Artificial intelligence system impact assessments (AI-SIAs) are documented processes for identifying individuals and groups impacted by an AI system. Common-use impact assessments are already found in the context of business, the environment, finance, human rights, IT, privacy, personally identifiable information and security.
To help frame the benefits of these assessments and their use in relation to AI, here we introduce one of the available frameworks: BS ISO/IEC 42005:2025AI System Impact Assessment. This document provides standardised global guidelines for organisations to evaluate the societal, individual and organisational effects of an AI system, thereby ensuring the outputs of deployed AI systems are safe.
To mitigate the negative outputs and consequences of AI system usage or deployments, a structured approach – aligned with the requirements in BS ISO/IEC 42001:2023 (AI management systems) and BS EN ISO/IEC 23894:2024 (managing bias) – is provided across two aspects.
The first is how to develop and implement AI-SIAs based on the following stages:
process documenting
organisational management process integration
AI-SIA timing
AI-SIA scope
responsibility allocation
threshold establishment for sensitive and restricted uses
performing the AI-SIA
AI-SIA results analysis
recording and reporting
process approval
monitoring and review
The second aspect is about how to document AI systems using comprehensive recording protocols addressing scope, technical specifications, functionality, data quality metrics, algorithms, deployment parameters, stakeholder identification, impact analysis and risk mitigation.
Technical Implementation
Standardised documentation protocols assist the analysis of AI functionality, capability and purpose framed by the development of AI-SIAs across both these domains. Comprehensive information can then be provided on data provenance, quality metrics and AI processing methodology particularly where there are regulatory requirements applicable to the AI system.
The most prominent global AI legislation, the EU’s AI Act, includes Article 27 that requires detailed documentation with information about the purpose of an AI system deployment for authorities to assess compliance. There is guidance within the standard on, for example, document algorithms and models used in AI system development elaborating on how to develop relevant processes, and performance metrics and validation procedures of said systems.
Impact Analysis Approach
The approach provided also identifies actual and reasonably foreseeable effects, which require systematic evaluation of benefits and potential harms, to meet fundamental ethical and organisational needs. To do this, the guidelines include an analysis of systemic failures and misuse scenarios to exploit AI benefits and mitigate AI harm.
Existing Standards Integration and Challenges
A pre-emptive approach is taken in 42005 by identifying risks before AI deployment and simplifying the justification of AI-related decisions. It does this using matrices that map relevant clauses across BS ISO/IEC 42001:2023 and BS EN ISO/IEC 23894:2024. This helps clarify confusion between the concepts of “risk” assessment and “system impact” assessment. AI-SIAs are about identifying foreseeable impacts and AI risk assessments focus on setting strategies for mitigation. As such, there is a comparison between both approaches in BS EN ISO/IEC 23894:2024 and BS ISO/IEC 42005:2025 based on system and organisational levels in regard to societal, individual and organisational impacts, as well as between potential events and the likelihood of events occurring.
Further challenges for organisations deploying or using AI are that AI-SIAs are not easily tied to commercial need and financial qualification. Fundamental and human rights, for example, can be perceived as long-term considerations which are not easily quantifiable, and often misunderstood and feared by organisations keen to make profit. To resolve this lack of understanding, a modifiable visual guide for impact assessment alignment between existing assessments (including those for human rights and business) and AI-SIAs is provided.
Regulatory, Geographical, Cultural and Environmental Contexts
Increasingly, the geo-regulatory coupling of AI systems requires in-depth understanding of legal context and the need for co-existent approaches to culture, geography and environment. The approach in BS ISO/IEC 42005:2025 provides guidance for these contexts to demonstrate systematic risk evaluation and stakeholder analysis across multiple jurisdictions due to its multilateral content development processes.
Implementation Benefits
The direct benefits of implementing AI-SIAs bring about an overall improvement of AI system outputs. For example, it minimises hidden bias in some AI systems that could take the form of pejorative visual and verbal outputs or the omission of critical and overlooked demographic groups. Identifying these trends in stereotyping that could unintentionally downplay or overlook key groups could result in dire consequences (see this forbes article and this techUK article).
Conclusion
As part of a growing list of governance and policy assets available to those deploying and providing AI systems, AI-SIAs can provide analytical frameworks and approaches to SIAs supported through technical rigor.
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Kir Nuthi
Head of AI and Data, techUK
Kir Nuthi
Head of AI and Data, techUK
Kir Nuthi is the Head of AI and Data at techUK.
She holds over seven years of Government Affairs and Tech Policy experience in the US and UK. Kir previously headed up the regulatory portfolio at a UK advocacy group for tech startups and held various public affairs in US tech policy. All involved policy research and campaigns on competition, artificial intelligence, access to data, and pro-innovation regulation.
Kir has an MSc in International Public Policy from University College London and a BA in both Political Science (International Relations) and Economics from the University of California San Diego.
Outside of techUK, you are likely to find her attempting studies at art galleries, attempting an elusive headstand at yoga, mending and binding books, or chasing her dog Maya around South London's many parks.
Usman joined techUK in January 2024 as Programme Manager for Artificial Intelligence.
He leads techUK’s AI Adoption programme, supporting members of all sizes and sectors in adopting AI at scale. His work involves identifying barriers to adoption, exploring solutions, and helping to unlock AI’s transformative potential, particularly its benefits for people, the economy, society, and the planet. He is also committed to advancing the UK’s AI sector and ensuring the UK remains a global leader in AI by working closely with techUK members, the UK Government, regulators, and devolved and local authorities.
Since joining techUK, Usman has delivered a regular drumbeat of activity to engage members and advance techUK's AI programme. This has included two campaign weeks, the creation of the AI Adoption Hub (now the AI Hub), the AI Leader's Event Series, the Putting AI into Action webinar series and the Industrial AI sprint campaign.
Before joining techUK, Usman worked as a policy, regulatory and government/public affairs professional in the advertising sector. He has also worked in sales, marketing, and FinTech.
Usman holds an MSc from the London School of Economics and Political Science (LSE), a GDL and LLB from BPP Law School, and a BA from Queen Mary University of London.
When he isn’t working, Usman enjoys spending time with his family and friends. He also has a keen interest in running, reading and travelling.
Sue leads techUK's Technology and Innovation work.
This includes work programmes on cloud, data protection, data analytics, AI, digital ethics, Digital Identity and Internet of Things as well as emerging and transformative technologies and innovation policy.
In 2025, Sue was honoured with an Order of the British Empire (OBE) for services to the Technology Industry in the New Year Honours List.
She has been recognised as one of the most influential people in UK tech by Computer Weekly's UKtech50 Longlist and in 2021 was inducted into the Computer Weekly Most Influential Women in UK Tech Hall of Fame.
A key influencer in driving forward the data agenda in the UK, Sue was co-chair of the UK government's National Data Strategy Forum until July 2024. As well as being recognised in the UK's Big Data 100 and the Global Top 100 Data Visionaries for 2020 Sue has also been shortlisted for the Milton Keynes Women Leaders Awards and was a judge for the Loebner Prize in AI. In addition to being a regular industry speaker on issues including AI ethics, data protection and cyber security, Sue was recently a judge for the UK Tech 50 and is a regular judge of the annual UK Cloud Awards.
Prior to joining techUK in January 2015 Sue was responsible for Symantec's Government Relations in the UK and Ireland. She has spoken at events including the UK-China Internet Forum in Beijing, UN IGF and European RSA on issues ranging from data usage and privacy, cloud computing and online child safety. Before joining Symantec, Sue was senior policy advisor at the Confederation of British Industry (CBI). Sue has an BA degree on History and American Studies from Leeds University and a Masters Degree on International Relations and Diplomacy from the University of Birmingham. Sue is a keen sportswoman and in 2016 achieved a lifelong ambition to swim the English Channel.
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On 11 September, techUK held a workshop from 9:30 to 12:30 with DSIT’s Responsible Technology Adoption Unit (RTA), featuring an address from Felicity Burch, Director of RTA and facilitation by Nuala Polo, AI Assurance Lead of RTA with attendance from techUK’s Digital Ethics working group members. This session allowed for testing and feedback on a forthcoming assurance tool set for public consultation in Autumn 2024.
Nick Fitzpatrick, Manager, Frontier Economics discusses why ownership is a critical component of the conversation about getting the most out of geospatial data for the public good. Part of techUK's #GeospatialFuture campaign week