Our research has found<\/a> that marketers estimate AI will save them an average of five hours a week. However, nearly 40% of marketers say they don\u2019t know how to get the most out of new AI capabilities, especially generative AI<\/a>. This means we are in a crucial time of learning and optimising.<\/p>\n\n\n\n There\u2019s one more twist. AI adoption<\/a> is about organisational buy-in as much as individual training. We spoke with Jaime L\u00f3pez, senior director of marketing operations at Aiven.io<\/a>, about how you can set up your company and immediate team for AI success.<\/p>\n\n\n\n There\u2019s no single trick to B2B marketing \u2013 there are dozens. Freshen up on the fundamentals and learn more about how AI can help you through every stage of your funnel.\u00a0<\/p>\n\t\t\t\n\t\t\t\n\t\t\t\t\t\t\t Sales and marketing alignment is the foundation of good B2B marketing<\/a>. And data is the starting point for the alignment. AI models need to be trained to produce high-quality output and they can\u2019t learn the right lessons without good data. \u201cTwo-thirds of marketers say their company\u2019s data, the foundational layer, is not set up for generative AI,\u201d L\u00f3pez explained.<\/p>\n\n\n\n Disparate data streams often live in different tools, departments, or databases. This can make it very difficult to get a complete picture of customers, identify the value of accounts, and score or grade leads. It\u2019s a recipe for a less-informed customer strategy.<\/p>\n\n\n\n This is why you need to prepare your data infrastructure for AI by unifying your data<\/a>. Combining all your data on one platform gives your AI the most complete picture of your customers to work off. Simply put, you need this data to be clean (no errors or duplications) and complete (no missing info), so AI can interpret it and deliver useful feedback.\u00a0<\/p>\n\n\n\n The good news is that your marketing team has a great opportunity to set the tone for how AI is used across your organisation. You\u2019re closer to the customers than most other departments, and can show how adopting AI<\/a> helps you be more efficient.<\/p>\n\n\n\n \u201cMarketing ops professionals in particular have a very comprehensive view of the customer journey, they have access to a wealth of data, and they have the analytical skills to leverage it,\u201d L\u00f3pez said.<\/p>\n\n\n\n But marketing can\u2019t do this alone. The entire organisation needs to read from the same playbook. This starts by ensuring your organisation has clearly documented AI policies and boundaries, and that those policies align with your wider business objectives. Making these training resources accessible to all departments \u2013 not just marketing \u2013 is critical to ensure everyone is using AI ethically and safely. This could mean starting with AI-driven personalisation in email marketing or predictive analytics for lead scoring, or taking advantage of generative AI capabilities to help scale content creation. Before you start realising the power of AI in B2B marketing, it\u2019s essential to maximise the out-of-the-box capabilities of your existing stack, particularly your marketing automation<\/a> and customer relationship management (CRM)<\/a> platforms.\u00a0<\/p>\n\n\n\n If you\u2019re not using a platform with built-in AI capabilities, the next step is evaluating your existing stack for AI compatibility. <\/p>\n\n\n\n \u201cAsk yourself: can your current tools support AI?\u201d L\u00f3pez said. \u201cWill they support it in the future? And if not, what\u2019s needed to get there? This step is crucial for building a roadmap that incorporates AI seamlessly.\u201d You can\u2019t finish until you start, so in some ways, the most important step is to set the direction and make the initial, strategic move. That\u2019s not to say you should rush into it, only that it\u2019s time to get the engine running. You\u2019ll also want to make sure you\u2019re fuelling the engine properly, and that really comes down to two things: culture and strategy. \u201cThis isn\u2019t about becoming data scientists overnight, but ensuring everyone, from designers to performance marketers, has basic AI literacy to contribute meaningfully,\u201d L\u00f3pez said. \u201cWe owe it to our teams to give them that bridge to the future.\u201d As AI evolves, your strategy should scale and adapt to those changes, allowing for a smoother journey. This means setting clear milestones, from early adoption to full integration<\/a>, ensuring that your journey is progressive and adaptable.<\/p>\n\n\n\n Experimentation is also vital \u2013 and the only proven way to constantly improve your results. Try new things, learn from failures, and celebrate successes. With the dramatic increase in scale that AI provides us, we can afford to test more, fail more, faster and at less cost. <\/p>\n\n\n\n If you have taken AI literacy seriously, your team members will be able to both innovate in their area of expertise and constructively challenge the decisions of the team at large. In the end, a successful AI takeoff is not led by only one or two people: it\u2019s a true team effort. <\/p>\n\n\n\n Once you have your data foundation in place, your AI can get to work. Let\u2019s look at Marketing Cloud Account Engagement<\/a> as an example.\u00a0<\/p>\n\n\n\n Its AI can help identify high-value accounts that are worth your team\u2019s maximum time and effort and give recommendations about when and how much to reach out to them. It can get as granular as using lookalike audiences and predictive AI to identify ideal send times or creating personalised subject lines with generative AI. <\/p>\n\n\n\n Here\u2019s how Marketing Cloud Account Engagement\u2019s AI capabilities can boost your AI in B2B marketing efforts. <\/p>\n\n\n\n Struggling to come up with an eye-catching email subject line, or need copy ideas for your landing page? With a human-in-the-loop approach<\/a>, generative AI capabilities in Marketing Cloud Account Engagement can help.<\/p>\n\n\n\n AI can help you write:<\/p>\n\n\n\n While it\u2019s still crucial to have a human guide these efforts (trust us: customers can tell), AI can be the marketing assistant you never knew you needed.<\/p>\n\n\n\n\n4 steps for building AI in B2B marketing<\/h3>\n\n\n\n
\n
See how AI boosts B2B marketing<\/h2>\n\t\t\t\t\t\t\t
![\"\"](\"https:\/\/www.salesforce.com\/eu\/blog\/wp-content\/themes\/salesforce-blog\/dist\/images\/offer-block\/offer-illustration-layout-one.png\")
\n\n\t\t\n\t\t\t\t\t![\"\"](\"https:\/\/www.salesforce.com\/eu\/blog\/wp-content\/themes\/salesforce-blog\/dist\/images\/offer-block\/offer-accent-layout-one.png\")
\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\t\t\t![\"\"](\"https:\/\/www.salesforce.com\/eu\/blog\/wp-content\/themes\/salesforce-blog\/dist\/images\/offer-block\/offer-cloud-layout-one.png\")
\n\t\t\n\t<\/div>\n\n\n\nUnify and prepare your data for AI<\/h2>\n\n\n\n
This is a big concern for B2B marketers<\/a> and revenue teams that have disconnected data systems. Before you can see an impact with AI in B2B marketing, you need to unify that customer data.<\/p>\n\n\n\nStart being your company\u2019s AI leaders<\/h2>\n\n\n\n
Leading AI adoption across the entire organisation can be overwhelming. You need to start small with narrow and impactful use cases. It\u2019s tempting to deploy AI across all facets of marketing, but a focused approach with smaller, quicker use cases allows for deeper understanding, clear measurement of impact, and iterative learning. <\/p>\n\n\n\n
Small wins help build momentum and support for more extensive AI applications.<\/p>\n\n\n\nPrepare your MarTech build for scale and flexibility <\/h2>\n\n\n\n
Finally, choose technologies that will grow with your AI ambitions, accommodating future advancements without skipping a beat. AI will place a premium on scalability and flexibility. Your infrastructure must handle increased data loads and complex processing. The biggest benefit at the heart of almost every AI offering is \u201cdo more faster and better,\u201d and you need to be sure that proposition holds as your teams, audiences, and goals grow. <\/p>\n\n\n\nBuild a scalable AI roadmap and a culture open to innovation <\/h2>\n\n\n\n
A data-driven culture<\/a> is the foundation of successful AI in B2B marketing implementation. It\u2019s not primarily about technical expertise, L\u00f3pez explained, so much as curiosity and literacy.\u00a0<\/p>\n\n\n\n
Ensure your decisions are backed by data, showing accountability across the team. In the world of AI, understanding and interpreting data is no longer optional \u2014 it\u2019s essential. That may require skills assessments and training to ensure your team is properly set up for success. Ensuring everyone has AI literacy and can contribute meaningfully is crucial. <\/p>\n\n\n\nHow Marketing Cloud Account Engagement can help AI in B2B marketing<\/h2>\n\n\n\n
Content creation<\/h3>\n\n\n\n
\n