AI in Bid Writing: Making the Most of ChatGPT

AI in Bid Writing: Making the Most of AI

Public sector tendering grows more competitive each year, with bid teams constantly juggling quality demands against ever-tightening deadlines. The arrival of AI tools like ChatGPT has presented an intriguing possibility for those in the tendering world – could this technology help produce better bids in less time? As professional tender writers and public procurement consultants, we've seen firsthand how organisations are incorporating these tools into their bid processes – but often with underwhelming outcomes...

This guide explores what we've learned about AI's role in bid writing, drawing on our experience of reviewing hundreds of tender responses, some drafts and final responses clearly produced with quite a bit of AI assistance. We'll share practical advice on making these tools genuinely useful while avoiding the common pitfalls that consistently lead to poor evaluation scores. We'll also introduce how purpose-built solutions like Tender Library offer significant advantages over generic AI tools for serious bid professionals.

Thornton & Lowe?

Thornton & Lowe is a bid management consultancy - we provide bid writing services to our clients. As a company that directly employs bid writers and bid managers, offering outsourced services to businesses looking for consistent, high-performing bid support, you might wonder why we're discussing AI tools that could potentially reduce the need for our services. The answer is simple – while we believe in embracing technologies that improve the bid process, we also recognise their limitations!

Most clients looking for bid and tender writing support - often have many previous bids. These, as a starting point, are far better as a starting point than any ChatGPT AI bid writing efforts. Our value is in ensuring the content is right. Is tailored, relevant and fit for purposes considering the context of our client, their challenges and USPs, the wider competition - and yes - what the buyer actually wants!

We have been at the forefront of bid innovation for over a decade. We developed our Tender Library software over 10 years ago as a way to manage previous bid content, and it has recently undergone a significant uplift to include several AI tender writing and bid review elements - but 100% not as a replacement for expertise.

For Tender Library users, you benefit from combining the best of human expertise with advanced tools and carefully selected AI applications. For clients with established bid libraries, we use Tender Library to efficiently access and adapt their proven content. For newer clients, we draw on our extensive experience and template resources to quickly develop high-quality responses. In both cases, we use AI tools strategically – for structural assistance, requirement analysis, and quality enhancement rather than content generation. The reality is that winning bids still requires genuine expertise, specific evidence of capability, and tailored approaches based on real experience. No AI tool can replace these elements – but the right tools can help us deliver them more efficiently and effectively.

Benefit from AI efficiencies whilst maintaining the human touch. Quickly upload and organise your bespoke, manually drafted bids, then use our intelligent AI review tools to refine your work. Merge multiple responses to update content - whilst staying fully in control of your message.

What We're Seeing in AI-Generated Bids

Having evaluated bids for years, we've now developed a keen eye for AI-generated content. The telltale signs have become increasingly familiar – responses that seem comprehensive at first glance but lack the specificity and depth that indicate genuine expertise and experience.

You might recognise these characteristics in bids you've encountered: responses filled with broad statements about processes and methodologies without concrete examples; answers that restate the question rather than demonstrating understanding; case studies with suspiciously generic details; lists; more lists; and text that reads smoothly but somehow feels hollow of actual substance. The occasional 'z' included in 'organizations' (ChatGPT - we said British English... we like 's').

When we analyse these submissions, we consistently find they fall short on the elements evaluators value most. They lack organisation specific information that demonstrates genuine capability. They offer theoretical approaches instead of proven methodologies. They make claims without substantiating evidence. They miss nuanced aspects of requirements that aren't explicitly stated but are nonetheless important to the contracting authority. We need our bid writing to be 'real'. If it is not believable - which procurement team would ever award you a contract?

We will now examine how to try and remove this 'AI fluff' and really benefit from the solution as a bid writing tool.

Where AI Can Actually Help Your Bid Process

Despite these shortcomings, we've also seen thoughtful applications of AI that genuinely enhance the bid development process. The key lies in understanding which tasks AI handles well and which require human expertise and experience.

AI excels at helping you build initial frameworks for your responses (your storyboard). You might also ask it to suggest a structure for addressing a particular evaluation criteria, ensuring you consider all relevant aspects in your response. This can help prevent those late night realisations that you've missed addressing a key requirement.

It's also not bad at analysing evaluation criteria. You could simple provide a draft response along with the scoring criteria and assess it's improvement suggestions. You could ask it to identify both stated and unstated requirements within a specific area of a question, or to suggest what evidence would best demonstrate compliance. This analytical perspective can be particularly helpful when dealing with unusually worded or complex requirements.

AI bid reviews really can add value and act as a training tool for more junior members of the team to ensure consistency. Once you've written a response (using your organisation's genuine experience and expertise), AI can review it for completeness, suggesting areas where you might strengthen your evidence or clarify your approach. It can help identify potential gaps in your response or suggest alternative ways to structure or present your information for greater impact. A refined, secure and T&L trained version of this is also available within our Tender Library.

We've also seen the benefits of using AI for compliance checking – running completed responses against the original requirements to ensure they've addressed all aspects. This can help catch oversights before submission, particularly in complex tenders with numerous detailed requirements. However, see details below in terms of ensuring you protect your data!

Where teams get into trouble is when they rely on AI to generate the substantive content of their tender responses – the specific methodologies, the evidence of capability, the case studies, and the tailored approaches that distinguish winning bids from the rest.

The Genuine Limitations of AI in Bid Writing

Understanding the specific limitations of AI in the bid context helps explain why over-reliance leads to poor outcomes. These aren't just theoretical constraints – they're practical issues we observe regularly in submitted tenders.

Perhaps the most significant limitation is AI's inability to consistently provide the specific detail and evidence that evaluators seek. Public sector evaluation methodologies typically award higher scores to responses that demonstrate specific, relevant experience and tailored approaches. However, AI systems can only generate content based on their training data – they cannot access your organisation's unique experience, methodologies, or past performance. If you provide this data, along with specific prompts it can often create something which is a better base but rarely in a consistent format. Even with constant reminders.

The technical accuracy of AI-generated content also presents problems in specialist sectors. We've seen responses that confidently reference outdated regulations, combine elements from different frameworks, or provide plausible-sounding but incorrect technical explanations. In specialised tenders where evaluators are buying your knowledge, these errors severely undermine credibility.

Another significant limitation is AI's understanding of public sector priorities and contexts. Even when not explicitly stated in tender documents, factors like social value, equality considerations, sustainability goals and alignment with broader policy objectives often influence evaluation decisions. AI typically fails to address these nuanced aspects without specific prompting, and even then, provides generalised rather than contextually appropriate responses.

Tender Library: A Purpose-Built Solution for Bid Professionals

While generic AI tools have their place, purpose-built solutions like Tender Library offer significant advantages for serious bid professionals. Developed by Thornton & Lowe over a decade ago and recently enhanced with advanced AI capabilities, Tender Library was originally designed to help our own bid teams efficiently manage and leverage previous bid content.

Unlike generic AI tools, Tender Library doesn't just generate plausible-sounding text – it helps you find and repurpose your organisation's actual proven bid content. Using AI-enhanced vector searches, the system allows you to quickly locate relevant responses from your previous successful bids, providing content that's already tailored to your organisation's capabilities and experience.

For teams without an extensive bid history, Tender Library includes a database of over 150 of the most frequent UK procurement questions with template responses. These aren't generic AI outputs, but carefully crafted responses that provide a robust starting point far closer to a winning submission than what you'd get from ChatGPT or similar tools.

The platform also integrates our Tender Pipeline feature, allowing you to find new opportunities in the same environment where you develop your responses. This integration streamlines the entire bid process, from opportunity identification through to submission. View our bid software and services.

What makes Tender Library particularly powerful is how it combines AI capabilities with your organisation's genuine experience and expertise. Rather than generating fictional case studies or generic methodologies, it helps you use content that has been refined over time based on actual buyer feedback and competitive analysis. This content includes the specific details, proven approaches, and genuine evidence that evaluators look for – elements that generic AI simply cannot provide.

For new bidders, Tender Library's template responses serve as both a guide to what should be included and a substantial time-saver. For experienced bidders, the AI-enhanced search capabilities make it easier than ever to find and adapt your best previous content, significantly reducing the time spent recreating similar responses across multiple bids.

Developing a Sensible Approach to AI in Bid Writing

Based on our experience both using and evaluating AI-generated content, we've developed some practical guidance for integrating these tools effectively into bid processes.

Establish Clear Policies on AI Use

The foundation of successful AI use in bid writing is a clear policy on when and how it should be employed. This needn't be complicated – simply defining which aspects of the bid process can benefit from AI support and which require human expertise provides necessary guardrails. For example, you might specify that AI can be used for initial response structuring and requirement analysis, but not for generating case studies or evidence of capability.

This aligns with the UK government's approach - "suppliers' use of AI is not prohibited during the commercial process but steps should be taken to understand the risks associated with the use of AI tools in this context, as would be the case if a bid writer has been used by the supplier." The government recognises the potential benefits of AI in enabling suppliers to bid for more public contracts, but notes the importance of transparency and risk management.

Address Data Security Considerations

Your policy should also address data security considerations. Be mindful of the information you input into public AI systems, avoiding confidential client information, commercially sensitive pricing details, and personal data. Remember that information provided to public AI systems may be used in their training data, potentially making it accessible to competitors in future.

The AI Playbook emphasises this concern, noting that when using public AI applications, you must "not enter any official information directly into public AI applications or APIs unless it's already publicly available or cleared for publication."

Establish a Review Process for AI-Generated Content

Equally important is establishing a review process specifically designed to enhance AI-generated content. This should focus particularly on adding specificity, incorporating genuine organisational experience, ensuring technical accuracy, and aligning with evaluation criteria. The goal should be transformation rather than minor editing – taking AI-generated frameworks and infusing them with your organisation's actual capabilities, experience, and evidence.

This approach supports the principle in the Guidelines for AI Procurement that organisations should "ensure that you will be able to explain, justify and take responsibility for decisions that are made or assisted by the AI system."

Build Resources to Support Content Enhancement

Building resources to support this enhancement process pays dividends. Developing a library of detailed case studies, quantified performance data, technical methodology documents, and client testimonials provides the raw material needed to transform generic AI frameworks into compelling, evidence-based responses. These resources help your team efficiently incorporate specific, credible content that addresses evaluators' key concerns.

Purpose built solutions like Tender Library are invaluable here, as they help you find and repurpose your actual proven bid content rather than relying on generic AI outputs.

Train Your Team in Effective AI Use

Training your team in effective AI use represents another valuable investment. This should focus on creating effective prompts that generate useful outputs, critically evaluating AI-generated content, and efficiently enhancing that content with organisation-specific information. The goal is to maximise the efficiency benefits of AI while ensuring your submissions maintain the specificity, evidence, and technical accuracy that win contracts.

Contact us and we can discuss AI bid writing training options, which are included within our core sessions, as well as bespoke (in-house) sessions dedicated on AI for your bid teams).

The AI Playbook notes that "You should gain the skills needed to use, design, build and maintain AI solutions," emphasising that different skills are needed for different applications of AI. For bid teams, this means understanding how to effectively use AI as a tool within your specific context rather than trying to become AI experts.

Track and Document AI Use

As public sector procurement increasingly requires transparency around AI use, consider implementing a tracking system to document where and how AI has been used in developing bid responses. The Algorithmic Transparency Recording Standard (ATRS) could provide a useful model, even for internal documentation.

This proactive approach will help you respond to questions that may arise during tendering, which requires suppliers to answer questions for buyers and identify use of AI in procurement responses, for example.

Practical Applications: When to Use Generic AI vs. Tender Library

Understanding when to use generic AI tools like ChatGPT versus purpose-built solutions like Tender Library can help improve your bid process:

• For teams with substantial bid history: Your previous bid content will almost always outperform generic AI outputs. Using Tender Library to find and adapt your past successful responses is typically the most efficient approach. Your content has already been refined based on buyer feedback and competitive analysis – it's specific, proven, and tailored to your organisation's capabilities.

• For new bidders: Tender Library's database of template responses for common UK procurement questions provides a far stronger starting point than generic AI. These templates give guidance on what to include while saving substantial time compared to starting from scratch.

• For structural assistance: Generic AI tools can help structure responses to complex requirements. Provide the AI with detailed specifications and evaluation criteria to generate a comprehensive framework, then populate it with your specific methodologies and genuine case studies.

• For analysis and review: Both generic AI and Tender Library can assist with analysing evaluation criteria and reviewing draft tender responses. Use them to identify implicit requirements, check compliance, and highlight opportunities for strengthening evidence or clarifying approaches.

• For improving existing content: When you have relevant previous content but need to adapt it for a new requirement, you can use your original bid as context for AI tools to help with the adaptation. The result will be far closer to a winning response than starting with generic AI alone.

A Practical Guide to Effective AI Prompts for Bid Writing

The way you interact with AI tools significantly affects the quality of the outputs you receive. Good prompts are the key! They can generate genuinely useful content that saves time and improves the quality, while poor prompts often produce generic content that requires substantial reworking.

The AI Playbook emphasises that "the value of these interactions depends on the quality of your follow-up" and notes that AI suggestions should be "starting points for further development, not final content." This is especially important in bid writing, where specificity and evidence are often the key!

Structuring Your Response

When seeking help with structuring your response, provide specific context about the requirement and evaluation criteria rather than asking for generic frameworks. For example, instead of asking "How should I structure a response about project management?", try:

"How should I structure a response addressing this criteria: 'Demonstrate your approach to managing a multi-site facilities maintenance contract with varying response time requirements'? The contract requires 24/7 coverage across five locations with different priority response times based on criticality. I am bidding for a contract for a Council and the following scoring criteria is what creates an excellent responses - XXXX"

The additional context helps the AI generate a more tailored structure that anticipates the specific aspects evaluators will be looking for. Additional context may also include information about your business or about the specific contract. For example, you know the incumbent is underperforming and during a site visit you identified key areas you would want to improve during the mobilisation. Great - include it. Then review the draft you get from ChatGPT - edit it ensuring it fully reflects both what you wanted to say and the way you wanted it to come across.

Evaluation Criteria Analysis

For evaluation criteria analysis, share the exact wording of the criterion and ask the AI to identify both explicit and implicit requirements. You might ask:

"What are the stated and unstated elements evaluators might be looking for in this criterion: 'Outline your approach to ensuring service continuity during staff absence'? This is for a public sector healthcare contract where reliability is critical."

The AI Playbook notes that this analytical perspective can be particularly helpful when dealing with "unusually worded or complex requirements."

Content Improvement

When seeking content improvement suggestions, provide your draft response alongside the original requirement and ask for specific types of enhancement. For instance:

"Here's my draft response to the question 'Demonstrate your experience in delivering similar services'. How could I improve the specificity of my evidence and strengthen the demonstration of relevant experience? Please focus on making sure our case studies explicitly address the key requirements of this bid."

This specific guidance helps the AI focus on the most important aspects of improvement rather than making generic suggestions.

Compliance Checking

For compliance checking, include both the full requirement and your complete response, asking the AI to identify any aspects you may have missed or inadequately addressed:

"I've provided the full requirement section and our complete response below. Please identify any aspects of the requirement that we haven't adequately addressed, any claims we've made without supporting evidence, or any areas where we could strengthen alignment with the evaluation criteria."

The AI Playbook notes that this approach can "help catch oversights before submission, particularly in complex tenders with numerous detailed requirements."

Prompting with Previous Successful Bids

A particularly effective approach mentioned in the Playbook is using your previous successful bids as context for AI assistance:

"I'm providing our previous successful bid for a similar service. Please analyse this and suggest how we could adapt it for our new bid, which has these additional requirements [list requirements]. Please maintain the specific evidence and case studies while suggesting where we need to add new content to address the different aspects."

You may find it quicker to use this as a base and tailor yourself.... but asking it to highlight how it could be tailored considering the new specific contract you are bidding for, or the question you are working on.

Using AI Responsibly in Bid Development

The most effective approach involves an iterative process where there is:

• Human input
• AI helps analyse and structure
• Humans provide more specific content and evidence
• AI then helps refine and develop that content
• Humans review fully - editing and changing as they go.

As the AI Playbook emphasises, "The organisations that benefit most from AI in their bid processes will be those that understand both its capabilities and its limitations."

The Guidelines for AI Procurement also stress the importance of maintaining human expertise: "Consider how you will ensure that your team maintains the ability to explain, justify and take responsibility for decisions that are made or assisted by AI systems." This is crucial for bid teams, who must ultimately be able to defend and explain every aspect of their submissions.

The Evolving Role of AI in Bid Writing

AI tools will continue to develop, and their role in bid writing will evolve accordingly. Future versions may address some of the limitations we've discussed, potentially offering more sophisticated support for bid development. However, the fundamental principle emphasised throughout the AI Playbook and Guidelines for AI Procurement remains unchanged: AI works best as a complement to human expertise, not a replacement for it.

It notes, "The organisations that benefit most from AI in their bid processes will be those that understand both its capabilities and its limitations." This is particularly true in bid writing, where success depends on demonstrating genuine understanding, expertise, and relevant experience.

The most forward-thinking bid teams will use AI to enhance efficiency in appropriate areas while ensuring their submissions retain the specific evidence, tailored approaches, and technical accuracy that evaluators value. They'll also use purpose-built solutions like Tender Library that combine AI capabilities with organisational knowledge assets.

These teams will maintain a focus on building and documenting their genuine capabilities and experience.

Bid writers should also stay informed about evolving government frameworks like the AI Management Essentials and the Algorithmic Transparency Recording Standard (ATRS). Understanding these developments will help bid teams not only leverage AI effectively in their own processes but also demonstrate compliance with emerging requirements in their submissions.

In essence, AI represents a potentially valuable addition to the bid writer's toolkit, but it doesn't change the fundamental elements of a winning submission. The most successful bids will still be those that demonstrate genuine understanding of requirements, propose tailored approaches based on relevant experience, and provide specific evidence of capability and past performance.

By developing a thoughtful approach to integrating AI into your bid processes – using them where they add value while compensating for their limitations – you can improve both the efficiency and effectiveness of your tender responses, ultimately improving your costs of bidding in public sector procurement.