AI has transformed proposal work. Tools can draft content, run compliance checks and generate first drafts in minutes, not days. Or so the narrative goes, according to most AI vendors.

Our tenth annual survey of nearly 300 proposal leaders tells a different story. Proposal roles have fundamentally changed, but demand is rising faster than automation can keep up. More than two-thirds of respondents (68%) reported year-over-year growth in proposal volume, while 63% said the same about RFP responses. Growing RFP volumes have driven a 25 to 50% workload spike for proposal teams at most firms, even as they deploy more AI.

Proposal professionals have never been more indispensable. That’s because winning has never been about generating content – it’s about orchestrating the right people, information and decisions.

The Real Bottleneck: Orchestration, Not Writing

AI has automated drafting and summarizing content, but the real friction in proposal management lies in coordinating busy subject matter experts, chasing approvals, and locating accurate content across siloed systems. SME delays and time spent locating or maintaining content were the top pain points for proposal leaders we surveyed.

The average RFP response still takes about one to two weeks and requires anywhere from six to more than a dozen contributors to get over the finish line. For organizations handling the typical five to nine RFPs monthly, the chaos compounds quickly at the organizational level.

These coordination gaps go beyond operational headaches to create material business risks. In professional services, for example, the typical opportunity ranges from $1 to $5 million in revenue potential. Missing even one response monthly can put tens of millions of dollars in annual revenue at risk.

AI Adoption Accelerates, but Maturity Lags

Most proposal teams use AI, but many have not yet reached full automation maturity. We found that nearly three-quarters of organizations (73%) have automated at least a quarter of the proposal process, but most can’t respond to between 10 and 20% of incoming RFPs due to bandwidth.

One of the biggest barriers is tool fragmentation. Many proposal teams rely on general productivity software requiring manual collaboration and handoffs, rather than integrated systems that centralize content, collaboration and governance. This results in siloed information that’s difficult to find, repurpose and govern at scale.

Additionally, proposal teams lack the feedback loops needed for continuously improving AI systems. While nearly 90% told us it’s important to include ROI or business cases in proposals, more than 25% said measuring effectiveness remains elusive. They simply don’t know what drives win rates.

The Next Frontier: From Document Production to Revenue Orchestration

Over the past decade, proposals and RFPs have moved from a back-office task to a primary driver of revenue. Our research shows that proposals are central to revenue generation, with a significant amount of new and existing client sales coming from winning RFPs.

As AI-driven proposal management matures, proposal professionals will shift further from repetitive, tedious work, like answering RFP questions, to revenue orchestration and measurable decision enablement. Their value will lie in shaping strategy, driving client relationships and ensuring proposals are tightly linked to business outcomes.

When systems are integrated – connecting proposal tools to knowledge management and ROI modeling – AI can reliably handle the mechanical work of proposals. That frees humans to focus on the client context, differentiated narratives and complex decisions that ultimately win deals.

The next phase of proposal work won’t be defined by who uses AI, but by who turns AI into a coordinated system. Firms that integrate AI across people, content and process will be able to scale without scaling risk; those that treat it as a content-generating feature will hit a ceiling.