--- title: "PS23342 - Assessment of the Cyber Security Risks to Artificial Intelligence (AI)" ocid: "ocds-b5fd17-294c6864-213c-4a7f-8b09-d2501276aee3" canonical_url: "https://d3tenders.com/contract/?ocid=ocds-b5fd17-294c6864-213c-4a7f-8b09-d2501276aee3" markdown_url: "https://d3tenders.com/contract/ocds-b5fd17-294c6864-213c-4a7f-8b09-d2501276aee3.md" json_url: "https://d3tenders.com/contract/ocds-b5fd17-294c6864-213c-4a7f-8b09-d2501276aee3.json" source: "Contracts Finder" current_stage: "Award" buyer: "BEIS" published: "2023-12-12" --- # PS23342 - Assessment of the Cyber Security Risks to Artificial Intelligence (AI) Buyer: BEIS Current stage: Award OCID: ocds-b5fd17-294c6864-213c-4a7f-8b09-d2501276aee3 [View canonical contract page](https://d3tenders.com/contract/?ocid=ocds-b5fd17-294c6864-213c-4a7f-8b09-d2501276aee3) [Download OCDS JSON](https://d3tenders.com/contract/ocds-b5fd17-294c6864-213c-4a7f-8b09-d2501276aee3.json) ## Summary The Department for Science, Innovation and Technology, represented by BEIS, has recently awarded a contract to Grant Thornton Limited. The procurement process, under the title "PS23342 - Assessment of the Cyber Security Risks to Artificial Intelligence (AI)," falls under the research services industry category. The contract, valued at £82,000 GBP, involved a selective procurement method through a call-off from a dynamic purchasing system. The tender period ended on 20th October 2023, with a contract period from 20th November 2023 to 29th February 2024. This tender presents an opportunity for businesses involved in research services, particularly those with expertise in cyber security risks to AI technologies. Small and medium-sized enterprises (SMEs) and voluntary, community, and social enterprise sector (VCSE) organisations may find this tender suitable for their capabilities. The study aims to map cyber risks to different AI technologies and their deployment, providing insights that can inform policy work in the rapidly growing field of AI adoption across UK businesses. ## Notice **Please note this is an Award Notice and not a call for competition, this Contract has been awarded via the Crown Commercial Services - RM3764.3 - Lot 1: Cyber Security Services 3.** The Department for Science, Innovation and Technology has a requirement to appoint a supplier to conduct a study to comprehensively map the cyber risks to different AI technologies and their deployment. Purpose AI use is growing. In April 2023, an estimated 16% of all UK businesses had adopted at least one AI technology. However, this number is now likely to increase significantly with the growth of more accessible and powerful generative AI models. To inform our policy work in this space, the Department wants to improve its understanding of the cyber risks to AI models and systems. The Department would therefore like to commission a study to comprehensively map the cyber risks to different AI technologies and their deployment. Objectives The Department is commissioning this research primarily to develop a comprehensive mapping of the cyber security risks to AI models and systems. More specifically, the Department seeks to gain: - Comprehensive mapping of cyber security risks to AI across different AI technologies and across different parts of the AI life cycle. - An understanding of all AI risks with a delineation between those specific to broader software and those solely in relation to AI. - Identification of the impacts these vulnerabilities and risks can cause, including the scale of the damage/impact. ## Key Details | Field | Value | | --- | --- | | Publication source | Contracts Finder | | Latest notice | https://www.contractsfinder.service.gov.uk/Notice/c8c753ba-1816-4663-be0f-0c3a0df24176 | | Notice type | Award Notice | | Procurement type | Dynamic | | Procurement category | Services | | Procurement method | Selective | | Procurement method details | Call-off from a dynamic purchasing system | | Tender suitability | SME, VCSE | | Awardee scale | SME | | All stages | Award | ## Dates | Field | Value | | --- | --- | | Publication date | 12 Dec 2023 | | Submission deadline | 20 Oct 2023 | | Future notice date | Not specified | | Award date | 1 Dec 2023 | | Contract period | 20 Nov 2023 - 29 Feb 2024 | | Recurrence | Not specified | ## Values | Field | Value | | --- | --- | | Tender value | £82,000 | | Lots value | Not specified | | Awards value | £82,000 | | Contracts value | Not specified | ## Status | Field | Value | | --- | --- | | Tender status | Complete | | Lots status | Not specified | | Awards status | Active | | Contracts status | Not specified | ## Buyer | Field | Value | | --- | --- | | Main buyer | BEIS | | Locality | SWINDON | | Post town | Swindon | | Postcode | SN2 1FF | | Country | England | | ITL 1 | TLK South West (England) | | ITL 2 | TLK7 Gloucestershire and Wiltshire | | ITL 3 | TLK71 Swindon | | Local authority | Swindon | | Electoral ward | Rodbourne Cheney | | Westminster constituency | Swindon North | | Delivery location | Not specified | ## Supplier | Field | Value | | --- | --- | | Number of suppliers | 1 | | Supplier names | GRANT THORNTON | ## CPV Codes ### Divisions - 73 - Research and development services and related consultancy services ### Codes - 73110000 - Research services - 73210000 - Research consultancy services ## Release History - 12 Dec 2023 at 15:47 - Award - Award Notice - https://www.contractsfinder.service.gov.uk/Notice/c8c753ba-1816-4663-be0f-0c3a0df24176 ## Documents - https://www.contractsfinder.service.gov.uk/Notice/c8c753ba-1816-4663-be0f-0c3a0df24176 12th December 2023 - Awarded contract notice on Contracts Finder - https://www.contractsfinder.service.gov.uk/Notice/Attachment/e4931b59-0e82-4a65-8624-9c125e7775e3 n/a ## Notice URLs - http://www.uksbs.co.uk ## Provenance This Markdown file is an alternate public rendering of the D3 Tenders contract record. The canonical page is https://d3tenders.com/contract/?ocid=ocds-b5fd17-294c6864-213c-4a7f-8b09-d2501276aee3. The underlying structured data is available as OCDS JSON at https://d3tenders.com/contract/ocds-b5fd17-294c6864-213c-4a7f-8b09-d2501276aee3.json.