Can AI Replace Proposal Writers?

Feb 13
4 min read

Updated: Feb 17

When you run a business, you make critical decisions every single day. Choices like where to place resources, when to hire, when to change or adapt are constant, and in the flurry of decisions handing your proposal writing to Artificial Intelligence might seem like an obvious one. The simplicity of tasking AI with writing proposals might seem obvious. After all, by virtue of their model, AI tools grow smarter every day and are often a useful tool as a starting point. But the real choice before business owners now is whether risking the outcome of a bid is worth placing on young technology that, as research suggests, still frequently falls short.

In other words: AI can write your proposal… but should it?

The AI Writing Copilot

AI can save your company time. A recent systematic review in academic writing found that AI tools could “significantly improve overall efficiency” across multiple stages of the writing process including idea generation, editing, or communication (“Artificial Intelligence in Academic Writing: Opportunities and Risks”).

Similarly, research on human-AI collaborative writing (Stanford’s CoAuthor dataset) shows many writers use AI suggestions as a starting point rather than final draft. The average human in the study wrote over 70% of their own content, editing AI output rather than copying it (Lee et al.). In proposal writing, the efficiency of this approach has obvious appeal.

The takeaway is simple: AI is useful for getting you started but falls short when it comes to meeting your specific criteria.

The Confident Mistakes

Context and Intent

Despite their benefits, AI models can get lost in the definitively human nuances of language. AI can struggle to grasp awareness of your company’s goals, industry subtext, and the strategic significance of certain proposal elements. The model’s approach might be the same for each section of the proposal, misunderstanding elements that are core to winning points and attracting buyers. For example, if a bid asks for “innovation,” AI might produce a generic paragraph about modern solutions, without tailoring the section to a strategic advantage. This type of risk analysis and judgement is still a fundamentally human capability.

Misinformation

Misinformation can present one of the largest risks for your company. Despite the constant, exponential growth of AI models, unverified information remains a major concern. AI systems are not infallible and may still present incorrect details, often referred to as “hallucinations.” But the risk goes beyond fabricated facts. AI can also misinterpret the inputs it’s given, misunderstanding the nuance of your business, your positioning, or the intent behind a requirement. A response may sound confident and well-written yet subtly miss the point of the question altogether. These errors can be difficult to detect without a human reviewer who understands both the content and the context.

Bias

AI models are not immune to bias, and the way that it may influence generative results proves a human review is essential. According to the American Psychological Association, algorithms can “promote discrimination or other forms of inaccurate decision-making that can cause systematic and potentially harmful errors” because the data they learn from carries human assumptions. In other words, AI reflects patterns in the data it was trained on, including the assumptions written into that data.

Human-AI Collaboration

You might be wondering if the solution is simply to have a human editor go over an AI generated proposal, but studies show that this can still fall short. Recent research from MIT Sloan found that human-AI collaborative teams didn’t always outperform the best of humans or AI working alone, stating that “…combining humans and AI to complete decision-making tasks often fell short” (Eastwood). MIT went so far as to state that human-AI teams’ work output was “statistically significantly worse”, based on more than 100 studies (Malone).

The Human Advantage

Strategic Interpretation

If you’ve ever written a proposal, you know that it’s more than a language puzzle the AI might comprehend and solve. Proposals are critical, strategic documents, with subtext still only grasped by writers experienced in the world of bidding. A human writer can interpret a bid's intent, anticipate evaluation pain points, and tailor a narrative to present your company in a way that AI simply isn’t equipped to do.

Persuasion, Selling, and Emotion

While AI can generate coherent prose and legible sentences, current models still lack an understanding of tone and emotions. And when it comes to the inherent sales pitch written between the lines of a proposal document, the persuasive art of writing a compelling and competitive proposal is of paramount importance. At this stage of AI language models, truly resonating with evaluators is still a skill that lies only in the hands of human writers.

Finer Details

Evaluating proposals is often a game of numbers, and if a document contains even the smallest mistake or discrepancy, the entire proposal itself may be disqualified. These critical details can range from compliance requirements and formatting rules to technical nuances, client-specific language, to even the subject line of a submission email. This comes down to another one of those many choices: if something as small as meeting a single requirement is critical to winning a proposal, would you prefer to leave that in the hands of a still developing model, or trust a human writer?

Where’s the balance?

While AI is a useful tool composed of coding and research, caring about your company’s future isn’t something it can ever be programmed to do. And at the end of the day, proposals aren’t written for machines, they’re written for people. That’s where the importance of a writer will continue to make a difference.

NVR

Bids & Proposals