As part of our whitepaper ‘The vision of 27 marketers and content creators for 2026’, we asked AI content marketing strategist Ina Toncheva for her vision for 2026 and two practical tips she would give to readers. You can read her response below.
Who is Ina Toncheva?
Ina Toncheva is an AI content marketing strategist, trainer, and speaker. She helps marketers and marketing teams build AI-powered content systems that produce on-brand, high-quality content at scale – the kind that consistently drives traffic, leads, and conversions. With 18 years of experience in marketing and strategy, including work with Fortune 500 brands, she brings deep strategic insight and hands-on expertise to every project.
For twenty years, B2B marketing relied on a familiar engine: publish content and distribute it through blogs, webinars, and whitepapers; capture emails, nurture, and hand to sales. The formula worked because the channels still had oxygen. Today, that oxygen is gone. What once guaranteed reach now disappears into the noise.
In the pre-AI era, strong content naturally earned distribution. Today that’s much harder. A blog post no longer guarantees visibility. A polished report no longer guarantees leads. A clever ad no longer guarantees reach.
Content supply is effectively infinite, but attention is not. Distribution has become the rarest resource in marketing and it has to be designed from the very beginning. Only a plan that accounts for channel behavior, audience habits, and content created natively for each platform offers a real advantage.
Static PDFs (ebooks, whitepapers) worked for years because users believed they were hard to create, and therefore valuable. At the time, that wasn’t wrong. Today, people assume they can be produced instantly with AI, and their perceived value has dropped.
In 2026, the lead magnets that convert are interactive, code-powered tools – custom GPTs, calculators, copywriting tools, diagnostics. Brands like Canva and Veed use custom GPTs to drive millions of interactions inside ChatGPT, meeting users where they already are. Think of custom GPTs as a new distribution channel.
And the good news is that they’re not just for big brands. My customers and followers use my custom GPTs to assess their blog’s AI search readiness or the strength of their landing pages – proof that even simple, narrowly scoped tools can deliver real value. They also keep my personal brand top-of-mind: every time someone runs a diagnostic, they’re engaging with my frameworks and way of thinking. The advantage comes from solving a specific problem in a way that feels fast, useful, and personal.
AI-generated summaries are quickly becoming one of the most important distribution channels of 2026. When someone asks ChatGPT or Perplexity a question, they don’t browse a list of links, but read a single synthesized answer. Inside that answer, the model decides which brands, claims, and ideas to surface. In practice, this creates a new kind of “front page,” driven not by keywords but by how clearly your ideas can be interpreted and cited.
Optimizing for AI search requires a slightly different structure than traditional SEO. Models choose content they can easily understand: clear answers upfront, headings written the way people actually ask questions, schema markup to highlight structure, and supporting elements like stats, examples, and credibility signals that make your content quotable.
And to be clear: optimization for AI search (AEO) doesn’t replace SEO; it builds on it. The core SEO principles still matter. But instead of optimizing only for ranking, you adapt your content so it’s structured for extraction, ready to be lifted, referenced, and trusted by AI systems.
The best custom GPT ideas come from work you already repeat. If you give the same advice to clients, edit similar content, or answer the same audience questions, that’s your starting point.
Ask yourself two questions: – What high-value interaction do I repeat? – What’s the best GPT format for it: an evaluation tool, a knowledge assistant, or a quiz?
Format-specific GPTs can generate email subject lines or social captions. Diagnostic GPTs explain why a landing page or blog post isn’t working. Quiz-style GPTs act as interactive lead magnets that keep users engaged. The goal isn’t to necessarily invent something new, but to productize the value you already deliver every day.
When entering a new channel, most teams start by guessing what might work. A faster, more reliable approach is to create a blueprint based on the content that already performs well there.
Here’s a simple method:
1. Analyse three top-performing examples on that channel using your LLM of choice – whether video scripts, LinkedIn posts, or short-form videos – and ask why they succeed.
2. Ask the model to extract a blueprint: structure, flow, pacing, hook style, length, language patterns, and what makes each piece effective.
3. Use that blueprint as a template, combining it with your own ideas and expertise to produce channel-native content quickly and confidently.
This turns distribution into a system you can scale, not something you hope for after publishing.
Would you like to discover the other 26 marketers’ and content creators’ visions for 2026? Download the whitepaper here.
