{"id":42331,"date":"2026-04-09T16:47:46","date_gmt":"2026-04-09T15:47:46","guid":{"rendered":"https:\/\/www.dataiq.global\/?post_type=100-alumni&p=42331"},"modified":"2026-04-30T02:17:00","modified_gmt":"2026-04-30T01:17:00","slug":"anu-krishnan-chief-data-analytics-officer-chevron","status":"publish","type":"100-alumni","link":"https:\/\/www.dataiq.global\/devstage\/dataiq100\/anu-krishnan-chief-data-analytics-officer-chevron\/","title":{"rendered":"Anu Krishnan, Chief Data & Analytics Officer, Chevron"},"content":{"rendered":"

Paul Hatley, Chief Research and Product Officer, DataIQ: \u201cDataIQ\u2019s Number One recognizes a form of leadership that goes well beyond technical execution. It is in\u00a0Anu Krishnan, Chief Data\u00a0and\u00a0Analytics Officer at Chevron,\u00a0that\u00a0we\u00a0see a leader who has consistently combined industrial depth with a clear-eyed understanding of how data and AI create value at scale.<\/span><\/i>\u00a0<\/span><\/p>\n

\u201cAcross a 30-year career in the energy sector, Anu has\u00a0operated\u00a0where complexity is the norm. Her work reflects an ability to translate ambition into operating reality,\u00a0whether\u00a0that\u2019s\u00a0scaling global AI capabilities, delivering enterprise data platforms, or embedding governance disciplines that make data usable, trusted, and repeatable. Building and leading teams of over 1,600 specialists is no small feat; doing so while\u00a0maintaining\u00a0coherence, standards, and measurable business impact is where her leadership stands apart.<\/span><\/i>\u00a0<\/span><\/p>\n

\u201cWhat distinguishes Anu is her tenacity in focusing on the fundamentals that many\u00a0organizations\u00a0overlook. From\u00a0establishing\u00a0robust data governance to delivering significant cost efficiencies, she has consistently prioritized long-term value over short-term wins. At the same time, she has\u00a0demonstrated\u00a0a willingness to challenge entrenched thinking.<\/span><\/i>\u00a0<\/span><\/p>\n

\u201cHer influence extends beyond delivery into how\u00a0organizations\u00a0think about data leadership\u00a0by being\u00a0pragmatic, value-led, and grounded in communication and trust as much as technology.<\/span><\/i>\u00a0<\/span><\/p>\n

\u201cThis recognition\u00a0as the 2026 DataIQ North America Number One\u00a0reflects a leader who is advancing data and AI\u00a0and\u00a0helping to shape how the discipline matures across the industry.\u201d<\/span><\/i>\u00a0<\/span><\/p>\n

 <\/p>\n

Anu Krishnan is Chief Data and Analytics Officer at Chevron, where she leads enterprise data and AI strategy to drive operational performance and long-term transformation across the organization. With a 30-year career in the energy sector, including more than 14 years focused specifically on data and AI leadership, Anu brings deep industry\u00a0expertise\u00a0and\u00a0a track record\u00a0of scaling data capabilities globally.<\/span>\u00a0<\/span><\/p>\n

Prior to joining Chevron, Anu played\u00a0a central role\u00a0in shaping the data and AI landscape at Shell, contributing significantly to the company\u2019s digital transformation from 2013 to 2025. During this time, Anu led AI and\u00a0GenAI platform strategy, balancing external solutions with in-house development, and scaled data science and AI and ML initiatives globally to maximize business value.<\/span>\u00a0<\/span><\/p>\n

Anu also led Shell\u2019s digital platforms strategy, overseeing cloud migration to Azure and AWS, and delivering more than 30 production data platforms and data lakes. She built and scaled global data and analytics teams to over 1,600 professionals across data engineering, AI, data science, visualization, and information management.<\/span>\u00a0<\/span><\/p>\n

A strong advocate for governance and standardization, Anu\u00a0established\u00a0enterprise data governance practices spanning master data management, data quality, and data cataloging, while promoting the development and reuse of data products. Her work also delivered significant cost efficiencies, including more than $70 million in annual savings through technology optimization and supplier rationalization.<\/span>\u00a0<\/span><\/p>\n

Anu\u2019s leadership reflects a focus on combining scale, discipline, and innovation to embed data and AI into core business operations.<\/span>\u00a0<\/span><\/p>\n

 <\/p>\n

As a data and AI leader, which traits and skills do you think matter most, and which of those have been most influential for you in your current position?<\/span><\/b>\u00a0<\/span><\/h3>\n

\u201cKey skills and traits that have helped me over my career\u00a0include: being able to create a strong value focused business case to seek funding\u00a0and\u00a0approval; getting stakeholders excited and having them tell the story about how the AI solution added value to their business; sharing success stories (and failures) and highlighting collaboration across teams; and sharing competitive intelligence with senior leadership to drive faster decisions.\u201d<\/span>\u00a0<\/span><\/p>\n

\u00a0<\/span><\/p>\n

Reflecting on your career, what is one non-traditional piece of advice (outside of technical skills) you would give to an aspiring data or AI leader aiming for the C-suite?<\/span><\/b>\u00a0<\/span><\/h3>\n

\u201cMy advice\u00a0would be\u00a0focus on storytelling and answering the \u2018so what\u2019 aimed at the relevant audience. Leadership is always focused on value and not about the technology, so do not go into technical details (unless\u00a0it’s\u00a0a leader who loves technology).\u201d<\/span>\u00a0<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Paul Hatley, Chief Research and Product Officer, DataIQ: \u201cDataIQ\u2019s Number One recognizes a form of leadership that goes well beyond technical execution. It is in\u00a0Anu Krishnan, Chief Data\u00a0and\u00a0Analytics Officer at Chevron,\u00a0that\u00a0we\u00a0see a leader who has consistently combined industrial depth with a clear-eyed understanding of how data and AI create value at scale.\u00a0 \u201cAcross a 30-year […]<\/p>\n","protected":false},"author":19,"featured_media":42972,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","_searchwp_excluded":"","footnotes":""},"100-designation":[1486],"100-search-term":[1489],"class_list":["post-42331","100-alumni","type-100-alumni","status-publish","format-standard","has-post-thumbnail","hentry","100-designation-100-brands-2026-americas","100-search-term-2026-north-america-brands"],"acf":{"sort":"","rank":1,"forename":"Anu","surname":"Krishnan","fullname":"Anu Krishnan","jobtitle":"Chief Data & Analytics Officer","organisation":"Chevron ","introduction":"","content_2":"","content_3":"","content_4":"","100_thumbnail_image":42972,"affinoid":""},"publishpress_future_action":{"enabled":false,"date":"2026-05-22 10:58:04","action":"change-status","newStatus":"draft","terms":[],"taxonomy":"100-designation","extraData":[]},"publishpress_future_workflow_manual_trigger":{"enabledWorkflows":[]},"_links":{"self":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/100-alumni\/42331","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/100-alumni"}],"about":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/types\/100-alumni"}],"author":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/users\/19"}],"replies":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/comments?post=42331"}],"version-history":[{"count":3,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/100-alumni\/42331\/revisions"}],"predecessor-version":[{"id":43571,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/100-alumni\/42331\/revisions\/43571"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/media\/42972"}],"wp:attachment":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/media?parent=42331"}],"wp:term":[{"taxonomy":"100-designation","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/100-designation?post=42331"},{"taxonomy":"100-search-term","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/100-search-term?post=42331"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}