{"id":13497,"date":"2026-06-18T11:23:10","date_gmt":"2026-06-18T11:23:10","guid":{"rendered":"https:\/\/www.salesforce.com\/?p=13497"},"modified":"2026-06-18T11:23:11","modified_gmt":"2026-06-18T11:23:11","slug":"how-to-implement-agentic-marketing","status":"publish","type":"post","link":"https:\/\/www.salesforce.com\/eu\/blog\/how-to-implement-agentic-marketing\/","title":{"rendered":"How to Implement Agentic Marketing in 5 Steps"},"content":{"rendered":"\n

CMOs know that agentic marketing will bring whole new levels of productivity, but deploying and scaling it is another matter. It\u2019s time to address the biggest barriers to agentic AI in marketing and explore how to implement the technology, step by step.<\/em><\/p>\n\n\n\n

In the short time that agentic AI<\/a> has been around, excitement for agentic use cases \u2013 from hyper-personalising campaigns to automating lead nurturing \u2013 has blossomed.\u00a0<\/p>\n\n\n\n

Marketing leaders have been especially drawn in. According to the Salesforce A-shaped CMO research, 85% of CMOs expect their teams to successfully implement agentic AI workflows within the next year \u2013 despite just one in 10 (13%) reporting that agentic AI has actually been deployed within the business.<\/p>\n\n\n\n

That means marketing leaders are committing to a technology they have no first-hand experience with. This is a dangerous blind spot.<\/p>\n\n\n\n

When asked why they have yet to adopt the tech, more than half (53%) of CMOs said the complexity of implementing agentic AI outweighs the potential benefits. <\/p>\n\n\n\n

As agentic AI reshapes the business, it\u2019s setting a new mandate for marketing leaders to become \u2018A-shaped\u2019 CMOs who bring the pillars of science and art of marketing together with the crossbar of operational excellence. An integral part of that journey is to embed agentic AI into their marketing operations.<\/p>\n\n\n\n

Here are my best practices for implementing agentic AI in marketing, based on findings from the <\/strong>A-shaped CMO report<\/strong><\/a> in partnership with The Drum.<\/strong><\/p>\n\n\n\n

1. Demonstrate quick wins with agentic AI\u00a0<\/strong><\/h2>\n\n\n\n

A quarter of CMOs say they have never used agentic AI. Today\u2019s marketing leaders need to get hands-on with AI agents<\/a> to build a real understanding of what\u2019s possible with the technology \u2013 and what isn\u2019t.<\/p>\n\n\n\n

The key to success is to start small and build over time. Here\u2019s how to structure your approach to ensure short-term proof translates into long-term enterprise value.<\/p>\n\n\n\n

Start by clarifying the customer problem you\u2019re trying to solve \u2013 not just for the sake of efficiency, but to relieve a friction point in your buyer\u2019s journey. Identify a single, repetitive workflow that would benefit from more speed, scale, or personalisation, and track your team\u2019s baseline performance in this area.<\/p>\n\n\n\n

From there, monitor ROI signals for 60-90 days to prove the use case\u2019s value. By following an incremental rollout, you can test agentic AI\u2019s capabilities and show stakeholders across the business the impact of the technology operating on the ground.<\/p>\n\n\n\n

A phased adoption helps avoid the \u201cpilot trap\u201d \u2013 where brilliant projects are proven in isolation but never scaled across the enterprise. Compounding small, sequential wins proves the value of agentic marketing before investment is scaled \u2013 increasing the likelihood that your project makes it into enterprise-wide production. <\/p>\n\n\n\n

\u201cOne of the common challenges reported by CMOs is being asked to look at AI, but not being given additional budget. So one of the things that I’ve seen work is starting small and proving and quantifying that value early on. Success breeds success; it’s the incremental and marginal gains that build upon each other. Once you show that initial success, it starts to snowball. The board gets on board, and then you start to unlock more funding and support.\u201d<\/em>

Azlan Raj, CMO<\/em><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

2. Establish strong data foundations<\/strong><\/h2>\n\n\n\n

Before scaling agentic AI use cases, you must audit the data foundations for your deployment. We call this assessing your AI readiness<\/a>.\u00a0<\/p>\n\n\n\n

Understanding your data quality, governance, and security standards will guide the journey. You don\u2019t necessarily need perfect <\/em>data \u2013 very few organisations, if any, can say they have that \u2013 but you do need a connected, accessible foundation for your AI agents to use. Or at least for the use case you have in mind to test.<\/p>\n\n\n\n

Without robust data governance<\/a>, businesses using agentic AI risk security breaches, compliance problems, and customer distrust. And their AI agents simply won\u2019t be able to make smart, accurate, or trustworthy decisions specific to their business context.<\/p>\n\n\n\n

Follow these best practices to clean and standardise your data: <\/p>\n\n\n\n