Crafting compelling proposals that stand out from your competition is time-consuming, often requiring extensive research, creativity, and meticulous attention to detail. To make things even worse, most bid and proposal professionals are stretched thin, struggling to juggle all their responsibilities and respond to an ever-increasing number of RFPs. However, with the advent of generative AI, the proposal industry is in the midst of a profound transformation that seeks to streamline the RFP process while enhancing proposal automation.

The rise of artificial intelligence for the proposal process

By now most people have heard of artificial intelligence. It’s the newest technology that’s reshaping the landscape of multiple industries. For the proposal industry, generative AI models are currently being used in two ways:

1. To quickly generate responses, answers, and other content pieces to use in proposals.
2. To analyze RFPs and automatically generate initial drafts of proposals based on the outlined criteria.

We’ve written before about how generative AI L can be used to quickly generate new responses & sales proposals, but equally as important is the ability to scan and analyze initial RFPs. To do this, artificial intelligence models use large datasets of successful past proposals, RFPs, and industry knowledge to automatically generate relevant content.

Analyzing the initial RFP, artificial intelligence can seek to understand each unique opportunity, evaluate their requirements and evaluation criteria, and generate a draft response with relevant details, examples, and explanations.

These automatic drafts provide a quicker starting point for proposal teams, allowing them to spend less time gathering initial content and more time refining and customizing.

However, the power of artificial intelligence can extend beyond generating new responses and scanning RFPs. Used in combination with human expertise and industry-knowledge, AI can enhance proposal content, leading to increased win rates. Here are five additional ways you can use generative AI to enhance your proposals.

Five ways generative AI enhances proposal automation

1. Increasing personalization

As every bid and proposal professional knows, personalization is key to winning business. Proposals that lack personalization are less likely to stand out from their competition, resulting in fewer wins. While automation paired with a robust content library already makes personalization easy, generative AI takes it even further by dynamically adapting content based on specific requirements outlined in the initial RFP.

Using the content in your library and the analyzed RFP, generative AI can craft answers, introductions, or other content pieces in seconds that are tailored to each unique client.

2. Improving consistency

Let’s be honest: your probably not the only one working on your proposals. Regardless of your company size, proposals often go through multiple different reviewers or stakeholders. Unfortunately, as the number of people working on a proposal increases, the consistency of the overall document often decreases.

Generative AI models can help eliminate this pain point for professionals while maintaining consistency across the proposal. How? AI models use the data or content stored in your library to generate new responses. By using a large set of data, these models are able to get a feel for the average tone, style, and voice your company regularly uses on proposal content.

Unlike your other team members and stakeholders, who often have wildly different styles of writing, AI models rely solely on the data provided. Additionally, if content pieces don’t seem consistent, it’s easy to generate new ones that do.

3. Decreasing time spent on proposals

Quick question: how long do you typically spend on a proposal? Based on our industry knowledge, even professionals that use some form of proposal automation still spend hours writing, researching, and rewriting content. Generative AI cuts time spent in half (or more), by quickly generating initial content pieces and suggestions. This quick content generation makes it possible for overtaxed teams and organizations to meet tight deadlines without compromising quality.

4. Quality Assurance

While AI might seem like a brand new concept, some form of it has been around for decades now. One way professionals across all industries are used to interacting with AI is through pieces of quality assurance software, like spell checkers, grammar plugins, and more.

Generative AI can also be used to improve overall quality by conducting real-time quality assurance checks and flagging content pieces for inconsistencies, inaccuracies, and potential errors. This helps proposal writers produce more polished and error-free proposals.

5. Data-Driven Insights.

Generative AI models are already designed to analyze large data sets and provide content that mimics human language. This same type of large-data analysis can be used to help proposal teams make more data-driven insights.

For example, teams can use the vast amounts of data available to them in their content library or proposal software in combination with generative AI to provide crucial insights and recommendations for optimizing proposal content. This data-driven approach enables organizations to continuously improve their proposal writing strategies and increase their chances of winning bids.

Generative AI and the future of the proposal process

As generative AI models, like Qvidian AI Assist, continue to improve, these models will likely produce increasingly sophisticated drafts that require less revision. However, human judgement, creativity, and strategic thinking is always a vital part of the proposal process. Bid and proposal specialists working in collaboration with generative AI tools will help push the industry forward, leading to overall enhancements in the proposal automation industry that save time and increase win rates.