Marsh aims to be an \u201cAI winner\u201d through growth, productivity and efficiency gains, according to John Doyle, president and CEO of the broker and risk adviser.<\/p>\n
\u201c[W]e see AI as a powerful accelerator and enabler in delivering value to our clients, colleagues and shareholders,\u201d Doyle said during an earnings call with equities analysts to discuss first quarter results. (See below for Marsh\u2019s Q1 results wrapup).<\/p>\n
He emphasized that it\u2019s important to remember that Marsh is not selling commoditized products or simply procuring insurance at the lowest possible price. \u201cAI will help us serve our clients who have bespoke and complex needs even better. It will not replace the trusted advice, expertise and capabilities with which we deliver value to clients.\u201d<\/p>\n
As KPMG said in a recent report, AI is delivering value, but only for those businesses that scale it \u2013 and Marsh is focusing on<\/p>\n
\u201cWhile AI adoption is accelerating worldwide, only a small group of \u2018AI leaders\u2019 are seeing clear returns. These leaders consistently outperform others, including 82% saying that AI is already delivering meaningful business value, compared to 62% of their peers,\u201d said KPMG International in its first Global AI Pulse survey<\/a>, published in March.<\/p>\n \u201cThis is not simply an AI maturity gap; it is a widening performance gap between organizations that treat AI as an enterprise-wide transformation and those that are trying to bolster AI onto existing models and seeing incremental gains,\u201d said KPMG.<\/p>\n Marsh is following an enterprise-wide strategy for its AI investments.<\/p>\n Doyle said that he and his team \u201cfeel good\u201d about the company\u2019s AI investments and how these new tech capabilities are improving the business. \u201cWe moved early on AI, and we\u2019re excited about how it\u2019s already making us better and how it\u2019s going to make us better in the future,\u201d he said, noting that Marsh\u2019s scale matters.<\/p>\n \u201cOur strategy leverages our scale and capacity to invest in AI to drive even greater value from our proprietary data assets and our role as our clients\u2019 trusted adviser,\u201d Doyle said.<\/p>\n He went on to detail Marsh\u2019s strategy for its AI tech investments, which focuses on three main pillars: growth, productivity and efficiency.<\/p>\n Growth<\/p>\n In the area of growth, Doyle said the company is \u201cbuilding AI-enabled applications and services that are generating new revenue streams as well as enhancing world-class capabilities and data-driven insights in insurance, health, human capital and investments.\u201d<\/p>\n There are also significant AI growth opportunities to be found in Marsh\u2019s consulting businesses \u2013 Oliver Wyman and Mercer, he said.<\/p>\n Oliver Wyman\u2019s Quotient team was created to help clients deploy their own AI strategies and is its fastest-growing practice, Doyle continued.<\/p>\n \u201cWe\u2019re advising clients in multiple sectors such as banking, energy, government and manufacturing around AI and workforce transformation. We\u2019ve already advised on more than $50 billion of capital investment in AI deployment, and Mercer is working with clients to assess and inventory skills and redesign jobs as AI is integrated into ways of working.\u201d<\/p>\n Productivity<\/p>\n Marsh\u2019s second AI pillar is productivity, which focuses on deploying AI capabilities to boost the performance of the group\u2019s colleagues.<\/p>\n \u201cThis is showing up in hundreds of different ways across a wide variety of roles. A good example of our work is to embed AI in our client management tools and to develop AI agents to help colleagues source and prequalify leads to support sales productivity,\u201d Doyle explained.<\/p>\n Efficiency<\/p>\n The final AI pillar is efficiency, Doyle said, noting that across Marsh\u2019 business, the impact of AI automation is beginning to emerge.<\/p>\n \u201cA critical reason for creating our Business and Client Services unit, or BCS, is to exploit the efficiency potential of AI. By consolidating our back-office operations and technology into scalable centers, BCS is accelerating the pace of AI-driven automation and process reengineering.\u201d<\/p>\n Doyle went on to cite an example with the fact that the company now handles thousands of documents weekly, improving the efficiency of these processes by 20%, while \u201cenhancing the quality of the data and its usability to further support clients with valuable insights.\u201d<\/p>\n \u201cWe are beginning to reduce the cost and time associated with upgrading code to modernize applications. For example, we recently used AI to turn a legacy tool into a newly designed broker workbench in days, saving months of team effort,\u201d he added.<\/p>\n Further, Doyle added, Agentic AI has been deployed for Marsh\u2019s IT help desk, which has significantly reduced inquiries, improved colleague experience and created downstream efficiencies in Marsh\u2019s support centers. (Agentic AI is described by Amazon\u2019s AWS<\/a> as an autonomous AI system that can act independently, without constant human oversight, to achieve pre-determined goals.)<\/p>\n \u201cAnd in our policy renewal center, AI has enabled us to transform a traditionally manual, email-heavy process into a streamlined digital solution in weeks, a project that otherwise would have taken many months,\u201d he affirmed. \u201cAI-enabled savings will fuel additional growth investments, including in producer talent, and new capabilities while building our confidence in continued margin improvement.\u201d<\/p>\n Q1 Results Overview<\/p>\n During the first quarter, Marsh reported consolidated revenue of $7.6 billion, an increase of 8% compared with the first quarter of 2025, or 4% on an underlying (organic) basis (level with Q1 2025).<\/p>\n Operating income during Q1 2026 fell 12% to $1.8 billion and included a $425 million charge related to the Greensill litigation (compared with Q1 2025 when operating income was $2 billion).<\/p>\n Net income attributable to the company during Q1 2026 was $1.1 billion, compared with $1.38 billion in Q1 2025. Earnings per share for Q1 2026 were $2.36, while adjusted earnings per share increased 8% to $3.29.<\/p>\n Risk and Insurance Services Segment<\/p>\n Marsh\u2019s Risk and Insurance Services (RIS) segment (comprising Marsh Risk and reinsurance broker Guy Carpenter) reported revenue of $5.1 billion during Q1 2026, an increase of 6%, or 3% on an underlying (organic) basis. Operating income decreased 19% to $1.3 billion and included the charge related to the Greensill litigation, while adjusted operating income increased 7% to $1.9 billion.<\/p>\n Marsh Risk\u2019s revenue in the first quarter of 2026 was $3.7 billion, an increase of 8%, or 4% on an underlying basis. In U.S.\/Canada, underlying revenue growth was 3%. In International, underlying revenue growth was 5%, and included 6% growth in EMEA, 5% growth in Asia Pacific, and 2% growth in Latin America.<\/p>\n Guy Carpenter\u2019s revenue in the first quarter was $1.2 billion, an increase of 3%, or 2% on an underlying basis.<\/p>\n \n Topics
\n InsurTech<\/a>
\n Data Driven<\/a>
\n Artificial Intelligence<\/a>\n <\/p>\n","protected":false},"excerpt":{"rendered":"Marsh aims to be an \u201cAI winner\u201d through growth, productivity and efficiency gains, according to John Doyle, president…\n","protected":false},"author":2,"featured_media":6874,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[6280,24,25,111,6281,5807,6282],"class_list":{"0":"post-6873","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-ai","8":"tag-2026-financial-results","9":"tag-ai","10":"tag-artificial-intelligence","11":"tag-artificial-intelligence-ai","12":"tag-financial-results","13":"tag-kpmg","14":"tag-marsh"},"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/6873","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/comments?post=6873"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/6873\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media\/6874"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media?parent=6873"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/categories?post=6873"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/tags?post=6873"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}