure.

Why AEC Leaders Should Review the Full Report

AEC firms now operate in an environment where formal RFP processes govern a significant share of revenue. The benchmark data confirms that opportunity values remain high, contributor networks remain large, and capacity gaps persist. These dynamics create structural constraints that directly influence growth outcomes.

The report provides sector-level benchmarks on volume, win rates, automation maturity, contributor scale, and operational friction. Leaders can use these data points to assess whether their current proposal systems align with the economic weight of the work they pursue and to inform their broader proposal tech evaluation process.

The key question is diagnostic. Do current workflows, tooling, and governance practices support sustained growth at existing deal sizes and volume levels?

The full QorusDocs benchmark report offers the empirical detail required to answer that question rigorously. AEC leaders responsible for RFP performance should review the complete findings to benchmark their organizations and inform next-stage investment decisions.

Read the full 10th Annual Proposal Management Survey by QorusDocs to review the complete findings and compare your organization’s proposal performance against industry benchmarks.

The Proposal Technology Layer Behind Modern RFP Teams

Proposal operations increasingly rely on specialized software. These platforms manage response workflows, coordinate SME contributions, maintain answer libraries, and support drafting with AI assistance. In many organizations they function as the operational backbone for RFP execution.

The landscape of proposal technology now spans multiple categories. Some platforms focus on structured content libraries and response workflows. Others emphasize AI-native proposal engines that analyze RFP requirements, generate first drafts, and retrieve relevant institutional knowledge automatically. Many teams evaluate tools across this spectrum when modernizing their proposal process.

Leaders exploring this market often begin by mapping the broader proposal technology ecosystem and comparing how different platforms support qualification, drafting, collaboration, and governance. Stargazy maintains a continuously updated directory of proposal tools and analysis of how these technologies are reshaping RFP response operations.

Explore the full proposal technology landscape here: https://stargazy.io/proposal-tech

FAQ

What is the average proposal team size in AEC firms? The QorusDocs benchmark indicates that many proposal responses involve 11 or more contributors, with some teams involving more than 20 stakeholders across technical, pricing, and leadership roles.

Why do AEC firms struggle to respond to all RFP opportunities? Many organizations report they cannot complete 10–19% of incoming RFPs due to resource constraints, SME availability, and proposal coordination complexity.

How is AI used in proposal management today? Most organizations apply AI to research, drafting assistance, and quality checks. However, many firms have not yet integrated AI into qualification analysis or risk assessment.