More generally, the AI PPN is bound to be controversial and has already spurred insightful discussion on LinkedIn. I would recommend the posts by Kieran McGaughey and Ian Makgill. I offer some additional thoughts here and look forward to continuing the conversation.
In my view, one of the potential issues arising from the AI PPN is that it aims to cover quite a few different aspects of AI in procurement, as well as neglecting others. Slightly simplifying, there are three broad areas of AI-procurement interaction. First, there is the issue of buying AI-based solutions or services. Second, there is the issue of tenderers using (generative) AI to write or design their tenders. Third, there is the issue of the use of AI by contracting authorities, eg in relation to qualitative selection/exclusion, or evaluation/award decisions. The AI PPN covers aspects of . However, it is not clear to me that these can be treated together, as they pose significantly different policy issues. I will try to disentangle them here.
Buying and using AI
Although it mainly cross-refers to the Guidelines for AI procurement, the AI PPN includes some content relevant to the procurement and use of AI when it stresses that ‘Commercial teams should take note of existing guidance when purchasing AI services, however they should also be aware that AI and Machine Learning is becoming increasingly prevalent in the delivery of “non-AI” services. Where AI is likely to be used in the delivery of a service, commercial teams may wish to require suppliers to declare this, and provide further details. This will enable commercial teams to consider any additional due diligence or contractual amendments to manage the impact of AI as part of the service delivery.’ This is an adequate and potentially helpful warning. However, as discussed below, the PPN suggests a way to go about it that is in my view wrong and potentially very problematic.
AI-generated tenders
The AI PPN is however mostly concerned with the use of AI for tender generation. It recognises that there ‘are potential benefits to suppliers using AI to develop their bids, enabling them to bid for a greater number of public contracts. It is important to note that 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 bidder.’ It indicates some potential steps contracting authorities can take, such as:
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‘Asking suppliers to disclose their use of AI in the creation of their tender.’
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‘Undertaking appropriate and proportionate due diligence:
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If suppliers use AI tools to create tender responses, additional due diligence may be required to ensure suppliers have the appropriate capacity and capability to fulfil the requirements of the contract. Such due diligence should be proportionate to any additional specific risk posed by the use of AI, and could include site visits, clarification questions or supplier presentations.
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Additional due diligence should help to establish the accuracy, robustness and credibility of suppliers’ tenders through the use of clarifications or requesting additional supporting documentation in the same way contracting authorities would approach any uncertainty or ambiguity in tenders.’
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‘Potentially allowing more time in the procurement to allow for due diligence and an increase in volumes of responses.’
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‘Closer alignment with internal customers and delivery teams to bring greater expertise on the implications and benefits of AI, relative to the subject matter of the contract.’
In my view, there are a few problematic aspects here. While the AI PPN seems to try not to single out the use of generative AI as potentially problematic by equating it to the possible use of (human) bid writers, this is unconvincing. First, because there is (to my knowledge) no guidance whatsoever on an assessment of whether bid writers have been used, and because the AI PPN itself does not require disclosure of the engagement of bid writers (o puts any thought on the fact that third-party bid writers ma have used AI without this being known to the hiring tenderer, which would then require an extension of the disclosure of AI use further down the tender generation chain). Second, because the approach taken in the AI PP seems to point at potential problems with the use of (external, third-party) bid writers, whereas it does not seem to object to the use of (in-house) bid writers, potentially by much larger economic operators, which seems to presumptively not generate issues. Third, and most importantly, because it shows that perhaps not enough has been done so far to tackle the potential deceit or provision of misleading information in tenders if contracting authorities must now start thinking about how to get expert-based analysis of tenders, or develop fact-checking mechanisms to ensure bids are truthful. You would have thought that regardless of the origin of a tender, contracting authorities should be able to check their content to an adequate level of due diligence already.
In any case, the biggest issue with the AI PPN is how it suggests contracting authorities should deal with this issue, as discussed below.
AI-based assessments
The AI PPN also suggests that contracting authorities should be ‘Planning for a general increase in activity as suppliers may use AI to streamline or automate their processes and improve their bid writing capability and capacity leading to an increase in clarification questions and tender responses.’ One of the possibilities could be for contracting authorities to ‘fight fire with fire’ and also deploy generative AI (eg to make summaries, to scan for errors, etc). Interestingly, though, the AI PPN does not directly refer to the potential use of (generative) AI by contracting authorities.
While it includes a reference in Annex A to the Generative AI framework for HM Government, that document does not specifically address the use of generative AI to manage procurement processes (and what it says about buying generative AI is redundant given the other guidance in the Annex). In my view, the generative AI framework pushes strongly against the use of AI in procurement when it identifies a series of use cases to avoid (page 18) that include contexts where high-accuracy and high-explainability are required. If this is the government’s (justified) view, then the AI PPN has been a missed opportunity to say this more clearly and directly.
The broader issue of confidential, classified or proprietary information
Both in relation to the procurement and use of AI, and the use of AI for tender generation, the AI PPN stresses that it may be necessary:
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‘Putting in place proportionate controls to ensure bidders do not use confidential contracting authority information, or information not already in the public domain as training data for AI systems e.g. using confidential Government tender documents to train AI or Large Language Models to create future tender responses.‘; and that
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‘In certain procurements where there are national security concerns in relation to use of AI by suppliers, there may be additional considerations and risk mitigations that are required. In such instances, commercial teams should engage with their Information Assurance and Security colleagues, before launching the procurement, to ensure proportionate risk mitigations are implemented.’
These are issues that can easily exceed the technical capabilities of most contracting authorities. It is very hard to know what data has been used to train a model and economic operators using ‘off-the-shelf’ generative AI solutions will hardly be in a position to assess themselves, or provide any meaningful information, to contracting authorities. While there can be contractual constraints on the use of information and data generated under a given contract, it is much more challenging to assess whether information and data has been inappropriately used at a different link of increasingly complex digital supply chains. And, in any case, this is not only an issue for future contracts. Data and information generated under contracts already in place may not be subject to adequate data governance frameworks. It would seem that a more muscular approach to auditing data governance issues may be required, and that this should not be devolved to the procurement function.
How to deal with it? — or where the PPN goes wrong
The biggest weakness in the AI PPN is in how it suggests contracting authorities should deal with the issue of generative AI. In my view, it gets it wrong in two different ways. First, by asking for too much non-scored information where contracting authorities are unlikely to be able to act on it without breaching procurement and good administration principles. Second, by asking for too little non-scored information that contracting authorities are under a duty to score.
Too much information
The AI PPN includes two potential (alternative) disclosure questions in relation to the use of generative AI in tender writing (see below Q1 and Q2).
