In 2024, the question was: Should we use AI?
In 2025, it became: How do we implement it?
In 2026, the real question is: Where does it actually create value?

AI has moved from experimental to operational faster than most of us anticipated. New tools emerge daily, agents are becoming more capable, and traditional workflows are starting to feel unnecessarily slow and simply inadequate to match the market.

This means staying up to date with AI advancements is key, hence why we’ve updated this article to reflect where AI is making a measurable impact in B2B marketing today

1. Brainstorm, Record, Publish – Without the Bottlenecks

Content no longer has to take a full week from ideation to publishing.

Today, AI can support the full workflow, while you stay focused on the thinking.

Brainstorm & Script: LLMs can turn raw ideas, voice notes, or bullet points into structured drafts, scripts, or outlines. The strategic input is still yours. The formatting and refinement don’t have to be.

Record: Video avatar tools like HeyGen allow teams to produce consistent video content without actually having to stop what they’re doing to record. This is especially useful for product explainers, updates, or thought leadership snippets.

Publish: AI agents can coordinate the entire flow, from scripting to recording, down to publishing.

The result? Less friction between idea and distribution. Faster and more consistent content.

2. The Content Multiplier Effect

We keep parroting this just because it’s true: content shouldn’t live in a single format. We believe firmly in the Circular Content Economy.

Your team invested time in researching, drafting, refining, and publishing. Your audience consumes information across different platforms and in different formats. Your content may be relevant at different times, in different formats, and on different platforms. Need us to keep naming reasons?

A blog can become a LinkedIn post, a webinar can turn into short social clips, and a case study can evolve into a podcast episode.

Repurposing isn’t about duplication, it’s about distribution and amplification.

In our article, “Ways to Recycle Your 3 Favorite Types of Content in 2026”, we outline six practical ways to extend the life of your content, along with the AI tools that make the process faster and far more scalable.

3. GEO: Preparing for the “Answer Economy”

Search behavior has shifted, newsflash!

Take a simple example. You’re at home, want to bake a chocolate cake in the air fryer (because it’s faster), and you only have one egg.

Do you open Google, search “air fryer chocolate cake”, open another tab for “1 egg chocolate cake recipe”, and merge the two recipes yourself? Or do you ask your favorite LLM: “Give me an air fryer chocolate cake recipe that only uses one egg.”

We all know the answer.

That same behavioral shift applies to B2B buyers. Instead of piecing information together from multiple search results (your website, review pages, demo videos…), they’re asking AI tools direct, specific questions about vendors, platforms, and recommendations.

That means traditional SEO is only part of the picture.

Enter Generative Engine Optimization (GEO), which focuses on structuring your content so AI systems can easily extract, interpret, and cite it.

Practical applications:

  • Use clear subheadings that answer specific pain points.
  • Include concise, well-structured answer sections.
  • Prioritize clarity over keyword density.

If your buyers are asking AI for advice, you want to be part of the answer. Check out our article "7 Tips to Optimize Content for LLMs and Generative Search" and get more tips on how to adapt to this new SEO on steroids.

4. AI Buying Assistants

The generic “How can I help you?” pop-up is losing effectiveness.

In 2026, AI buying assistants are moving beyond scripted flows and FAQ responses. When trained properly, they function as a real extension of your sales and marketing team.

These systems can be trained on:

  • Your service/product documentation.
  • Case studies.
  • Sales transcripts.

Tools like Intercom Fin, Sierra AI or Forethought can respond to detailed, service/product-specific questions and qualify leads before routing them to a sales rep. This reduces friction and shortens the path from research to conversation.

The key difference here is that these systems are informed, not scripted.

5. Signal-Based Prospecting and Social Listening

Cold outreach is evolving and is now much easier to personalize. It’s also more about timing.

Context matters, it always has, it is just now simpler to get. A company that just secured funding has different priorities than one undergoing budget cuts. A new Marketing Director may signal strategic shifts in procedures and tools. Keeping context in mind not only means true personalization, but it also means you have better chances of actually closing a deal.

AI now makes it possible to monitor buying signals at scale:

  • Leadership changes.
  • Funding rounds.
  • Product launches.
  • Industry recognition.

Tools like Amplemarket and Apollo can surface relevant signals and draft personalized outreach based on real context and goals. Instead of “Just checking in”, your outreach becomes: “I saw you recently expanded into X. Here’s how our service can help you reach this new audience.”

Relevance and true personalization improve response rates, and AI makes it easier, faster, and scalable.

 

AI is not a marketing strategy. It’s a tool.

Used well, it removes friction, extends the reach of good ideas, and helps teams operate at a level that previously required significantly more headcount (and budget!).

Used poorly, it creates noise and pollutes your toolkit – it is of no use to include tool X just because everyone talks about it, it needs to make sense for your team.

The difference, as always in marketing, comes down to intent and execution. If you need help with the transition, reach out!