Introduction
Just like every other industry in the world today, B2B marketing has been changing at breakneck speed due to the rise of generative AI.
71% of B2B marketers now use this technology on a weekly basis and 20% on a daily basis, for things like expediting content creation, brainstorming more innovative campaign ideas and automating repetitive tasks.
It is widely acknowledged within the industry that a team's ability to effectively leverage this transformative technology can be a significant source of competitive advantage.
At xGrowth, we feel the same.
This article explores our view on how AI is transforming content strategy and Account-Based Marketing (ABM), where it creates leverage, where it adds risk, and how forward-thinking teams can evolve their strategy to lead in this new era.
The Current State of AI in B2B Marketing
More and more marketers are using tools like ChatGPT, Claude, and Jasper to complete content creation and research tasks faster. This is the most obvious use case of AI.
We are also seeing traditional software players like Hubspot, Salesforce, et cetra, introduce a slew of native AI features to help marketers be more efficient with customer segmentation, predictive campaign analytics and the like. But the biggest shift we have seen from 2024 to 2025 and now going into 2026, is the rise of specialised AI agents.
An AI agent is a piece of software that's highly trained to perform a very specific task on its own with minimal human intervention.
Take Clay and its agent, Claygent, for example. B2B marketers can use Clayagent and have it autonomously browse websites, extract data about prospects and create a target account list for an ABM campaign, replicating what a sales researcher does, but faster and cheaper and all with a simple prompt.
Claygent is only one part of a much larger transformation happening in B2B marketing, particularly within Account-Based Marketing (ABM).
Beyond prospect research, there are now agents that focus on content creation and personalisation, enabling teams to generate campaign assets and tailor messaging for different account tiers, industries, or stages of the buyer journey.
Others specialise in predictive targeting and account selection, continuously analysing intent and engagement signals to surface high-value accounts in real time.
Some are even emerging in marketing lifecycle orchestration, helping to coordinate campaigns, adjust spend, and re-engage leads across multiple channels.
While new agents continue to be created, two in particular, the content ( personalisation) agents and predictive targeting (account selection) agents, are the ones we’ll explore in more detail throughout this article.
The Rise of AI-Powered Search and Its Impact on Content Strategy
Let’s start with the content creation. Unless you have been living under a rock, you know that search has changed.
The way businesses find you online has changed, and it seems to be in constant flux right now.
The most prominent example is Hubspot, which lost up to 80% of its blog and website traffic because of AI overviews from Google.
Ahrefs has also conducted a study showing that the AI overview feature reduces clicks by 34.5%.
The above two data points are uncomfortable, but they also present an opportunity. AI systems prioritise trustworthy, structured, and well-researched sources. The goal is no longer just to rank, but to be the source AI trusts enough to reference. Marketers who focus on clarity, structure, and originality will stay visible even in a world where fewer people click through.
The depth and breadth of your content now matters more, so that you have a higher chance of getting cited in an AI-generated answer.
All of this to say, the pace at which you churn out helpful content holds the key to agent engine optimisation.
AI as a Content Creation and Personalisation Tool
So, how can you use AI to augment your ABM efforts?
Research and Content Creation
Initial research has shown that using AI as a companion to do your research, understanding what specific questions people are asking, and then using it to generate guided content, does not impact visibility and citations. This is where you can reach scale and great depth on a specific topic. A single copywriter can cover a keyword, get all the questions target account prospects are asking related to it and generate very specific, pointed pieces.
Customisation at Scale
Another important use case is tailoring existing content for different buyer personas. In most ABM programs, a core piece, such as a white paper or case study, is written by a strategist for a single primary audience. Adapting that same piece for other personas has always been a slow and manual task.
AI makes this much faster. With a few prompts, it can take a base asset and rewrite it to match a new audience. For example, a technical deep dive written for an IT director can be reframed for a CFO by focusing on ROI and business outcomes instead of product architecture. The core message stays the same, but the emphasis, tone, and structure shift to suit each role.
For ABM teams, this approach ensures consistency across campaigns while still speaking directly to every stakeholder. It means one strong piece of thought leadership can quickly become several versions, each aligned with a different buyer persona.
Beyond Text-Based Content
We touched on this a little bit in the customisation section, but content is not just text; it’s visual, it’s landing pages, videos, webinars, slides, and infographics. Generative AI can be used for all in the context of Account-Based Marketing.
For instance, Lumen Technologies, an American-based enterprise networking company, uses Adobe GenStudio to scale and personalise its B2B marketing campaigns. They cut their campaign timelines from 25 days to 9 days, while producing on-brand visuals, ads, and emails tailored to different industries and buyer personas. The company used Adobe Firefly models within GenStudio to generate creative assets quickly without compromising brand consistency. Here is their detailed case study. This is just one of many case studies where generative AI has supercharged content strategy.
Predictive Targeting and AI for Account Selection
If content creation is how AI helps you speak to the right audience, predictive targeting is how it helps you find that audience in the first place. This is a more advanced use case for AI, and it's likely something that would need to be built into your marketing technology stack.
In Account-Based Marketing, one of the most complex parts is knowing which companies are actually ready to buy.
Platforms such as 6sense, Demandbase, and HubSpot are using AI to do this really well.
6sense uses machine learning to analyse billions of intent data points and predict which accounts are most likely to buy in the next few weeks.
Demandbase uses a similar model that sorts accounts into readiness stages based on real engagement signals.
HubSpot’s predictive account scoring takes a different approach. Instead of manually assigning points to activities, it analyses past conversions and automatically identifies which attributes best predict deal closure. The system keeps learning and adjusting, so over time it gets more accurate
Here are some more practical ways ABM teams are using these tools:
Weekly target refresh: A SaaS company using 6sense updates its Tier 1 and Tier 2 accounts every week. As intent signals change, the list updates automatically so the team always works with the freshest data.
Smart prioritisation: When Demandbase detects that a group of accounts is researching a topic such as customer data platforms, the marketing team immediately launches a short LinkedIn campaign and email sequence on that theme.
Evolving Ideal Customer Profiles: A HubSpot user reviews their top 100 closed deals and lets the predictive model adjust the ICP. The AI highlights industries with high engagement and removes those that no longer fit.
These examples show the difference between automation and real AI. Automation follows rules you set. AI finds new patterns you might have missed. It helps your ABM program stay flexible, accurate, and relevant as buyer behaviour changes.
Potential Pitfalls: AI Limitations and Over-Automation Risks
We have talked a lot about how you can harness the power of AI to augment your ABM efforts, but all of this comes with some risks.
Here are the things we know are its shortcomings:
- It hallucinates
- It hallucinates confidently
- If not given the right context, it can spit out very generic information
There is just one best practice that, if ignored, can do more harm than good.
Keep a human in the Loop, that’s it!
This is an important one. There are companies out there painting a world where AI agents will do everything. AI works best as a companion, not as an isolated entity. The human orchestrating the AI in their own unique way and bringing it into your AI strategy is what will give your company that competitive advantage.
How to Future-Proof ABM and Content Strategy in the Age of AI
If there is one takeaway from everything we have discussed so far, it is that AI is no longer a passing experiment. It has reshaped how B2B marketers research, create, distribute, and measure content, and it has become deeply embedded in Account-Based Marketing. The challenge now is to stay adaptable as the technology continues to evolve.
The good news is that future-proofing your strategy does not mean starting from scratch. It means strengthening what already works and layering AI intelligently on top of it.
Build Authority That AI Trusts
As we discussed earlier in The Rise of AI-Powered Search, visibility today depends more on credibility than on keyword optimisation. When AI systems summarise information, they prioritise trustworthy, structured, and well-researched content. The goal is not just to be seen but to be cited.
Invest in original research, case studies, and content that adds depth to your category.
Just like we saw in AI as a Content Creation and Personalisation Tool, authority comes from understanding your audience and creating content that actually helps them.
Use AI to Scale Smartly, Not Mindlessly
AI should help you scale what works, not replace strategy.
The examples we looked at in Predictive Targeting and AI for Account Selection showed how innovative teams are using AI to surface the right accounts and then act faster.
The same thinking applies here. Use AI to identify patterns, speed up production, and personalise communication, but keep humans in charge of context, tone, and message.
Align Marketing and Sales Around AI Insights
ABM only works when both teams move together. AI can be the bridge that keeps them aligned. Earlier, we saw how predictive systems like 6sense and HubSpot surface real-time buying intent.
The next step is to ensure both the marketing and sales teams interpret those insights consistently and adjust their actions accordingly. This shared understanding is what turns data into impact.
Lead With Your Point of View
AI can help you create, but it cannot think for you.
As we discussed in Potential Pitfalls, over-automation risks flattening your brand’s voice. Your point of view is what gives your content authenticity and credibility.
Use AI for research and structure, but let people shape the ideas, opinions, and stories that your audience will remember.
Conclusion
AI in B2B marketing presents a dual reality. It offers an unprecedented opportunity, but also real risks. On one hand, the rise of generative models, predictive targeting and AI-agents means you can scale personalisation, streamline content creation and surface high-intent accounts faster than ever before. On the other hand, without a strategy, oversight and a strong brand voice, you risk producing generic content, eroding credibility or missing the very audience you’re trying to reach.
The companies that will win are the ones that blend innovative AI tools with a strategic Account-Based Marketing framework. Those who use AI to amplify what they already do well, align marketing and sales, refine the Ideal Customer Profile with data, tailor messaging per account and persona, and keep humans in charge of strategy and storytelling will gain a lasting competitive edge.
If you’re reading this now, we invite you to take a moment to audit your current use of AI in marketing. Look at where your tools are doing work, where human judgment is still required and where data could inform better decisions.
Then explore how an AI-enhanced ABM framework can shift you from being reactive to being ahead of your market. The future belongs to those who know how to use AI, not just because it’s new, but because it’s aligned with how genuine buyers now behave.
If you want to have a chat with us to see how we can enhance your ABM with AI, reach out today for a free discovery session.
