{"id":76065,"date":"2025-09-30T14:30:41","date_gmt":"2025-09-30T12:30:41","guid":{"rendered":"https:\/\/www.makingscience.com\/?p=76065"},"modified":"2025-09-30T14:30:41","modified_gmt":"2025-09-30T12:30:41","slug":"35-of-cmos-are-stuck-in-ai-pilot-purgatory","status":"publish","type":"post","link":"https:\/\/www.makingscience.com\/en\/blog\/35-of-cmos-are-stuck-in-ai-pilot-purgatory\/","title":{"rendered":"35% of CMOs are stuck in AI pilot purgatory, new research reveals"},"content":{"rendered":"

Report by Making Science finds CMOs risk stagnation, as integration challenges, rising channel complexity, and creative inefficiency block AI progress<\/span><\/i><\/p>\n

LONDON, UK [September 30th 2025]<\/span>: <\/span>Making Science<\/span><\/a>, a global consulting firm specialising in AI-powered digital acceleration and performance marketing, has released new research based on a 2025 commissioned survey conducted on its behalf by <\/span>Forrester Consulting<\/span><\/a> that highlights a striking paradox in AI adoption by US B2C marketing leaders. While 95% of CMOs report positive returns from AI implementation in commerce media campaigns, only 17% use AI as a foundational capability across their marketing operations.<\/span><\/p>\n

The independent survey of 269 CMOs at US B2C companies with annual media spend above $50 million reveals that although AI tools are widely available (80% of CMOs report access to them), most organisations remain unable to scale beyond isolated pilots. More than a third (35%) are stuck in what the research calls \u201cpilot purgatory,\u201d where AI shows promise in some channels but fails to reach enterprise-wide adoption.<\/span><\/p>\n

The study highlights the complexity driving this gap. Over half of CMOs (57%) are managing seven or more active channels, while three-quarters (77%) work with two or more external agencies. Nearly half (46%) place the orch<\/span>estration burden on in-house teams, but only 29% reuse creative efficiently across channels, despite demand for content having multiplied at least three times.<\/span><\/p>\n

Despite these challenges, investment momentum is strong. Two-thirds (66%) of CMOs plan to invest in AI-powered marketing platforms in the next 12 months. In making these decisions, they prioritise vendor reputation, support, and ongoing innovation (61%), the potential for return on investment (56%).<\/span><\/p>\n

\u201c<\/span>This research reveals a critical challenge for CMOs: while the value of AI is clear, the lack of strategic orchestration is a major roadblock<\/span>. <\/span>Integration complexity and siloed processes continue to hold CMOs back,\u201d <\/span>said <\/b>Jos\u00e9 Antonio Mart\u00ednez Aguilar<\/b><\/a> (JAMA), Founder and CEO of Making Science.<\/b> \u201c<\/span>With marketing teams navigating an ever-growing number of channels and formats, the ability to unify creative, media, and data into a cohesive system will be the deciding factor for who truly breaks through and who falls further behind in the competitive landscape.<\/span><\/p>\n

\u201cAI has moved beyond experimentation and is now central to marketing performance: the next wave of AI adoption will not be defined by access to tools, but by the ability to coordinate them across channels and teams.\u201d\u00a0<\/span><\/p>\n

The findings also reveal that real-time optimisation across channels is where most of the CMOs (67%) see the greatest value in AI above creative production at scale, centralised planning or workflow automation. Together, these priorities outline a clear path forward: unifying operations through orchestration rather than adding more disconnected tools.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Report by Making Science finds CMOs risk stagnation, as integration challenges, rising channel complexity, and creative inefficiency block AI progress LONDON, UK [September 30th 2025]: Making Science, a global consulting firm specialising in AI-powered digital acceleration and performance marketing, has released new research based on a 2025 commissioned survey conducted on its behalf by Forrester […]<\/p>\n","protected":false},"author":23,"featured_media":76097,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[913],"tags":[],"class_list":["post-76065","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-technology-ai-en"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.makingscience.com\/en\/wp-json\/wp\/v2\/posts\/76065","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.makingscience.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.makingscience.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.makingscience.com\/en\/wp-json\/wp\/v2\/users\/23"}],"replies":[{"embeddable":true,"href":"https:\/\/www.makingscience.com\/en\/wp-json\/wp\/v2\/comments?post=76065"}],"version-history":[{"count":0,"href":"https:\/\/www.makingscience.com\/en\/wp-json\/wp\/v2\/posts\/76065\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.makingscience.com\/en\/wp-json\/wp\/v2\/media\/76097"}],"wp:attachment":[{"href":"https:\/\/www.makingscience.com\/en\/wp-json\/wp\/v2\/media?parent=76065"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.makingscience.com\/en\/wp-json\/wp\/v2\/categories?post=76065"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.makingscience.com\/en\/wp-json\/wp\/v2\/tags?post=76065"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}