5 Best Practices to Leverage AI in B2B Marketing Automation

Since the public release of various open and closed-source large language models (LLMs), the adoption and utilization of AI-powered tools and technologies have skyrocketed in Business-to-Business (B2B) marketing workflows.

The intuitive user interfaces of these powerful, easy-to-use, and affordable tools even allow professionals with non-technical backgrounds to automate tasks or parts thereof at scale.

However, while leveraging these tools to increase the volume and improve the quality of work, marketers might find it difficult to select the right solution, determine the scope of automation, train their team members, etc., which can lead to inefficiencies and extravagant costs.

In this article, let’s look at five best practices that will help B2B marketers start on the right foot with AI.

Best Practices with AI

1. Determine areas of automation

The areas that can be automated in your B2B marketing workflows depend on factors like your organizational goals, available resources, current tools, performance differential, etc.

Pinpointing which particular aspects of your marketing efforts can be profitably automated is the first step towards enhancing your workflows with AI in a measured way.

B2B marketing teams can start by auditing their workflow to find repetitive, routine, and administrative tasks. Then, they can list the relevant action items for each of those tasks to determine the breadth and scope of AI automation that can be integrated into those processes.

For instance, you can collate all of your past marketing lead-generation data to automate your pipeline forecasting process, enabling you to proactively monitor the potential ROI of your promotional efforts.

Other areas within a B2B marketing workflow that can be automated to varying degrees include social media scheduling, lead scoring, providing customer service through chatbots, personalizing emails, and retargeting through programmatic ads.

2. Enforce a data governance framework

A data governance framework consists of a set of metrics, standards, procedures, and policies that provide guidance to B2B marketers on how different kinds of data will be collected, analyzed, managed, stored, transferred, archived, or deleted.

Such a framework is essential for effective automation of marketing processes and workflows as it ensures that the data collected, whether it is from prospects, leads, or customers, is accurate, clean, and adheres to regulatory laws such as GDPR and CCPA.

Consequently, this gives the right team members the right level of access to sensitive data and facilitates effective inter-departmental collaboration, allowing for more accurate and utilitarian automation processes while protecting the organization from legal risks.

The key elements of such a framework for a B2B marketing team looking to automate tasks and processes within their workflow include the threshold quality of data, the people who should have access to it, the procedures for its analysis, management, etc., the key metrics to be monitored, and tools to be used.

3. Prioritize continuous learning

As you already know, the digital marketing world constantly changes. From the algorithm updates of the search engines to the addition of new platforms, B2B marketers need to keep an eye on the industry trends.

The same logic holds true for rapidly evolving technologies such as AI where new models, apps, integrations, and regulations come up every other day.

Although regularly monitoring all this news can get challenging, particularly for small B2B teams with limited resources, prioritizing continuous learning while managing AI-powered automation to make your marketing workflow efficient is critical for gaining and maintaining a competitive advantage.

B2B marketers can listen to podcasts like Breaking B2B by Sam Dunning and Confessions of a B2B Marketer by Tom Hunt, follow YouTube channels like The AI Advantage and B2B Marketing YouTube, and subscribe to newsletters of authoritative brands like HubSpot and Marketing AI Institute.


Additionally, you can also leverage LLMs that have internet access to get a quick roundup of all the recent trends. Tools like ChatGPT 4.5, Microsoft Copilot, Google Gemini, and Perplexity AI can come in handy in this regard.

4. Measure the AI impact

Including AI-powered tools in your B2B marketing workflows may increase your expenses, change your existing SOPs, and require you to rethink your strategies. All of these can have a huge effect on the bottom line of your business, making the close monitoring of the impact of AI-driven tools on your B2B marketing processes pivotal.

You must have set a few goals or defined some objectives that you wish to achieve through AI automation, as mentioned in the first best practice earlier. This could range from getting more leads, publishing content faster, and generating reports faster.

Hence, you can start measuring the impact of these tools on your B2B marketing processes by examining whether those goals or objectives have been achieved. For instance, you can compare how quickly you used to finish a draft before and after you integrated AI into your content creation process.

At the same time, you also need to look for any unprecedented impact these tools had on your workflow. For instance, you may have spent more money on these tools than you had earlier predicted, whether directly (usage-based pricing) or indirectly (training the team).

After you have the tangible numbers in front of you, it is crucial to sit with your team to find out how to get more out of these automation tools, whether it is switching to a different solution or tweaking your current workflows.

5. Maintain transparency with customers

It is apparent that AI-powered automation tools in your B2B marketing workflow will be handling customer data in varying degrees, making it essential for you, as a brand, to keep your buyers informed about how their information is handled.

This will build trust, set realistic expectations, keep you compliant, differentiate you from the competition, and encourage you to use these rapidly evolving technologies responsibly.

B2B marketers should clearly disclose how they plan to use AI-based technologies to handle their data and what benefits it brings to the end user in their privacy policies. Additionally, they can take steps to educate their audience about these technologies via content.

Furthermore, it is recommended that you offer opt-out options to your customers while explicitly highlighting how this will affect their experience with your brand.

Wrapping up

AI-powered tools in B2B marketing workflows help brands increase the quality and volume of their output. However, it can be difficult to select the right tools and choose which tasks or processes can be enhanced with AI.

B2B marketers can navigate these challenges by tangibly defining the areas of automation, enforcing a robust and scalable data governance framework, prioritizing continuous learning about all things AI, regularly measuring the impact of these tools on their workflow, and maintaining transparency with their audience and customers about how they use AI.

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