The transformative edge of AI in content writing for B2B success

The transformative edge of AI in content writing for B2B success  

Today’s B2B market is rapidly evolving, and so are the tools and technologies at the disposal of marketers, including the game-changing potential of Artificial Intelligence (AI) in content creation. However, this powerful tool comes with certain risks that must be carefully managed. 

With the increasing need for high-quality content across digital platforms, the synergy between human strategic thinking and creativity, and AI innovation presents huge promise for stimulating business growth in the B2B sector. However, this joined-up approach is essential to maintain that level of quality – marketers have rightly expressed concerns over the possibility of lazy businesses producing mediocre content at scale, which would be easy to do. 

Below, we will delve into the significant benefits that AI-powered content writing can offer your business and why it represents a wise investment for the future, if done right. We also look at the risks of getting ‘greedy’ and taking a powerful but ultimately less creative tool for granted. 

What are the advantages of AI in B2B Content Creation?

Efficiency and Speed

Gone are the days when content production was strictly limited by human speed and work hours. AI’s exceptional computing power champions efficiency, producing content at a pace beyond human reach. This not only enables increased content creation but also liberates marketers and content creators to prioritize tasks that demand a human touch, like strategy formulation and creative storytelling.

In this new world, the human focus switches to spending more time identifying audiences, defining messaging and crafting productive prompts. Once this is done, AI swiftly brings the content to life, although nothing replaces the skill of a copywriter in ensuring that the final version is polished and unique, and in no way feels artificial.

Watch out for: Getting complacent, and assuming AI can produce high-quality, engaging content with little or no effort and human direction. It’s an overused phrase, but ‘Garbage in, garbage out’ is the perfect description of what you will get without the application of strategic thought and expert prompt engineering.

Example AI tools for this use case*

  • AI-powered writing assistants such as, and Writesonic
  • AI content generators like ArticleForge and Kafkai

Data-Driven SEO Enhancement

Search engine optimization is an arena ruled by those who can masterfully blend relevance with reach. AI excels in analyzing vast amounts of SEO data, identifying trends, and integrating keywords that improve search engine visibility. This strategic application propels content in front of the right audience, ensuring that your message not only lands but resonates. However, behind every AI analyzing SEO data and making recommendations should be a Subject Matter Expert (SME) defining and monitoring their organization’s search engine strategy, carefully curating a list of target keywords and ensuring that the content produced to push them up the rankings remains relevant, useful, interesting and differentiated.

Watch out for: Letting AI take over and muddy your search strategy, focusing on volume over laser targeting of core keywords with the best possible content. Search engines reward content that delivers visits as well as targeting the right keywords – mediocre web pages that are crawled but not read will deliver short term gains at the most.

Example AI tools for this use case

AI can support many different SEO tasks, but key tools to test are:

  • SEO specific tools like MarketMuse, Frase and Clearscope
  • Keyword research tools with recently added AI capabilities such as Ahrefs and SEMrush
  • Some of the content tools listed above, will also build keyword-focused content

Personalization at Scale

The modern consumer does not merely buy products or services—they seek experiences tailored to their preferences. Their expectation is to receive customized experiences, and this has been proven to dramatically increase conversion to purchase. AI’s capacity to analyze behavior data and generate personalized content opens up new opportunities for hyper-targeting, even on a 1:1 basis, but this is definitely not a ‘plug and play’ exercise, and unless carefully implemented, the risks could easily outweigh the benefits. To effectively leverage AI for content personalization at scale, human oversight and intervention are critical at every stage.

To use AI to generate content personalization at scale, several elements would need to be combined, all requiring human input:

  1. A detailed strategy would need to be developed, identifying target audiences, their specific requirements and the areas of content that should be personalized. Even with all the potential that AI has, these areas should be limited and carefully monitored
  2. Live access would need to be provided to the AI for all relevant data and data points via integration. Ideally, these would be centralized, probably in a CDP (Customer Data Platform).
  3. Specific data points would need to be tagged so that they could be correctly identified and used by the AI
  4. Messaging guides would need to be developed and briefed
  5. Product information would need to be compiled and tagged based on relevant data points
  6. Thorough testing would need to be conducted, and this would help to create and refine the very detailed prompt required to brief the AI

Artificial Intelligence has the power to drive complex content personalization, learn from it, save time and improve results, there’s no doubt. However a considerable amount of human input and oversight would be essential to ensure accurate targeting and avoid errors.

Watch out for: incorrect or inappropriate personalized messaging due to under-briefing or lack of monitoring. The quality of the output for this approach will completely rely on the human input and understanding of the approach.

Example AI tools for this use case

  • AI-driven content personalization platforms including Personyze, Omniconvert and RichRelevance
  • Marketing Automation tools which are now including AI-driven personalization features such as Marketo, Hubspot and Oracle Eloqua

Consistency and Brand Voice

Preserving a uniform brand voice across a multitude of content pieces is essential. AI assists in maintaining this cohesive tone throughout all content varieties—blogs, social media posts, ads—upholding your brand’s identity and message. This unwavering uniformity builds brand recognition and trust, crucial currencies in the corporate world.

Once again, however, human involvement is crucial. The messaging first needs to be defined and variations identified depending on product and persona. AI will then require training with appropriate content – it’s not enough to point an LLM at your website and walk away. Tests should be run based around different types of content and messaging and feedback provided before a consistent brand voice can be assured for every piece produced.

Watch out for: using the wrong content to brief messaging and tone of voice. For instance, a website’s blog section may contain articles going back several years, during which that tone of voice is likely to have evolved. Spend the time to identify the content that best represents your tone of voice today and as mentioned above, test your chosen AI’s ability to reproduce it.

Example AI tools for this use case

  • AI writing assistants such as Persado, Phrasee and Jasper, which can be fed brand guidelines and language or understand brand voice
  • Style guide and brand management platforms with AI like Frontify and Lucidpress

Competitive and Relevant

In a landscape where content gets pushed out like clockwork, staying competitive means staying ahead of the curve. AI has the power to equip businesses with insights and tools that not only keep pace with content trends but also predict and act upon them, but it needs human input to ensure that it is monitoring the relevant trends and making useful predictions. This requires careful briefing from a planner / strategist, who will also review predictions and recommendations to ensure they are realistic, relevant and aligned with the organization’s goals.

Watch out for: ‘hallucinations’, irrelevant or impossible to achieve recommendations, or ‘trends’ based on unreliable sources. Your AI can be an excellent research partner, but the secret to a strong partnership is that it has more than one party, and the other party must be human!

Example AI tools for this use case

  • Content intelligence and analytics tools that harness the power of AI, such as BuzzSumo, Concured and Ceralytics
  • Social listening and consumer insights tools that are using AI, for examples Sprout Social and Brandwatch

A Convergence of Creativity and Analytics

Perhaps among the most salient benefits of AI is its harmonization of creativity with analytics. By harnessing AI for labor-intensive analytical tasks, content creators can unlock their creative potential, weaving narratives that captivate minds and hearts.

Once more, the key will be in the oversight of these tasks, and this will require strategists, data experts, and content experts who define strategic approaches, provide comprehensive briefings and feedback to help AI tools to learn, and also set up and link the tools to the relevant analytics platforms they will use to understand results and recommend optimizations and next steps. This is about more than just linking your AI to Google Analytics and saying ‘identify the best-performing content and recommend more of it’. You need to ensure that it understands exactly which data points are most relevant as well as the purpose your different content pieces in order to provide useful, relevant feedback. If done well, however, this dance between AI’s analytical prowess and human creativity could well be the defining choreography of successful content strategies moving forward.

Watch out for: your AI wasting time in identifying the wrong content trends by measuring the wrong data points.

Example AI tools for this use case

  • Tools that use AI to combine content optimization and analytics, such as Atomic Reach and Acrolynx
  • AI-generated art and design tools, for example Artbreeder and Adobe Sensei


 Time to Invest in AI for Content Writing?

The synergy between human creativity and AI precision represents the future of content writing, although the value of human copywriters remains irreplaceable; their unique insights and emotive touch are the beating heart of storytelling that AI cannot emulate. Some content will always be more suited to a copywriter’s touch, but there is no doubt that AI can change the game. However, solid foundations need to be laid to ensure that every piece, be it a two-paragraph email or a 20 page whitepaper, is of the same high standards that you would expect of a copywriter. These foundations require constant human input and oversight, including the definition of strategy and messaging, training on tone of voice, the crafting of detailed and sometimes complex prompts and, perhaps most importantly, review of all content produced to ensure that the highest quality standards are maintained.

AI is without doubt the most exciting business tool of the last 10 years, and it has almost unlimited potential for supporting B2B marketers in making content creation easier, more efficient and more productive. However, it is not a ‘magic bullet’ that can be deployed and left to run on its own. To get the most out of Artificial Intelligence, content creators need to adapt the way they work, but they must remain the owners of everything they produce, ensuring that quality, relevance and originality are always maintained.

*All examples of AI tools are correct as of publication date