{"id":401267,"date":"2026-11-14T10:00:44","date_gmt":"2026-11-14T04:30:44","guid":{"rendered":"https:\/\/www.scconline.com\/blog\/?p=401267"},"modified":"2026-11-13T18:22:42","modified_gmt":"2026-11-13T12:52:42","slug":"dubai-arbitration-week-2026-clifford-chance-ai-in-arbitration-risk-opportunity","status":"publish","type":"post","link":"https:\/\/www.scconline.com\/blog\/post\/2026\/11\/14\/dubai-arbitration-week-2026-clifford-chance-ai-in-arbitration-risk-opportunity\/","title":{"rendered":"Dubai Arbitration Week 2026: Examining AI&#8217;s growing role, risks and safeguards in international arbitration"},"content":{"rendered":"<div style=\"text-align: justify; line-height: 150%;\">\n<p style=\"margin-bottom: 3%;\">Dubai Arbitration Week 2026, held from 9 to 13 November, brought together arbitration practitioners, legal professionals and technology experts to discuss developments shaping international dispute resolution. Among the sessions was <span style=\"font-weight: bold;\">&#8220;AI in Arbitration &#8211; Balancing Risk and Opportunity&#8221;<\/span>, organised by Clifford Chance on 11 November 2026 at Lulu &amp; The Beanstalk, ICD Brookfield, Dubai. The session considered the expanding use of artificial intelligence (AI) throughout the arbitration lifecycle, examining how practitioners are using AI for document review, case assessment, translation, legal research and hearing administration. The discussion also addressed the risks associated with its use, particularly in relation to confidentiality, data security, legal professional privilege, professional responsibility and the disclosure of AI-generated material.<\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.scconline.com\/blog\/wp-content\/uploads\/2026\/11\/10_Clifford-Chance-session-DAW-1.jpg\" alt=\"\" width=\"616\" height=\"400\" \/><\/p>\n<p style=\"margin-bottom: 3%; text-align: center; font-style: italic;\">[In picture from left to right: Mr. Pravin Arvyta, Ms. Victoria St-Amour, Dr. Mustapha Tawbi and Ms. Prachi Trivedi]<\/p>\n<p style=\"margin-bottom: 3%;\">The panel featured <span style=\"font-weight: bold;\">Mr. Pravin Arvyta<\/span>, Director, Deloitte; <span style=\"font-weight: bold;\">Dr. Mustapha Tawbi<\/span>, GenAI Partner Technologist Lead, Amazon Web Services; <span style=\"font-weight: bold;\">Ms. Prachi Trivedi<\/span>, Counsel, Clifford Chance; and <span style=\"font-weight: bold;\">Ms. Victoria St-Amour<\/span>, Senior Associate, Clifford Chance. Drawing on their professional experiences, the panellists discussed both the practical benefits of AI and instances where its use had produced unexpected or unreliable results.<\/p>\n<p style=\"text-align: center; font-weight: bold;\">AI&#8217;s growing role in arbitration and lessons from its failures<\/p>\n<p style=\"margin-bottom: 3%;\">Opening the discussion, <span style=\"font-weight: bold;\">Mr. Pravin Arvyta<\/span> recalled an early experience with an AI translation tool used to review communications across multiple jurisdictions. During the review of an exchange between two individuals who had a difficult relationship with their line manager, the tool translated an Egyptian Arabic expression into an opposite sentiment. The example illustrated the limitations of literal translation where meaning depended on cultural and linguistic context. Although the tool had translated much of the communication successfully, the particular expression demonstrated why AI-generated translations still required human verification. <span style=\"font-weight: bold;\">Ms. Prachi Trivedi<\/span> shared a personal example involving an AI voice-generation tool. She had used it to create a personalised Christmas message from Santa Claus for her two young children. The tool generated a booming voice that sounded like a well-known broadcaster, frightening the children, who asked her to stop the recording. Further, <span style=\"font-weight: bold;\">Ms. Victoria St-Amour<\/span> also recounted another experience involving an AI tool that repeatedly reassured her that a tree transplanted from her old garden would survive in its new location. Despite seeing no signs of life in the tree, she continued receiving positive assurances from the system.<\/p>\n<p style=\"margin-bottom: 3%;\">These examples introduced an important distinction that ran through the session: AI could generate convincing responses, but convincing responses were not necessarily accurate ones. Context, verification and human judgement remained essential.<\/p>\n<p style=\"text-align: center; font-weight: bold;\">Applying AI across the arbitration lifecycle<\/p>\n<p>Discussing the practical use of AI in arbitration, Ms. Victoria observed that the technology was particularly suited to the document-heavy and fact-intensive nature of proceedings. Lawyers and experts routinely spend substantial time searching, organising and comparing documents before synthesising the information for clients or submissions. These were tasks in which AI tools were increasingly capable of assisting. She nevertheless cautioned against delegating every task to AI. The distinction, she explained, was between using technology to augment existing work and allowing it to replace tasks requiring legal judgement and strategic assessment. Where the task involves professional judgement or the client&#8217;s strategy, she emphasised:<\/p>\n<p style=\"margin-bottom: 3%; margin-left: 36pt; font-weight: bold;\">&#8220;&#8230;AI needs to be kind of used with a lot of proportion, or perhaps not at all.&#8221;<\/p>\n<p style=\"margin-bottom: 3%;\">Referring to institutional guidance, she noted that arbitration organisations were beginning to address the appropriate use of AI. The objective of such guidance was not to discourage adoption, but to enable practitioners to benefit from the technology while protecting procedural rights and the integrity of the arbitral process. Ms. Victoria identified three stages at which AI was proving particularly useful.<\/p>\n<ul style=\"list-style-type: disc;\">\n<li>\n<p style=\"font-weight: bold;\">Early case assessment<\/p>\n<\/li>\n<\/ul>\n<p style=\"margin-bottom: 3%;\">The first was the early assessment of a dispute. When a client approaches a legal team with an urgent request for advice and a substantial volume of documents, AI can assist in preparing preliminary chronologies, summarising key themes and identifying gaps in the documentary record. This can be particularly valuable for respondents. While a claimant may have spent months preparing its case, a respondent may receive a request for arbitration and have only 28 days to prepare its response while reviewing thousands of documents. AI-assisted review can help the responding party understand the available material more quickly and identify the principal risks at an early stage. This may also allow the client to consider settlement before the proceedings become more advanced.<\/p>\n<ul style=\"list-style-type: disc;\">\n<li>\n<p style=\"font-weight: bold;\">Document production and review<\/p>\n<\/li>\n<\/ul>\n<p style=\"margin-bottom: 3%;\">The second area was document production. Ms. Victoria explained that AI tools could assist with, or undertake substantial parts of, document review, provided that human supervision and verification remained in place. She referred to AI tools capable of reviewing approximately 100,000 to 200,000 documents in a day. The benefit was not limited to the speed of review. By reducing the time spent on repetitive tasks, the technology could allow lawyers to examine the material more comprehensively and concentrate on issues requiring legal analysis. However, she cautioned that the human effort involved in preparing an AI-enabled review should not be underestimated. In one exercise, the team had spent several weeks developing a prompt that ultimately extended to approximately three or four pages. The prompt was then tested against a sample set of documents, with human reviewers assessing the AI-generated results.<\/p>\n<ul style=\"list-style-type: disc;\">\n<li>\n<p style=\"font-weight: bold;\">Hearing administration<\/p>\n<\/li>\n<\/ul>\n<p style=\"margin-bottom: 3%;\">The third area concerned the administrative aspects of hearings. AI-assisted transcription could generate summaries of proceedings and daily hearing reports in near real time, particularly in virtual hearings. These summaries could assist stakeholders who were unable to attend the proceedings. The broader objective, she explained, was to allow lawyers to focus on preparing the strategy for the following day rather than spending time compiling summaries of what had already taken place. Ms. Victoria emphasised that the value of AI lay in identifying tasks that could be automated or accelerated, such as document comparison, information extraction and transcription, while retaining human involvement in matters requiring judgement, context and strategy. Although individual efficiencies might appear modest, their cumulative effect over an arbitration lasting two or three years could be substantial.<\/p>\n<p style=\"text-align: center; font-weight: bold;\">AI-enabled document review: data mapping, translation and extraction<\/p>\n<p style=\"margin-bottom: 3%;\">Mr. Pravin expanded on the practical workflow involved in AI-assisted document review, explaining that its use could begin before the actual review of documents. At the outset of a large arbitration, AI could assist in preparing a data map identifying where relevant information might be located. This could help practitioners understand the systems, custodians and data sources that might need to be examined. He stressed, however, that the exercise required manual assessment to avoid an overly broad collection or the omission of relevant sources. AI could also assist in drafting legal-hold communications and questionnaires for custodians. Once responses were received, the technology could help collate the information, identify the need for follow-up questions and organise material for collection and processing. One of the areas he considered particularly useful was the processing of scanned and handwritten documents. Traditional optical character recognition (OCR) systems make scanned documents searchable, but can produce errors. Generative AI could assist in reading poorly scanned or handwritten material, including documents containing stamps or markings that obscure the underlying text.<\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.scconline.com\/blog\/wp-content\/uploads\/2026\/11\/10_Clifford-Chance-session-DAW-2.jpg\" alt=\"\" width=\"267\" height=\"333\" \/><\/p>\n<p style=\"margin-bottom: 3%; text-align: center; font-style: italic;\">[In picture: Mr. Pravin Arvyta]<\/p>\n<p style=\"margin-bottom: 3%;\">Mr. Pravin also discussed the potential to extract information from documents in multiple languages and translate it in context. Rather than relying solely on literal translations, the AI system could be given information about the relevant government authority, corporate entity, industry or subject matter of the dispute. He referred to an exercise involving a local conglomerate with businesses across the Gulf Cooperation Council (GCC), where documents in languages including Arabic and Farsi had to be reviewed. The translations were subjected to fact-checking, with a certified translator conducting sample checks. For him, the advantage was not simply the speed of translation. It was also the extent of the material that could be reviewed. AI could make it possible to examine a much larger proportion of the available document population rather than relying predominantly on sample checks. AI could further assist with extracting metadata, identifying document authors and creation dates, preparing summaries and helping counsel determine which documents should proceed to further review.<\/p>\n<p style=\"margin-bottom: 3%;\">He emphasised that these results depended on the quality of the prompts. The system needed to be given an understanding of the subject matter, background of the dispute, the role it was expected to perform, the client&#8217;s location and the relevant industry. Such prompts could be extensive and required careful development. As he explained, weeks were spent on engineering those prompts and testing them before applying the workflow to the full document population. The team would first test the results against sample documents and proceed to wider deployment only after assessing their reliability.<\/p>\n<p style=\"text-align: center; font-weight: bold;\">Where AI performs well and where caution is required<\/p>\n<p style=\"margin-bottom: 3%;\">Mr. Pravin identified accounting reviews as an area in which he had observed particularly useful results. AI systems could examine financial statements, perform calculations, identify errors and generate spreadsheets containing the results of the analysis. He clarified that the purpose was not to replace accounting professionals, but to validate their work and assist in auditing financial information. He was more cautious about using AI in fraud and misconduct investigations, particularly where the analysis involved subjective or nuanced communications. Sentiment analysis, for example, could assess the tone or intensity of an email, but might not consistently capture the context in which the communication was made. An AI-generated assessment could appear objective while overlooking the circumstances that gave the communication its meaning. The outputs therefore required careful examination before being relied upon. The point was particularly important in investigations, where an inaccurate interpretation could affect the assessment of conduct or evidence. AI could assist with the analysis, but the conclusions drawn from it had to remain subject to human judgement.<\/p>\n<p style=\"text-align: center; font-weight: bold;\">The economics of AI-assisted arbitration<\/p>\n<p style=\"margin-bottom: 3%;\">The panel then considered whether the increasing use of AI would necessarily reduce the cost of arbitration. Ms. Victoria observed that clients expected AI to generate efficiencies and reduce legal spending. However, the relationship between AI adoption and lower costs was not necessarily straightforward. The use of AI involved licence fees, hosting costs, e-discovery and forensic technology support, as well as the time required for validation and human oversight. She suggested that the more significant benefit could be the ability to produce a more comprehensive work product within the same budget, rather than simply undertaking the same work at a lower cost. She also considered whether arbitral tribunals might increasingly examine the use of available technology when assessing the costs claimed by parties.<\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.scconline.com\/blog\/wp-content\/uploads\/2026\/11\/10_Clifford-Chance-session-DAW-3.jpg\" alt=\"\" width=\"258\" height=\"327\" \/><\/p>\n<p style=\"margin-bottom: 3%; text-align: center; font-style: italic;\">[In picture: Ms. Victoria St-Amour]<\/p>\n<p style=\"margin-bottom: 3%;\">The question was whether a party that had incurred substantial costs through a conventional document-review process, despite the availability of AI-assisted alternatives, could reasonably expect to recover all those costs from the opposing party. In this context, she referred to Article 41(5) of the ICC Arbitration Rules, 2026, which permits tribunals, when making decisions on costs, to take into account relevant circumstances, including the extent to which each party has conducted the arbitration in an expeditious and cost-effective manner. She did not suggest that parties should be subject to a blanket obligation to use AI. Rather, the existing principles of reasonableness, proportionality and cost-effectiveness could become relevant when assessing how parties had conducted the proceedings and the costs they sought to recover.<\/p>\n<p style=\"text-align: center; font-weight: bold;\">Responsible enterprise AI: confidentiality, data control and verification<\/p>\n<p style=\"margin-bottom: 3%;\">The discussion then moved to the risks associated with entering confidential arbitration material into AI systems. <span style=\"font-weight: bold;\">Dr Mustapha Tawbi<\/span> emphasised that confidentiality was not merely an additional feature in arbitration-related AI systems, but a fundamental requirement. He suggested that organisations developing an AI strategy should begin with two questions: is my data fully under my control? and whether the outputs generated by the system were verified, accurate and controlled.<\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.scconline.com\/blog\/wp-content\/uploads\/2026\/11\/10_Clifford-Chance-session-DAW-4.jpg\" alt=\"\" width=\"288\" height=\"342\" \/><\/p>\n<p style=\"margin-bottom: 3%; text-align: center; font-style: italic;\">[In picture: Dr Mustapha Tawbi]<\/p>\n<p style=\"margin-bottom: 3%;\">He explained that organisations first needed to establish appropriate data governance, including who had the right to access particular information and what level of authorisation was required. Introducing an AI layer without first establishing these controls could create an additional risk. The second consideration was the boundary within which the data was processed. Organisations needed to understand whether information entered into an AI system would remain within their control and whether a technology provider could use it to train other models. Referring to Amazon&#8217;s generative AI, Dr. Mustapha discussed the platform&#8217;s features for building generative AI applications, including controls intended to keep customer inputs and outputs within the customer&#8217;s account and prevent them from being used to train other models. He also referred to encryption, customer-controlled encryption keys and private connectivity as measures that could support data security. He emphasised that the accuracy of AI-generated outputs was particularly important in arbitration. An inaccurate output relied upon in a legal proceeding could damage a party&#8217;s case, potentially in ways that might not be capable of being remedied.<\/p>\n<p style=\"margin-bottom: 3%;\">Dr. Mustapha discussed the use of guardrails and monitoring mechanisms to manage inappropriate outputs and maintain traceability. He also referred to the importance of being able to track activity and understand what was happening within the system. Data location was another consideration. Organisations needed to understand where their data was stored and processed, particularly where regional requirements applied. He discussed Amazon Web Services&#8217; regional infrastructure and sovereign-cloud-related arrangements in the context of the United Arab Emirates (UAE). He concluded by returning to the two questions with which he had begun: whether the organisation had control over its data and whether the outputs could be verified. These questions, he suggested, should be answered before moving ahead with an AI deployment.<\/p>\n<p style=\"text-align: center; font-weight: bold;\">AI adoption and the regulatory landscape in the UAE<\/p>\n<p style=\"margin-bottom: 3%;\">Considering AI adoption in the UAE and the wider Middle East and North Africa (MENA) region, Dr. Mustapha described the region as an active participant in the adoption of AI technologies. He referred to figures indicating an increase in enterprise use of AI in the UAE, while observing that only a proportion of organisations had moved towards more advanced applications. He identified skills shortages as one of the challenges affecting wider adoption. Organisations needed to develop the technical and operational capabilities required to deploy AI at scale and understand the differences between frontier models, customised models and hybrid approaches.<\/p>\n<p style=\"margin-bottom: 3%;\">On regulation, he argued that regulatory frameworks should address the risks arising from the use of technology rather than prescribe technology itself. The level of regulatory oversight appropriate for a general-purpose application would not necessarily be suitable for a system used in a sensitive legal process such as arbitration. He also emphasised the importance of clarity in regulatory obligations and suggested that regulators should work with industry and draw on established standards, including the International Organisation for Standardisation (ISO) relating to AI management and governance.<\/p>\n<p style=\"text-align: center; font-weight: bold;\">Legal professional privilege and the risks of open-source AI tools<\/p>\n<p style=\"margin-bottom: 3%;\">Ms. Prachi addressed the implications of AI use for legal professional privilege, particularly where lawyers or in-house legal teams enter client information into publicly accessible AI systems. She referred to the UK legal framework, which recognises legal advice privilege and litigation privilege, and discussed the observations of the Upper Tribunal in <span style=\"font-style: italic;\">R (on the application of Munir)<\/span> v. <span style=\"font-style: italic;\">Secretary of State for the Home Department<\/span><a id=\"fnref1\" href=\"#fn1\" title=\"1. [2026] UKUT 00081 (IAC)\"><sup>1<\/sup><\/a>.<\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.scconline.com\/blog\/wp-content\/uploads\/2026\/11\/10_Clifford-Chance-session-DAW-5.jpg\" alt=\"\" width=\"276\" height=\"354\" \/><\/p>\n<p style=\"margin-bottom: 3%; text-align: center; font-style: italic;\">[In picture: Ms. Prachi Trivedi]<\/p>\n<p style=\"margin-bottom: 3%;\">The case concerned, among other matters, the use of AI-generated material in legal proceedings. The Tribunal addressed the submission of inaccurate AI-generated legal authorities and made separate observations about the use of confidential client material in open-source AI tools. The Tribunal observed that entering client letters and Home Office decision letters into an open-source AI tool amounted to placing the information on the internet in the public domain, with consequences for client confidentiality and legal professional privilege. Ms. Prachi used the decision to highlight the need for legal practitioners to exercise caution when using AI tools to process client-related information. She recommended the use of secure, enterprise-protected tools, with the work remaining under the direction of a legal practitioner. She compared the use of AI to seeking assistance from a paralegal or junior member of the legal team. The technology could support the work, but responsibility for the work product remained with the lawyer. She also highlighted the risks arising when employees use personal AI tools to obtain assistance with legal matters, particularly where an individual may be the subject of an internal investigation or where the information is contentious. In-house legal teams should therefore consider clear policies discouraging the use of personal AI accounts for sensitive work.<\/p>\n<p style=\"margin-bottom: 3%;\">Ms. Prachi further observed that professional responsibility required lawyers to be able to explain and justify their use of AI. Where the use of AI became relevant to a dispute over privilege, questions could arise concerning the prompts entered, the information supplied and the manner in which the system had been used. The broader point was that the use of a secure tool did not, by itself, resolve every privilege issue. The purpose of the use, the nature of the information entered and the lawyer&#8217;s supervision remained important considerations.<\/p>\n<p style=\"text-align: center; font-weight: bold;\">Assessing privacy and confidentiality before using AI in arbitration<\/p>\n<p style=\"margin-bottom: 3%;\">Ms. Prachi explained that the assessment of whether arbitration material could be entered into an AI system should begin with the relevant contracts. Practitioners needed to examine the underlying dispute, the engagement terms with the client and the obligations governing the handling of client information. The applicable data-protection regimes would also need to be considered. In addition, the processing of personal data should be proportionate to the purpose for which it was required. The fact that arbitration proceedings involved large volumes of documents did not necessarily justify entering all available personal information into an AI system.<\/p>\n<p style=\"margin-bottom: 3%;\">Mr. Pravin added that organisations were increasingly considering models deployed within their own infrastructure or private environments. Such arrangements could offer greater control over data and confidentiality, although they might involve trade-offs in terms of functionality and access to the latest models. He also warned against inadvertent disclosure through everyday use. Employees might use personal accounts or devices to generate prompts without appreciating that information connected to a professional matter could be entered into an external platform. This reinforced the need for education and clear organisational policies on AI use.<\/p>\n<p style=\"margin-bottom: 3%;\">Dr. Mustapha acknowledged that private or on-premises environments could offer advantages for sensitive data, but cautioned that they might also limit access to the capabilities of newer frontier models. He reiterated that data security depended on both the safeguards provided by the technology provider and the manner in which the user operated the system.<\/p>\n<p style=\"text-align: center; font-weight: bold;\">Should parties disclose their use of AI in arbitration?<\/p>\n<p>In the final substantive discussion, Ms. Prachi considered whether parties should be required to disclose their use of AI during arbitration proceedings. She identified a potential tension between transparency and procedural fairness, on the one hand, and one the other she emphasised:<\/p>\n<p style=\"margin-bottom: 3%; margin-left: 36pt; font-weight: bold;\">&#8220;&#8230;flexibility and party autonomy are one of the key attractions to many of the users.&#8221;<\/p>\n<p style=\"margin-bottom: 3%;\">While confidence in the integrity of the arbitral process was important, requiring disclosure of every instance of AI use could impose unnecessary restrictions, particularly where the technology was used for routine administrative tasks. She suggested distinguishing between non-material and material uses of AI. Routine activities such as proofreading, preparing document lists or reviewing submissions with human supervision might not require the same level of disclosure as uses capable of affecting evidence or the outcome of a dispute. As AI becomes more integrated into arbitration practice, discussions about its intended use could increasingly form part of procedural conferences. Parties and tribunals could address the circumstances in which disclosure would be required and the safeguards necessary for particular applications.<\/p>\n<p style=\"margin-bottom: 3%;\">Ms. Prachi also referred to the possibility of tribunals appointing AI experts to assist in understanding how a system had been used, particularly where a party&#8217;s use of AI was challenged or its effect on evidence or reasoning was unclear. This approach is reflected in the Chartered Institute of Arbitrators (CIArb) Guideline on the Use of AI in Arbitration, 2025 (Guidelines). The Guideline recognises the tribunal&#8217;s power to regulate the use of AI by parties, make procedural directions and appoint AI experts where technical assistance is required. It also addresses the possibility of requiring disclosure in appropriate circumstances. Ms. Prachi cautioned against adopting a single blanket rule governing every use of AI. Instead, she favoured allowing procedural guidance and soft-law instruments to evolve in line with arbitration&#8217;s flexibility and the changing nature of the technology.<\/p>\n<p style=\"font-weight: bold;\">Conclusion<\/p>\n<p style=\"margin-bottom: 3%;\">The Clifford Chance session at Dubai Arbitration Week 2026 examined how AI is becoming an increasingly integrated part of arbitration practice. The speakers highlighted its practical applications in early case assessment, document review, translation, financial analysis and hearing administration, while emphasising that its benefits depend on careful implementation and effective human supervision. The discussion also demonstrated that efficiency cannot be considered in isolation from the risks associated with confidentiality, data security, legal professional privilege, accuracy and professional responsibility. Secure systems, carefully designed prompts, verification procedures and clear internal policies were identified as essential elements of responsible AI adoption.<\/p>\n<p style=\"margin-bottom: 3%;\">On the question of disclosure, the speakers favoured a proportionate approach that distinguishes routine AI-assisted tasks from material uses that could affect the evidence or outcome of proceedings. As AI becomes more deeply embedded in arbitration practice, the development of procedural guidance and the role of arbitral tribunals in supervising its use are likely to assume greater importance. The central message was that AI can enhance the efficiency of arbitration proceedings, but it cannot replace the professional judgement, oversight and accountability of the lawyers, experts and arbitrators responsible for the process.<\/p>\n<p style=\"margin-bottom: 3%;\"><span style=\"font-weight: bold; font-style: italic;\">SCC Times is the Official Information &amp; Documentation Partner for <a href=\"https:\/\/www.scconline.com\/blog\/post\/category\/events-collaborations\/dubai-arbitration-week\/\" target=\"_blank\">Dubai Arbitration Week 2026<\/a>. Stay tuned for comprehensive coverage, key insights and highlights from the event!<\/span>&nbsp;<\/p>\n<\/div>\n<hr\/>\n<p style=\"margin-left: 18pt; text-indent: -18pt;\"><a id=\"fn1\" href=\"#fnref1\">1.<\/a> [2026] UKUT 00081 (IAC)<\/p>\n","protected":false},"excerpt":{"rendered":"<p style=\"font-style: italic;\">From document review and case assessment to confidentiality, privilege and disclosure, practitioners at a Clifford Chance session during Dubai Arbitration Week 2026 discussed how artificial intelligence is changing arbitration practice and why human oversight remains essential.<\/p>\n","protected":false},"author":67537,"featured_media":401270,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[118433,97664,107243],"tags":[119693,119689,92407,119691,86108,89543,77326,119683,105857,119682,119692,51064,119690,118858,85897,119694,119688,119695,119685,119686,119684,30768,119687],"class_list":["post-401267","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-dubai-arbitration-week","category-events-collaborations","category-international","tag-ai-and-arbitration-costs","tag-ai-and-confidentiality","tag-ai-and-legal-practice","tag-ai-disclosure-in-arbitration","tag-ai-governance","tag-ai-in-arbitration","tag-ai-in-dispute-resolution","tag-ai-assisted-document-review","tag-arbitration-technology","tag-artificial-intelligence-in-international-arbitration","tag-ciarb-guideline-on-the-use-of-ai-in-arbitration","tag-clifford-chance","tag-data-security-in-arbitration","tag-dubai-arbitration-week-2026","tag-generative-ai","tag-icc-arbitration-rules-2026","tag-legal-professional-privilege","tag-middle-east-and-north-africa","tag-mustapha-tawbi","tag-prachi-trivedi","tag-pravin-arvyta","tag-uae","tag-victoria-st-amour"],"yoast_head":"<!-- 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