{"id":139115,"date":"2026-04-21T02:50:39","date_gmt":"2026-04-21T06:50:39","guid":{"rendered":"https:\/\/www.bloomberg.com\/professional\/insights\/press-announcement\/bloomberg-survey-uk-finance-leaders-say-inaccurate-outputs-are-the-biggest-barrier-to-ai-adoption\/"},"modified":"2026-04-21T08:53:54","modified_gmt":"2026-04-21T12:53:54","slug":"bloomberg-survey-uk-finance-leaders-say-inaccurate-outputs-are-the-biggest-barrier-to-ai-adoption","status":"publish","type":[3815],"link":"https:\/\/www.bloomberg.com\/professional\/insights\/press-announcement\/bloomberg-survey-uk-finance-leaders-say-inaccurate-outputs-are-the-biggest-barrier-to-ai-adoption\/","title":{"rendered":"Bloomberg Survey: UK finance leaders say inaccurate outputs are the biggest barrier to AI adoption"},"content":{"rendered":"
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PRESS ANNOUNCEMENT<\/span><\/strong><\/p>\n\n<\/div>\n\n<\/div>

Bloomberg Survey: UK finance leaders say inaccurate outputs are the biggest barrier to AI adoption<\/h1>\n<\/p>\n\n<\/div>\n \n<\/div>\n\n\n <\/div>\n <\/section>\n<\/div>\n\n
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April 21, 2026<\/p>\n<\/p>\n\n<\/div>\n

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Bloomberg survey shows source attribution, error checking, and human oversight are key elements in building trustworthiness in AI solutions<\/span><\/i><\/p>\n

London \u2013 21 April 2026 – <\/b>A Bloomberg poll of more than 100 senior decision-makers at its AI in Finance Summit<\/a> in London reveals that concerns about inaccurate outputs are the single biggest barrier to the adoption of artificial intelligence in financial services.<\/p>\n

Half of respondents (50%) identified hallucinated facts or numerical errors as their primary concern when using AI in financial markets, while a further 27% pointed to a lack of explainability. Together, these findings highlight the importance of accuracy and transparency as AI tools become more embedded in financial decision-making.<\/p>\n

These concerns are directly shaping how financial professionals evaluate and adopt AI. When asked what gives them the most confidence in AI systems, respondents pointed to features that enable outputs to be verified and controlled: 32% selected AI that attributes its sources, 30% highlighted built-in error checking, and 25% chose human oversight. By contrast, only 9% said sophisticated language and reasoning was the most important factor, and 5% said fast AI outputs.<\/p>\n

\u201cThe results suggest that trustworthiness depends on whether an AI\u2019s outputs can be interrogated and validated, said Amanda Stent, Head of AI Strategy & Research at Bloomberg.<\/b> \u201cSolving this challenge depends on attribution, transparency and the quality of the underlying data so outputs can be traced to their sources, validated for accuracy, and confidently used in decision-making. This is exactly what is shaping Bloomberg\u2019s approach to AI development. We are focused on combining high-quality, trusted data with AI that is embedded into real workflows, and designed with accuracy, transparency and control at its core.\u201d<\/p>\n

While concerns around accuracy remain front of mind, there is strong appetite for more advanced applications. Nearly two-thirds of respondents (66%) identified full workflow AI assistants as the most exciting next development in financial services, far ahead of other use cases such as personalised portfolio insights (9%) or no-code quant tools (12%).<\/p>\n

This points to a clear direction for the industry: growing demand for end-to-end AI integration, but only where systems can deliver reliable, verifiable outputs at scale.<\/p>\n

As financial institutions continue to adopt AI, the findings highlight a defining challenge for the industry: ensuring that innovation is matched by the accuracy and accountability required for high-stakes financial decisions.<\/p>\n

At the event, Bloomberg also unveiled a 2026 roadmap<\/a> for ASKB<\/span><\/b>, its powerful new conversational AI interface, now in beta, that redefines how investors interact with the Bloomberg Terminal of the future to augment their entire investment process. The roadmap outlines the evolution of ASKB into a deeply integrated engine for institutional intelligence using Bloomberg\u2019s AI that is grounded in trusted data and content, embedded in firm-wide workflows, and designed for accuracy and control following Bloomberg\u2019s Responsible AI principles<\/a>.<\/p>\n\n<\/div>\n\n\n<\/div>\n\n\n <\/div>\n <\/section>\n<\/div>\n\n

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Methodology<\/h5>\n

The survey was conducted via live audience polling at Bloomberg\u2019s AI in Finance Summit in London on Thursday 16 April 2026. More than 100 senior decision-makers from UK financial services firms participated, representing both buy-side and sell-side firms.<\/p>\n\n<\/div>\n\n\t

About AI at Bloomberg<\/h5>\n

Since 2009, Bloomberg has been building and using artificial intelligence (AI) in the finance domain \u2013 including machine learning (ML), natural language processing (NLP), information retrieval (IR), time-series analysis, and generative models \u2013 to help process and organize the ever-increasing volume of structured and unstructured financial information. With this technology, Bloomberg is developing new ways for financial professionals and business leaders to derive valuable intelligence and actionable insights from high-quality financial information and make more informed business decisions.<\/p>\n\n<\/div>\n\n\t

About Bloomberg<\/h5>\n

Bloomberg is a global leader in business and financial information, delivering trusted data, news, and insights that bring transparency, efficiency, and fairness to markets. The company helps connect influential communities across the global financial ecosystem via reliable technology solutions that enable our customers to make more informed decisions and foster better collaboration. For more information, visit\u00a0Bloomberg.com\/company<\/a>\u00a0or\u00a0request a demo<\/a>.<\/p>\n\n<\/div>\n\n<\/div>\n\n\n <\/div>\n <\/section>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

A Bloomberg poll of more than 100 senior decision-makers at its AI in Finance Summit in London reveals that concerns about inaccurate outputs are the single biggest barrier to the adoption of artificial intelligence in financial services.<\/p>\n","protected":false},"author":1757,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"template-press-release.php","format":"standard","meta":{"_yoast_wpseo_primary_category":"3814","footnotes":""},"categories":[3715,3814,3661],"tags":[],"series":[],"class_list":["post-139115","post","type-post","status-publish","format-standard","hentry","category-artificial-intelligence","category-press-announcement","category-technology","type-press-release"],"yoast_head":"\nBloomberg Survey: UK finance leaders say inaccurate outputs are the biggest barrier to AI adoption | Insights | Bloomberg Professional Services<\/title>\n<meta name=\"description\" content=\"A Bloomberg poll of more than 100 senior 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