The UK government is on a mission to digitise the public sector. That means getting rid of legacy procurement systems and replacing them with smart new tech that enhances operational efficiency, accuracy, and cost-effectiveness. It doesn’t necessarily include AI tech, but Artificial Intelligence is also on the agenda.
We’re going to look at the impact AI has on public sector procurement. How it affects tendering processes without veering into an ethical quagmire, and what we can see on the horizon.
Tendering in AI: Introduction to AI in Procurement
Artificial intelligence (AI) is transforming the procurement landscape by automating manual tasks, providing data-driven insights, and enhancing decision-making. It uses advanced technologies and algorithms to perform procurement functions traditionally carried out by humans.
The goal is to optimise resource allocation, enhance operations and supply chain management, and unlock new levels of performance. By leveraging AI, procurement teams can streamline processes, deliver cost savings, and improve supplier relationships.
AI in Tendering: Tender Responses
The quality of your tender response is almost as important as the quality of your tender. A lot is riding on your ability to follow instructions, understand the requirements, and sell your business through compelling writing.
Artificial Intelligence can help with all three of these elements.
Let’s start with understanding … understanding the procurement process, the market, the buyer, and the buyer’s requirements.
How does one gain understanding?
Through data, a lot of high-quality data.
The thing is, collecting and sifting through large amounts of data is time-consuming, boring (let’s be honest), and doesn’t always yield actionable results. For AI technologies, though, this kind of work is bread and butter.
They can quickly analyse huge chunks of buyer-related data, like news stories, bid history, and past and current projects. The insight from internal and external data enables you to personalise your bid by providing solutions that meet buyers’ exact needs, in language that makes sense to them, and which address broader social value and sustainability issues.
Delta eSourcing is a great example of a procurement platform with an array of services that enhance procurement operations, including Delta Data Market Analytics, which has particular value for framework tender opportunities.
Bid Writing
There are reams of data expounding the importance of bid writing and the wisdom of using bid writing specialists to improve your chances of winning lucrative contracts.
However, not all suppliers can afford to hire bid writers, nor do they have the time to spend working with professional writers to get every nuance right. Content-creating generative AI tools like ChatGPT can be a reasonable compromise.
Generative AI tools can suggest format, structure, and phrasing as a basis for your proposal. Natural language processing can even mimic language patterns and communication styles.
An important note: Don’t use generated AI content as gospel. Even the best mimic can miss details, speed past word count, and fail to consider elements that buyers have earmarked as high priority.
It’s your responsibility to check the bid before submission to ensure it meets the contract’s requirements. You can’t go back and say, “Oops, the AI made a mistake. Can I have another chance?”
AI in Tendering: Transparency Requirements in Procurement Processes
The Procurement Act 2023 is all about transparency. Transparency is necessary to keep the public’s trust, to ensure fair tender evaluation and supplier selection, and to prevent fraud and corruption.
AI enters the picture, and transparency becomes opaque. Who knows what’s real and what’s AI? Knowing the difference is crucial to fair procurement processes. So, the government published PPN 02/24: Improving Transparency of AI Use in Procurement.
It covers AI in bid writing and evaluation and AI as a service/product or part of a service/product.
Technically, suppliers are allowed to use AI in their tender responses without prejudice from buyers. This means that even if buyers ask suppliers if they’ve used AI to help develop their response, they can’t penalise suppliers when the answer is yes.
On the other hand …
It could be argued that buyers have a right to be suspicious for three main reasons:
- AI is only as smart as the data it’s fed. Sometimes data is bad – inaccurate, false, incomplete, or out of date – which affects the validity of the data in a proposal. It’s up to the procurement team to ensure data quality before submitting the proposal.
- AI uses open-source data, which means that, in theory, all suppliers responding to the same contract have access to the same information. This can lead to conformity in responses, making it difficult to tell bidders apart, let alone evaluate each answer on its merits.
- There’s a question mark over data security. Have the AI tools used been tested and certified for data protection and cyber security measures? Is private or sensitive data at risk of exposure?
These challenges to the widespread adoption of AI for procurement purposes must still be overcome. The answers could lie in the AI Opportunities Action Plan, published on January 13 2025, by the Department for Science, Innovation, and Technology (DSIT), but that’s a discussion for another time.
AI in Tendering: What Does it Look Like?
What we can say about the plan is that proposed AI solutions have the potential to shake up the public procurement landscape a little bit more. For instance, it proposes a new tendering model that entails frequent, small-scale tenders for rapid prototyping.
The new AI procurement model encourages close collaboration between buyers and suppliers to get projects from the drawing board to the market.
The plan also recommends adopting faster procurement cycles. This entails multi-stage, gated, scaling AI procurement processes that eliminate a lot of tedious red tape. Basically, it simplifies the process for SMEs and startups to enter the market, but as the pilots scale up, procurement professionals are bound by tighter controls.
AI in Tendering: Public Procurement Marketing and Supplier Targeting for Procurement Professionals
We’ve mentioned AI technologies’ ability to crunch volumes of data to deliver meaningful information that supports the use of AI solutions in public sector procurement. AI tools have become a valuable asset in modern marketers’ approach to public sector marketing. The primary ways in which AI assists marketers is through deep data analysis, predictive analytics and modelling, and automation.
Deep data analysis, for example, uses AI algorithms to crunch supplier data (performance, financial well-being, compliance, etc.) for precision supplier targeting. Artificial intelligence compares this supplier data to contract requirements, finding the best match for specific tenders. This enables the procurement team to make strategic tender-related decisions.
It also identifies potential supplier risks so buyers can weigh the overall value of a tender against the time it takes to develop a risk mitigation strategy.
If the decision is in favour of the supplier, automation can step in and manage the bulk of contract creation, graduating into routine supplier management tasks.
Another benefit is demand forecasting. Advanced analytics uses historical data to identify trends and patterns in the marketplace, enabling artificial intelligence to predict future demand. Marketers can prepare flexible long-term strategies to optimise upcoming opportunities.
(Flexible because the future is fluid and marketers need to adapt to changing markets and changes in demand.)
AI in Tendering: A Final Word
AI in tendering is moving from a contentious issue to best practice. There are still plenty of challenges and pitfalls, but with the right tools and training, all public procurement stakeholders can benefit from deep data analysis, precision targeting, more efficient operations, and insightful decision-making.
One thing is clear: AI is fab, but it still needs human intervention to optimise its benefits. Currently, those in public sector procurement need to use AI with a touch of scepticism to ensure compliance with all procurement regulations. This includes transparency, ethics, accuracy, and data quality.
We can address these potential risks by providing AI algorithms with clean data and creating a suitable learning environment for AI to continuously develop and improve.
If you have any questions about incorporating AI into your public procurement marketing strategy, book a free demo with Cadence Marketing. Backed by our partner company, BiP Solutions, we have decades of experience in the B2G market and can help you optimise your campaigns for maximum reach and effect.
