{"id":67977,"date":"2026-09-03T21:31:36","date_gmt":"2026-09-03T21:31:36","guid":{"rendered":"https:\/\/www.elixirr.com\/en-gb\/?p=67977"},"modified":"2026-09-03T21:34:00","modified_gmt":"2026-09-03T21:34:00","slug":"maximising-the-return-on-ai-lessons-from-googles-advertising-platform","status":"publish","type":"post","link":"https:\/\/www.elixirr.com\/en-gb\/maximising-the-return-on-ai-lessons-from-googles-advertising-platform\/","title":{"rendered":"Maximising the return on AI: Lessons from Google’s advertising platform"},"content":{"rendered":"\n
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Artificial intelligence, specifically agentic AI, is quickly becoming a standard capability. Organisations across nearly every industry now have access to increasingly sophisticated models, copilots and automation tools. As these technologies become more widely available, the conversation is beginning to shift. The question is no longer whether a business has access to AI, but why some organisations using similar technologies continue to achieve dramatically different results.<\/p>\n

Digital advertising has quietly become one of the world’s largest real-time experiments in applied artificial intelligence. Every day, platforms like Google Ads make billions of decisions about where advertisements should appear, who should see them, how budgets should be allocated and which creative is most likely to resonate with a customer. It is easy to assume that Google’s AI is responsible for those outcomes. Looking more closely at how the platform operates suggests something different.<\/p>\n

Before Google’s AI is ever given the opportunity to optimise a campaign, the business has already made the decisions that matter most. Leaders determine whether success means increasing revenue, acquiring new customers, improving profitability, or maximising return on advertising spend. Those strategic choices establish what the platform is trying to accomplish.<\/p>\n

Once those objectives have been established, the Merchant Center provides the structured product and business data that enables Google’s AI to optimise toward them. Rather than serving as a simple repository of product information, the Merchant Center organises products, pricing, availability, promotions and other business information into a format the platform can understand. Google’s AI is not asked to infer what the business sells or how its products relate to one another. That understanding has already been established through the way the business structures and maintains its data.<\/p>\n

Seen this way, Google’s advertising platform is about far more than sophisticated algorithms. Strategy defines the objective, structured data provides the foundation and AI applies both at a speed and scale no team of marketers could replicate manually. The quality of the AI’s decisions is shaped long before the model begins making them.<\/p>\n

The same dynamic appears well beyond digital advertising.<\/p>\n

One recent engagement involved helping a regional U.S. bank modernise its data environment after fragmented information had limited the organisation’s ability to generate meaningful insights. Although the symptoms were most visible in reporting and business intelligence, the engagement revealed that stronger analytics alone would not solve the problem. The bank first needed a trusted data foundation. Rather than beginning with new dashboards, the team modernised the enterprise data architecture, rebuilt the Customer360 model and implemented a data-as-products strategy. With that foundation in place, the organisation was then able to modernise reporting and analytics, enabling more reliable insights, greater self-service capabilities and broader data-driven decision making.<\/p>\n

From Google’s advertising platform to one of our recent engagements with a regional US bank, the conclusion is remarkably consistent. Improving the technology alone would not have changed the outcome. Better results came from strengthening the objectives, data and enterprise foundations that allowed the technology to perform effectively.<\/p>\n

Perhaps this is where many organisations unintentionally narrow the conversation around AI. We often discuss data as though it were the end goal, when its real value lies in what it enables. AI cannot create understanding from poorly organised or incomplete information and it cannot compensate for unclear business objectives. Its effectiveness depends on the strength of the foundation supporting it.<\/p>\n

This changes how we should think about creating value from AI. For years, organisations differentiated themselves through access to technology. Today, access to AI is rapidly becoming an expectation rather than an advantage. As the technology becomes more widely available, differentiation shifts toward the work that surrounds it.<\/p>\n

Ironically, many of the investments that generate the greatest return from AI do not resemble AI initiatives at all. They involve clarifying business objectives before selecting a model, modernising fragmented data environments before deploying copilots, strengthening governance so information can be trusted across the organisation and redesigning processes that allow AI to scale effectively. None of those efforts generate the same excitement as launching a new AI capability, yet each one increases the value of every AI capability that follows.<\/p>\n

Technology will continue to evolve, models will continue to improve and today’s leading capabilities will eventually become commonplace. The organisations that realise the greatest value from AI will not be distinguished simply by having access to better AI. They will be distinguished by building businesses that allow commoditised AI to create exceptional value.<\/p>\n

The question for leaders is no longer simply where AI can be deployed, but whether the foundations are in place to turn it into meaningful value.<\/p>\n

Learn how we help organisations turn AI ambition into impact:<\/p>\n <\/div>\n <\/div>\n<\/section>\n\n\n\n

\n
\n Explore our AI services<\/span><\/a> <\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

The organisations that realise the greatest value from AI will be distinguished not by access to better technology, but by the foundations they build around it.<\/p>\n","protected":false},"author":142,"featured_media":68035,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[116],"tags":[],"related_service":[45],"related_industry":[62],"class_list":["post-67977","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog"],"acf":[],"yoast_head":"\nMaximising the return on AI: Lessons from Google's advertising platform<\/title>\n<meta name=\"description\" content=\"Explore why maximising AI value depends on clear business objectives, trusted data and strong enterprise foundations, not better technology alone.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link 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class=\"wp-component-card__preview-icon\">\n <span class='edwp-svg '><svg width=\"47\" height=\"47\" viewBox=\"0 0 47 47\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<g>\n<path d=\"M23.4141 0.539062C36.1232 0.539183 46.4258 10.8416 46.4258 23.5508C46.4257 36.2599 36.1231 46.5624 23.4141 46.5625C10.7049 46.5625 0.402465 36.2599 0.402344 23.5508C0.402344 10.8415 10.7048 0.539062 23.4141 0.539062ZM23.4141 1.68945C11.3606 1.68945 1.55273 11.4974 1.55273 23.5508C1.55286 35.6041 11.3607 45.4111 23.4141 45.4111C35.4673 45.411 45.2743 35.604 45.2744 23.5508C45.2744 11.4974 35.4674 1.68957 23.4141 1.68945Z\" fill=\"currentColor\"\/>\n<path d=\"M19.2841 33.6992C18.9579 33.6986 18.6374 33.6111 18.3543 33.4454C17.7167 33.0759 17.3203 32.3585 17.3203 31.5797V15.8189C17.3203 15.0379 17.7167 14.3227 18.3543 13.9531C18.6442 13.7827 18.9735 13.6951 19.3078 13.6994C19.6421 13.7037 19.9692 13.7998 20.2548 13.9776L33.4237 22.0406C33.6981 22.2166 33.9244 22.461 34.0812 22.751C34.238 23.0409 34.3203 23.3668 34.3203 23.6982C34.3203 24.0295 34.238 24.3555 34.0812 24.6454C33.9244 24.9353 33.6981 25.1798 33.4237 25.3558L20.2527 33.421C19.9604 33.6017 19.6256 33.6979 19.2841 33.6992Z\" fill=\"currentColor\"\/>\n<\/g>\n<\/svg>\n<\/span> <\/div>\n <\/figure>\n <div class=\"wp-component-card__content edwp-row-load\">\n <p class=\"wp-component-card__eyebrow\">\n Articles <\/p>\n <a href='https:\/\/www.elixirr.com\/en-gb\/maximising-the-return-on-ai-lessons-from-googles-advertising-platform\/' class='wp-component-card__title'>\n <h2>\n Maximising the return on AI: Lessons from Google’s advertising platform\n <\/h2>\n <\/a> <div class=\"wp-component-card__description\">\n The organisations that realise the greatest value from AI will be distinguished not by access to better technology, but by the foundations they build around it. <\/div>\n <div class=\"wp-component-card__meta\">\n <p class=\"wp-component-card__date\">\n 03 September 2026 <\/p>\n <div class=\"wp-component-card__terms\">\n <div class=\"wp-component-tags edwp-component\">\n <div class=\"wp-component-tags__tag\">\n Technology <\/div>\n <div class=\"wp-component-tags__tag\">\n AI Consulting <\/div>\n <\/div>\n <\/div>\n <\/div>\n <div class=\"wp-component-card__button-wrapper\">\n <button class=\"btn btn--link arrow wp-component-card__button\">\n Read more <span class='edwp-svg '><svg width=\"20\" height=\"20\" viewBox=\"0 0 20 20\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<g id=\"Lg\">\n<path id=\"Vector\" d=\"M1.12509 9.50162H15.8648L9.43259 3.06941C9.374 3.0113 9.3275 2.94216 9.29576 2.86599C9.26403 2.78981 9.24769 2.70811 9.24769 2.62559C9.24769 2.54307 9.26403 2.46137 9.29576 2.38519C9.3275 2.30902 9.374 2.23988 9.43259 2.18177C9.54971 2.06535 9.70814 2 9.87328 2C10.0384 2 10.1969 2.06535 10.314 2.18177L17.8151 9.6829C17.8737 9.74101 17.9202 9.81014 17.9519 9.88632C17.9837 9.96249 18 10.0442 18 10.1267C18 10.2092 17.9837 10.2909 17.9519 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