Finance chief Dan Durn is turning Adobe\u2019s finance organization into an early proving ground for agentic AI\u2014using autonomous software agents to forecast results, scan contracts, and even answer hundreds of thousands of emails.<\/p>\n
The push mirrors Adobe\u2019s broader strategy around agentic AI. For customers, the company lets them choose models, combine them with their own data and Adobe\u2019s, and point agents at specific business outcomes.<\/p>\n
Internally, Durn, who is also in charge of technology, security and operations, has taken a similar approach to finance: pairing a rules-based, data-heavy function with AI, within a structure where finance, IT, and security report to one leader so pilots can move to production quickly. \u201cAccuracy is non-negotiable,\u201d he adds; that\u2019s why Adobe<\/a> is investing in structured data and governance so it can move fast without sacrificing precision, he says.\u00a0<\/p>\n The rise of AI is rapidly reshaping corporate leadership<\/a>, accelerating turnover and elevating executives who can deliver fast, tangible results. Even long-tenured leaders face increasing pressure from investors to move aggressively on AI. Recent leadership changes, including the announced retirement of Adobe CEO Shantanu Narayen, highlight how little patience markets now have for perceived hesitation. At the same time, Adobe reported that annualized revenue from its AI-first products more than tripled year over year in its first quarter of fiscal 2026, which ended Feb. 27. Across Fortune 500 companies, this dynamic is creating a new internal proving ground where executives are judged by how effectively, and how quickly, they deploy AI to drive growth, efficiency, and innovation.<\/p>\n Using AI in finance<\/p>\n Inside finance, Durn groups AI use into three buckets: forecasting, anomaly detection, and general productivity.<\/p>\n For forecasting, AI uncovers patterns and signals in data that would be difficult for humans to detect quickly, he explains. Anomaly-detection agents flag performance that\u2019s unexpectedly strong or weak\u2014\u201cthings that can get lost in the sea of data\u201d\u2014so finance can intervene faster, he says.<\/p>\n However, Durn says the best examples now sit in productivity, citing three use cases:<\/p>\n 1. Extracting information from PDFs<\/p>\n One of the most developed use cases involves \u201ccontainers\u201d of information\u2014collections of PDFs such as investor transcripts, quarterly reports, and analyst research. Finance teams use Adobe\u2019s PDF Spaces to load documents into a shared digital workspace and use an agentic AI assistant to surface themes, insights, and messaging cues in minutes rather than hours.<\/p>\n A recent Forrester TEI study<\/a> found Acrobat\u2019s agentic AI Assistant increases efficiencies in document summarization and analysis by 45%. Durn says that matters because \u201cthe world\u2019s information lives in PDF,\u201d and AI that turns static content into insights that can be used.<\/p>\n 2. Cutting contract review time in half<\/p>\n Adobe is also using agentic AI to overhaul contract reviews across finance and procurement functions including revenue assurance, contract operations, product fulfillment, and vendor management. Instead of finance professionals combing through every clause, an AI assistant scans thousands of contracts, highlights provisions relevant to each function, and flags non-standard terms.<\/p>\n The system has cut review time roughly in half, speeding individual reviews and allowing teams to query the entire contract repository\u2014for example, identifying which contracts include auto-cancellation features or foreign-exchange adjustment windows, Durn says. Adobe built its first prototype by April 2024 and began onboarding teams in January 2025.<\/p>\n 3. Automating \u201ccommon\u201d inboxes<\/p>\n A third area is the \u201ccommon inboxes\u201d that handle high-volume internal and external email\u2014shared addresses for sales, treasury, finance, and supplier questions. Adobe deployed an agentic AI assistant that auto-tags, prioritizes, routes, and, when criteria are met, auto-responds to emails. Typical queries include supplier billing issues or standard credit-quality questions coming into the treasury from Salesforce<\/a>.<\/p>\n \u201cIn 2025 alone, the system auto-responded to about 300,000 emails across 19 inboxes, saving more than 5,000 hours of manual work and freeing teams to focus on more complex issues,\u201d he says. The tool took about six months to build; beta teams began using it around August 2024, with full rollout in January 2025.<\/p>\n The payoff, he stresses, isn\u2019t headcount cuts but the ability to scale more efficiently as Adobe grows.<\/p>\n Grassroots ideas, decade-long build<\/p>\n Durn traces these finance use cases to Adobe\u2019s long AI journey and a bottom-up idea pipeline. The company has invested in machine learning and AI for more than a decade, initially to understand customer usage patterns and embed intelligence into products\u2014work that laid the groundwork for generative and agentic AI.<\/p>\n Many of the best applications come from \u201creaching down into the organization\u201d and asking employees where AI could remove friction or make their jobs easier, he says. There are more ideas than capacity, so the team prioritizes those with the greatest impact.<\/p>\n When deciding whether to green-light AI investments, Durn focuses on organizational velocity\u2014the ability of back-office functions to keep pace with faster product innovation. If finance doesn\u2019t adopt AI, he argues, it risks becoming a \u201crate limiter of growth.\u201d<\/p>\n The actual spend is modest, he adds; much of the work involves change management and process redesign layered onto Adobe\u2019s technology.<\/p>\n Durn\u2019s perspective on change management coincides with new research from McKinsey<\/a>. To capture the full value of AI, organizations need to go beyond \u201ca piecemeal approach and push for a double transformation\u2014both technical and organizational\u2014that includes reimagining how work gets done across functions and workflows,\u201d according to the report<\/a>. While 88% of organizations surveyed are now experimenting with AI, fewer than 20% report tangible bottom-line results,, the research finds.<\/p>\n How AI is changing his own job<\/p>\n For his own workflow, Durn relies on AI primarily for insight generation. Ahead of earnings, his team loads pre-earnings research reports, Adobe filings, and peer transcripts into an AI-powered workspace to surface themes and likely investor questions.<\/p>\n Scripts and Q&A preparation are then run through models with guardrails to test whether messaging addresses those themes and to ask, \u201cIf I were an investor, what are my key takeaways?\u201d<\/p>\n He sees it as a useful check on clarity and consistency\u2014using AI to validate instincts and sharpen how Adobe communicates with the market.<\/p>\n","protected":false},"excerpt":{"rendered":"Finance chief Dan Durn is turning Adobe\u2019s finance organization into an early proving ground for agentic AI\u2014using autonomous…\n","protected":false},"author":2,"featured_media":352462,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[345,343,344,268,85,46,125],"class_list":{"0":"post-352461","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-artificial-intelligence","8":"tag-ai","9":"tag-artificial-intelligence","10":"tag-artificialintelligence","11":"tag-finance","12":"tag-il","13":"tag-israel","14":"tag-technology"},"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts\/352461","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/comments?post=352461"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts\/352461\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/media\/352462"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/media?parent=352461"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/categories?post=352461"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/tags?post=352461"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}