Proposal Writing and Management: AI Change is Coming

The way we write and manage proposals in the legal and consulting industry is on the brink of a major transformation, thanks to the power of generative AI tools like Chat GPT-4 and Microsoft Copilot. These models can harness a firm’s content library and personalize content with information about clients and decision-makers. This will enable system-generated proposal drafts that effectively communicate solutions and capabilities in a way that stands out in a competitive procurement process.

As the synergy between human creativity and AI capabilities unfolds, proposal managers have a unique opportunity to upskill into a realm of heightened efficiency, creativity, and client-centric excellence. In this article, I’ll outline how I see generative AI changing the proposal industry, with specific reference to legal and consulting firms.

Generative AI has a role to play at each step – so let’s break it down.

1. Plan the proposal

In keeping with traditional best practice theories, “planning before writing saves more time than it takes” (Shipley Associates). Generative AI has a significant role to play in accelerating and supporting the initial planning phase. Here are some tips for where you can integrate generative AI to your processes:

• Reviewing RFP requirements: generative AI can scan RFPs to extract and consolidate the stipulated requirements, streamlining the proposal’s alignment with client expectations.
• Generating templates: by preparing a Word document in the firm’s designated template, generative AI sets the groundwork for a coherent and structured proposal.
• Creating a storyboard: generative AI can draft a storyboard that outlines the logical progression of the proposal, ensuring the narrative’s cohesion and compliance with the RFP.
• Creating a compliance checklist: generative AI can curate a comprehensive compliance checklist to guarantee that all mandated components are integrated into the proposal.
• Creating a project summary and brief: succinctly summarizing the project from the RFP and publicly available information, AI can compile a brief for dissemination among all stakeholders. It can also generate custom templates for meetings including qualification meetings and kick-offs and summarize the notes afterward.

Of course, proposal managers will have to review all outputs to ensure accuracy and appropriate tone; but harnessing the power of AI to structure their planning will give them more time to focus on stakeholder management and solution generation.

2. Draft the proposal

Generative AI can be programmed and prompted to access a firm’s content library. A content library typically contains the firm’s general information (reviewed by SMEs), experience, CVs, and examples of recently submitted proposals.

By tagging each content item with relevant information – such as the industry, practice area, type of advice provided, client, and date – generative AI can effectively search and filter content to produce a proposal that accurately represents the firm’s capabilities and experience.

Generative AI can leverage content libraries in various ways:

• Crafting standard responses to procurement questions: generative AI can draw upon a content library stored on platforms like SharePoint to draft responses to common RFP questions, such as those related to managing conflicts of interest or the firm’s policies on diversity and inclusion.
• Identifying relevant experience: by analyzing tags associated with previous proposals and matter-specific data in the content library, generative AI can identify the most relevant experience for a given proposal. This ensures the proposal highlights the firm’s expertise in areas aligned with the client’s needs.
• Drafting relevant biographies and CVs: generative AI can also use the content library to demonstrate the unique expertise of individual lawyers by showcasing their roles in relevant matters and illustrating their capacity to handle similar cases for potential clients. It can prepare a draft on why previous experience is relevant to the matter at hand.

With the first draft generated 20-50% faster, proposal managers will be able to invest more time in tailoring the content, bringing in relevant SMEs and identifying new content that may not have been included in the content library.

3. Understand the competition and tailor the proposal

Generative AI can play an active role in preparing a competitive analysis by:

• Searching for publicly available information: reviewing sources like company websites, industry reports and news releases, the AI can compile a view of competitors’ strengths, weaknesses, market positioning, and unique selling points. This information empowers firms to strategically position themselves in proposals.
• Collating and interpreting data: generative AI can extract valuable insights from capture and proposal activities and client conversations. It can then collate the data into a format that a proposal manager can draw on as they form the win strategy.

This data can contribute to crafting nuanced competitive analyses that inform proposal win strategies and tailor proposal content accordingly. Proposal managers will be able to leverage this information to facilitate win strategy workshops and test value propositions with key stakeholders. They will need to confirm the data being used is accurate and the content provided is appropriate to the current opportunity.

4. Understand decision-makers and tailor the proposal

In addition to leveraging in-house content libraries, generative AI can use publicly available information on clients and decision-makers to tailor the proposal. By analyzing online sources, such as company websites, press releases and social media profiles, generative AI can gain insights into clients’ preferences, pain points and decision-making criteria, enabling it to tailor the proposal accordingly.

There are solutions in development that will allow firms to gather relevant decision-maker data via a Client Relationship Management system (or similar). AI-enabled content marketing, data and analytics solutions can gain a deeper understanding of the decision-makers within their client base. With this feature, firms will gain access to decision-makers’ reading habits and interests. Imagine the advantage of understanding client preferences and delivering content that captures their attention!

Why not use generative AI to help you with:

• Aligning with client values: generative AI can use public information to identify the client’s values, mission and vision and ensure that the proposal’s content aligns with these elements. This demonstrates the firm’s understanding of the client’s needs and commitment to supporting their goals.
• Addressing pain points: public information can reveal clients’ pain points, which generative AI can use to craft a proposal that directly addresses these issues and offers tailored solutions. This shows the firm’s ability to empathize with clients and provide practical, relevant advice.
• Personalizing content and design for decision-makers: generative AI can also use this information to identify the key decision-makers involved in the proposal process and tailor the content to appeal to their preferences, communication styles and professional backgrounds. This increases the likelihood that the proposal will resonate with the individuals who ultimately make the decision to hire the firm.

This will offer proposal managers a huge advantage. It is currently very difficult to comprehensibly gather and use decision-maker intelligence. It will not replace the need for proposal managers to work closely with account managers and client relationship teams, who have personal experiences working with decision-makers.

5. Develop the price strategy and draft value for money response

AI models can automate tasks and provide data-driven insights for decision-making. Some ways it will be useful include:

• Benchmarking: by accessing data from various internal and external sources (including historical data and current market trends), AI will be able to benchmark current rates and proposed rates against competitors and other clients. This feature depends on the public availability of required data.
• Client conversations: AI can help account managers capture and transfer knowledge from client conversations to the proposal team to support the win strategy.
• Negotiations: AI can review contractual clauses and previous agreements to identify what has been agreed in the past and what position a potential new client might have. This information can empower pricing managers and partners to create offers more likely to be accepted by the decision makers.
• Prompting content based on opportunity data: AI can recommend pricing content for the proposal based on opportunity inputs.

Pricing and proposal managers will have a big role to play in providing and maintaining appropriate data access. They will maintain responsibility for the overall interpretation of the data and strategy, as well as clear communication with key stakeholders.

6. Reviews and signoffs

AI and automated project management tools can be integrated into the proposal process to automate various reviews and sign-off tasks based on pursuit requirements. For example, completing a task can trigger the sending of assignments or approval emails, ensuring that the proposal process runs smoothly and efficiently. This level of automation reduces the administrative burden on proposal writers and enables strong risk management through the approval process.

The material developed in the planning phase (the project brief and compliance checklist) can also be included to ensure all SMEs understand the scope and requirements of the RFP.

The AI model can assist the proposal managers in reviewing their work once completed to ensure it complies with the RFP and incorporates the overall win strategy. Proposal managers will be responsible for ensuring amendments are revisited by SMEs if required.

7. Editorial and design

Generative AI extends its influence into the editorial and design stages. It can:

• Enhance the proposal’s language: generative AI can review and make the language more active, remove repetition and restructure sentences to put the client first. This ensures the proposal is engaging and effective.
• Elevate design aesthetics: with insights from the understanding of decision-makers, AI-powered tools like Microsoft Copilot can enhance the visual design of proposals, aligning with decision-makers’ preferences.

Proposal managers need to upskill in design prompting to ensure outputs are appropriate and aligned with firm branding. It would be useful to invest time in guides, assets and templates to help instruct the AI model.

In conclusion

The landscape of proposal management and writing is on the brink of exciting change, powered by generative AI. Rather than replacing proposal managers, AI becomes a valuable collaborator, enhancing our ability to deliver exceptional results for clients.

By embracing AI, we can free ourselves from routine tasks and focus on strategic thinking and building client relationships.