How Generative AI Can Improve Responses to Tenders and Public Procurements?

What is a Tender?

A tender is a process where a buyer, often a public body or a large company, invites suppliers to submit offers for goods or services. This process usually starts with a request for proposal (RFP) or quotation (RFQ), detailing the required specifications. Suppliers evaluate these requests and, if they choose to participate, submit a proposal tailored to the buyer's needs.

The buyer then reviews all the proposals received and selects the one that best meets their criteria, often based on price, quality, and supplier experience. In public procurement, this process follows strict rules to ensure fairness and transparency, ensuring that all qualified suppliers have an equal chance to compete.

What is Generative AI?

Generative AI, like OpenAI's ChatGPT, Anthropic's Claude, and Google's Bard, represents a major advancement in artificial intelligence. These systems use deep learning models to generate text, images, and other content forms. They learn from vast data sets to imitate and reproduce language structures, visuals, or sounds, allowing them to create new and relevant content that seems naturally human.

In the context of tenders, these generative AI tools radically transform the way proposals are written. By analyzing the requirements of tenders and drawing inspiration from successful past responses, these systems help develop personalized and accurate documents.

How Can Generative AI Increase the Success Rate of Tender Responses?

Generative AI can improve the quality of proposals:

• Identification of Key Issues: AI automatically extracts key tender data, company-specific points of attention, and risks, facilitating quick understanding of technical requirements.


• Utilization of Relevant Context and Information: AI integrates contextual information about the buyer, economic conditions, and previous tenders, enriching the proposal.


• Reduction of Errors and Inconsistencies: AI ensures all tender requirements are addressed, minimizing errors and oversights in the response.


• Anticipation of Competitors' Responses: AI helps predict competitors' strategies, allowing for the development of more competitive and distinctive proposals.


• Compliance and Regulatory Update: AI maintains compliance with current regulations through constant updates, ensuring responses meet current standards.

How Generative AI Reduces Costs and Increases Productivity in Preparing Tender Responses?

Integrating generative AI in preparing tender responses enables rapid and efficient information search. Using an AI-powered search assistant, teams can instantly access relevant information in both current and historical tender documents. This ability to quickly find necessary data speeds up the preparation process and significantly reduces the time spent on manual information searches.

Generative AI also fosters increased collaboration and improved productivity within writing teams. It predicts actions, risks, and content relevance in tender documents automatically, thus increasing efficiency by over 25%.

AI also assists in document control and management, achieving up to a 75% reduction in time spent on document analysis, metadata extraction, and integration with document management systems. This process optimization and facilitated collaboration translate into significant time savings and operational cost reductions.

How Can Generative AI Help Identify the Most Promising Tenders for Your Business?

Generative AI provides an effective solution for identifying the most promising tenders for a business. This technology enables the centralization of all information and documents related to tenders in one place.

AI analyzes the content of past tenders and relevant keywords to automatically rank the most interesting opportunities. It allows the creation of unlimited search profiles to support different business units, incorporating various filters such as geographic location, publication date, and language, thus facilitating the selection of tenders most suited to the company's strategy.

How to Ensure Data Security Using Generative AI to Respond to a Tender?

To guarantee data security when using generative AI in tender responses, several key measures are essential. Firstly, the use of isolated data storage systems is crucial. This prevents data mingling and unauthorized access. Each client must have their own databases and storage spaces, ensuring that each tender's data remains secure and confidential. This segregation is fundamental for protecting the integrity and confidentiality of sensitive information.

Secondly, implementing robust encryption techniques is essential to protect tender data, both at rest and in transit. Encryption transforms data into an unreadable format, ensuring that even if intercepted, it remains inaccessible to unauthorized individuals. Furthermore, the application of advanced access controls and specific permission settings ensures that only authorized users can access relevant data, thereby reducing the risks of unauthorized modifications or data breaches. Additionally, maintaining detailed audit and activity logs helps detect any suspicious activity and strengthens the overall security of data.