AI content creation in B2B: Creating high-impact B2B content with AI tools

Highlights

You’ll learn about top strategies and tools for high-impact AI content.

• Plan smarter with AI tools for keyword research and content gap analysis
• Create content faster and at scale using LLMs, such as ChatGPT, Jasper and Claude
• Personalize at scale with Contentstack AI and Personalization solutions
• Maintain quality through human oversight that aligns AI content to brand guidelines

 AI-driven content creation empowers B2B marketers to enhance their content workflows and produce high-quality content that engages their target audience.

AI adoption continues to grow within business circles, and its usage in content creation has been quite extensive. Beyond content marketing, marketers use AI in many other ways, such as brainstorming, data analysis and automation.

In essence, content marketers believe in its efficacy and will continue to deploy it in various areas of content creation.

AI in B2B content creation

AI content creation relies on natural language processing (NLP), which enables AI systems to understand, interpret and generate human language.

These models study the patterns of successful B2B content and replicate them based on specific prompts. Then, you have generative AI, built on large language models that can produce original content that follows specific instructions while maintaining a consistent tone and style.

The current state of AI adoption in B2B content marketing

A recent Salesforce survey reveals that around 51% of marketers already use AI in some form. From that figure, 76% say they use it for content creation. When you zero in on content marketing, the numbers go even higher.

According to CoSchedule, 85% of marketers use AI tools for content creation, and they report that it increased their productivity and saved them over five hours weekly.

Essential AI tools for B2B content creation

Here are some tools that marketers rely on for AI content creation.

Content ideation and planning tools

AI can be used to plan the process, like discovering topics popular with your audience and analyzing your content against competitors. AI simplifies these processes, creating a seamless content planning workflow.

• AI-powered keyword research tools: These tools analyze search trends, competitor content and customer questions to identify high-potential topics. Examples of such tools include SEO AI keyword generator and RyBob keyword tool.
• Content gap analysis tools: These tools examine your existing content libraries against your competitors and customer needs, identifying opportunities for new high-impact content.

Content generation tools

When it comes to actual content creation, generative AI and large language models (LLMs) do the heavy lifting. There are multipurpose AI content creation tools, such as ChatGPT, Claude and Perplexity. These tools can generate content in various forms, including long and short form content, white papers, case studies, emails, ad copies and even images.

Then, you have other tools that offer built-in knowledge bases and are suited to marketing content creation. These tools are mainly generative AI tools built for content marketing, such as Jasper, Copy.Ai and Frase IO.

This content, when produced, needs to get to the right audiences, and there is no better tool to use than Contentstack’s headless CMS. Separating content creation from delivery channels supports an omnichannel marketing strategy. Pair it with Contentstack AI Platform, and you gain the superpowers to generate, optimize and distribute content at scale.

Content personalization tools

Personalization has become essential in B2B marketing, and AI makes it scalable:

Contentstack Personalize enables brands to deliver individualized experiences based on industry, role, behavior and other variables without manually creating countless content variations.

Strategies for creating high-impact B2B content with AI

So, what strategies do marketing teams need to adopt to create high-quality content with AI? For one, they need to know their audience and create content that aligns with their needs and desires. Here are other strategies.

Design an efficient AI-content creation process

Before you start creating content, you need to have a system in place that is sustainable and repeatable. Create a content calendar with clear guidelines for your workflow. Here are other tips to follow.

• Assign roles: Ensure that there are clear roles in the content creation process. For instance, assign specific team members to create outlines and drafts, edit content and manage quality.
• Set up content templates and brand voice guidelines: This provides the structure that AI needs to generate on-brand content. Outline specific formatting, tone and business terms relevant to your business. That way, AI outputs maintain your brand’s unique voice.

Incorporate customer data to personalize content at scale

Choose the right AI based on your content creation needs. For general content creation, tools like ChatGPT or Claude would suffice, while Jasper, Surfer SEO and Content AI lean towards specific marketing content creation.

For personalized content, use AI to model unique buyer personas. AI combines data analysis with marketing insight to develop accurate and nuanced representations of your target audiences.

Finally, use AI to customize content based on intent signals. That way, you can adapt content to buyer behavior and drive stronger buyer engagement. 

Set up stringent quality control

Set up human editorial oversight with a clear mandate to review workflows, document common issues and define criteria for AI content approval. Ensure that AI-generated content and assets undergo thorough checks and reviews before they are published.

The editors should validate, fact-check and compare AI output against internal standards to ensure that outputs align with brand standards. Fine-tune the AI systems and tools to ensure they preserve the brand's voice and communication style across outputs.

Measure the impact of AI content

When you measure the impact of AI on your content creation workflow, you can learn and improve from the results. Measure time saved, content volume increase and engagement metrics for AI-generated content vs. your regular human-written content. You can deploy an A/B test to compare and see which approach resonates more with your audience.

Optimize content performance

Set your quality criteria and use AI systems to identify which topics, formats and approaches deliver the best results. By doing so, you can use the data to improve AI content output. Continue to monitor AI performance in your content workflow to identify and adapt to changing patterns in audience response and market conditions.

Implementing AI in your B2B content workflow

B2B teams should integrate AI into their content workflow to create a seamless process from start to finish. Here are the steps to take.

1. Audit current content workflow: Begin by auditing your current workflow to identify content tasks that consume the most resources relative to their strategic value. These high-effort, low-creativity tasks are usually the best ones to implement AI, at least initially.
2. Create the optimal human-AI collaboration model: The success of most AI deployments depends on how it dovetails with human intervention. You want to create a workflow that ensures there is proper human oversight to maintain the quality of AI interventions.
3. Determine tasks to automate: Categorize content activities based on brand sensitivity, complexity and creativity requirements. This allows you to determine what to automate with AI or what to leave to human expertise. For instance, you can use AI to create drafts for blog content while you assign thought leadership articles to content experts, since it requires more original insights.
4. Integrate AI with existing marketing tech stack: Integrate AI with your current systems, which may include your content management system, marketing automation tools or your customer data platform.
5. Train your team on effective AI usage: Such training helps marketers develop the skills to be productive with AI. That includes writing precise AI prompts, evaluating AI outputs and editing AI-generated content. Ensure that your content marketers understand AI prompt engineering so they can write clear, specific instructions that guide AI toward desired outcomes.

Overcoming limitations of AI usage in content creation

AI content creation in B2B has some notable limitations that content marketers have to be aware of. For one, quality control must be prioritized, and the workflows must adhere to global ethical standards.

Addressing content quality concerns

Even the most advanced AI system can push out incorrect information. Ensure you fact-check AI content and run it against your guidelines to be sure it adheres to your quality standards. Also, get editors to proofread and check AI content to ensure it is not generic or bland. Adequate human oversight helps you avoid AI content mishaps.

Managing ethics in AI usage

Be transparent about AI usage and outline how and where AI contributes to content creation. You also want to monitor problematic patterns and language to avoid biased outputs that may alienate portions of your audience or misrepresent important issues. Finally, set up a robust system to protect customer data and seek informed content when required.

Case study

Golfbreaks

Golfbreaks struggled with managing content across multiple international markets, and this prompted them to sign up for Contentstack's AI Accelerator. They were trained in using the AI assistant, Brand Kit and Automate.

The solutions include automated translation workflows, content optimization and personalization rules. That way, they could launch campaigns faster while maintaining consistent brand messaging across all regions.

Jack Simkins said. With Contentstack’s help, our AI use case has been expanded into a much more powerful tool that’s helping us to save time and move faster. 

Learn more about Golfbreaks' success with Contentstack’s AI.

The future of AI in B2B content creation

While AI has become a critical part of the modern marketer's toolkit, there is so much more it can do, even within the narrow confines of content creation. Here are a few things to expect in the future.

• Advancements in Generative Adversarial Networks (GANs): GANs use two neural networks to compete against each other, enabling them to learn and fine-tune outputs. These systems will improve the quality of AI-generated assets, especially for visual content that complements written materials.
• Multimodal content creation: This is a process where AI integrates multiple media materials and outputs to create more engaging content. This capability will generate complementary text, images and video assets, creating more cohesive content experiences.
• Hyper-personalization: Unlike regular personalization, which relies on historic data, AI will be deployed to learn from real-time data and personalize content on the go. 

How AI will continue to reshape B2B content strategies

While AI adoption gains momentum, marketers at enterprise organizations are seeking more ways to extract its benefits. Here are a few of those ways. 

• Content ecosystems rather than assets: AI will enable a more integrated content network that is dynamic and adapts to user behavior.
• Real-time content generation: B2B Content marketers will deploy AI to create on-demand content and marketing materials based on immediate customer needs rather than pre-planned campaigns.
• Continuous optimization: B2B companies will deploy AI to constantly refine content based on performance data.

Preparing your team for these changes involves cultivating both technical understanding of AI capabilities and the strategic thinking needed to apply these tools to genuine business challenges.

FAQ section

What are the most effective strategies for using AI in content creation?

Start with clear brand guidelines, focus AI on repetitive tasks and maintain human oversight for quality control. Also, analyze performance data and use it to refine AI outputs.

How can AI be used in B2B content creation?

Apply can be applied to research and identity topics, draft content and personalize at scale. It can also be used to adapt content to multiple channels and audiences, and to predict content performance across the B2B buying journey.

How can generative AI help B2B sales become more effective?

Marketers can use generative AI to create personalized sales content, automate proposal creation and generate custom objection handling. They can also use it to produce follow-up materials based on how prospects engage.

What are AI tools for content creation?

Popular AI tools for B2B content creation include general-purpose AI content tools like Copy.ai, ChatGPT and Claude, as well as specialized marketing content tools such as Jasper and Frase.io.

Learn more

According to the data, AI has come to stay, and its use in B2B content creation is now widely accepted. However, marketing teams must use it the right way—to complement human expertise. That way, they can always maintain quality and deliver on-brand content. 

Building on that, you need the right tool to automate the process and publish at scale. Contentstack AI and Contentstack EDGE combine AI and no-code automation, enabling you to reduce manual work, orchestrate processes and scale across systems.

Deliver content specific to your audience, produce AI content that aligns with your brand’s voice, tone and style, and deploy insights to optimize content operations. Talk to us today to learn more.