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What will high-performing content look like in 2026? Experts share how to adapt, lead, and prove the value of human creativity in the AI era.
AI has created insecurity for content writers, where their jobs could be in jeopardy from machine-generated content at scale.
The reality is that many content writers may be displaced, but the ones that can survive and be in demand are the ones who embrace the current changes in search and adapt.
Writers can be irreplaceable by learning how to create valuable content that is optimized for large language model (LLM) inclusion. They can also stand out by creating the kind of content that takes advantage of LLM and machine content limitations.
To offer real, actionable advice, we reached out to a selection of the leading voices in producing content to ask how they’re doing it and what “high performing” content will mean by 2026.
Our contributors agree: Staying relevant means honing the skills AI can’t replace and learning how to make it work for you, not against you.
Chelsea Alves opens with a reminder that experimentation defines this era: “The AI era is all about testing.” She advises writers to “pair their creative intuition with thoughtful analysis” and focus on what AI can’t replicate: “genuine insight, storytelling, and subject-matter expertise.”
“Writers should sharpen their ability to synthesize data and human context, not just summarize information.”
Alves also suggests a modern workflow where AI becomes a partner: “Writers will want to view AI as a collaborator, rather than as a competitor,” especially for “research acceleration (with human fact-checking), ideation, and outline while retaining full authorship over tone and empathy.”
But it only works when the writer knows how to communicate with AI effectively. “Feeding AI detailed, structured, and contextual prompts is imperative for it to deliver accurate and relevant results.”
Her closing warning points to a changing discovery environment: “Multi-format fluency is crucial,” because audiences now discover and engage with content through summaries, voice search, or in-platform experiences.
Andy Betts shares what he learned: “Position yourself as the strategic thinker who uses AI to research and aid your ideas, not replace them.”
“There is a real opportunity for marketers who lean into their core creative instincts and foundational optimization skills to amplify messaging, positioning, and branding. That is the gap AI cannot fill.”
“I shifted from tactical content to strategic content that builds authenticity for AI citations and references,” Betts adds, and then points to the signal coming from the biggest players in the market: “OpenAI, Meta, Google, PayPal are all hiring content strategists to shape CEO narratives and storytelling. If you are willing to own the strategy piece, that is where you genuinely stand out.”
Heather Lloyd-Martin takes the long view: “Writers who thrive in the AI era will double down on what machines can’t replicate: nuance, strategy, and authentic voice.” Even as AI accelerates research, she reminds us that fundamentals haven’t changed.
“Great writing still sells, teaches, and builds trust.”
She shares techniques, including “studying conversion writing to weave micro-conversions into every piece. Hone your storytelling to capture attention in an increasingly automated feed. Get comfortable with ‘messy prompting’ AI, and discover how to use it as a research assistant/creative wingman. And most importantly, infuse every line with brand personality and point of view.”
For her, differentiation in 2026 won’t come from writing speed or awesome prompts, but from “insight, strategy, amazing storytelling, and knowing how to use the power of AI to make your content even better.”
“Writers should not adapt; they should continue to produce human-level content written for humans,” argues Adam Riemer.
“AI can mimic, but it cannot replace. Humans being able to verify and fact-check, create content that they see being used is something only we can do.”
He adds, “Humans know what to look for and how to write for it. The biggest difference in skills is when we get stuck on wording, have character maximums or minimums, or need alternative word suggestions. This is where AI can shine.
→ Read More: This Is Why AI Won’t Take Your Job (Yet)
When asked how their writing has shifted in the age of LLMs, each expert landed on the same truth: the mechanics of good writing haven’t disappeared, but the structure carrying that writing has become far more intentional.
With the days of writing content for traditional SEO long gone, Alves advises writers to structure content with machine readability in mind. This means ensuring “clarity, consistency, and rich context so that LLMs can accurately summarize your content.”
“Topical relevance is more important than ever, as well as schema-informed structure.”
Instead of letting meaning build linearly, she now aims for “writing sentences that stand alone with context.”
For her, fundamentals are still as important. “Today’s writers must incorporate internal links, definitional clarity, and clear takeaways to make content easier for humans and machines to process.”
But she notes that writing for machines doesn’t mean flattening voice or storytelling. “It’s more about creating a layered content experience: a clear, structured skeleton for the machines and a compelling, emotive experience for the humans,” explains Alves.
For Betts, his core writing has not changed much, but his approach to structure has. “I am spending more time on prompts and briefs that guide AI rather than just writing final copy,” he explains.
“The content optimization tricks I have used for 25 years still work.”
But he’s learned to write deliberately for how AI understands context, nuance, and brand intent.
His take on what matters: “I always own the final output. That is non-negotiable.” And the real win? “It is writing smarter – less content overall, but each piece carries more weight. Your influence-per-word ratio goes up when you are directing AI instead of racing it.”
“I wrote about this on LinkedIn,” Lloyd-Martin shares. “Most ‘LLM writing rules’ echo what I’ve been discussing for over 20 years. Write clear, eye-catching subheads, and link to related pages. Understand search intent, and write engaging, standout content that answers questions and showcases your expertise.”
Where she experiments is structure. “I’ll add quick takeaways at the top to help both readers and machines grasp the value fast, or FAQs when they make sense.” AI now plays a role in deep research, too, “identifying where competitors earn LLM citations and where we don’t.”
But even with those tools, her north star hasn’t budged.
“AI may have enhanced my process, but it hasn’t changed how I write.”
“LLM inclusion is based on tons of potential signals,” Riemer says, keeping the conversation grounded in audience experience.
“Writing for a human audience at the audience’s needs and skill levels is what everyone should do. If you write higher or lower, overcomplicate or simplify, or add more because of a concept being touted as ‘fan out queries,’ then you’re creating a horrible user experience.”
He adds that “AI isn’t your customer … do not change your writing because of it; write for your audience and make sure AI can find, understand, and reference it.”
→ Read More: How To Get Your Content (& Brand) Recommended By AI & LLMs
The conversation around content performance has shifted from volume to value. When asked what holds up no matter how search or AI shifts, our experts reveal a comforting throughline: content built on depth, trust, and expertise isn’t going anywhere.
Alves opens the conversation by pointing out that AI hasn’t completely derailed the content frameworks that used to work. “Many content best practices remain the same, such as authority-driven frameworks like data storytelling, original research, and expert commentary.”
These, she notes, are more likely to be shared, trusted, and noticed by humans and search engines alike. “Case studies, proprietary data reports, and first-hand experiments continue to outperform derivative content, both in organic search and boosting brand credibility.”
She also sees the staying power in educational content built on empathy. Examples are tutorials, explainer videos, and playbooks that anticipate user needs and provide helpful, actionable next steps.
Alves also reminds us that even as AI delivers answers in an instant, audiences will still turn to trusted brands for depth and application.
“Consumers still favor and prefer human expertise over machines.”
“I am betting big on frameworks only experienced writers understand,” Betts says, pointing to brand storytelling rooted in company knowledge, executive messaging that shapes how people perceive your organization, and content strategy demanding real human judgment about stakeholder needs.
He also stresses that creative writing, the deeply human element, does not go away.
“Positioning writing as a strategic function, not a production task, drives business outcomes.”
He adds, “The briefs, editorial standards, and voice guidelines that train AI? Those matter now. That is where you multiply value.” And when it comes to measurement, he found that “measuring content by genuine business impact, not just visibility metrics, is where success truly lives.”
Lloyd-Martin keeps her focus on the assets many brands overlook. “Refreshing older blogs, guides, and sales pages often delivers faster wins than starting from scratch, and you can repurpose the content for different platforms.” She’s seen clients gain quick lifts from updated headlines, improved internal links, and repromotion.
“Great content doesn’t expire; it just needs a little love every once in a while.”
And no matter how AI or search evolves, she always recommends maintaining an email list. For her, “owning your audience and showing up in their inbox will always be a smart, sustainable marketing move.”
Riemer takes the most streamlined approach: “Same as always, proper page structure and follow best practices.”
When the conversation turns to proving return on investment (ROI), our experts tie value to measurable outcomes rather than volume.
Alves leads with evidence: “As with any marketing endeavor, it’s crucial to provide tangible evidence of success.” For her, the indicators have shifted. “Traffic and clicks used to be a top indicator of success; however, engagement quality (scroll depth, time spent on page), assisted conversions, lead quality, and influence on customer journeys are now key indicators of content’s impact.”
She emphasizes attribution and visibility across the funnel. “It’s paramount to have visibility into how content is fueling conversions.”
She also looks at “trust metrics,” lending credence to brand credibility, share of voice, appearance in AI summaries, and mentions in third-party articles/media.
Betts centers his measurement on strategic influence. “I have stopped counting words and started tracking what matters,” he explains. He focuses on the broader role content plays. “I focus on how my editorial direction shapes company communications, including AI-generated content.”
He points to what executive content drives: “recruitment quality, investor conversations, brand positioning that sticks.” He then highlights a shift in how stakeholders see content.
“It is no longer ‘content is overhead’. It is ‘content strategy multiplies organizational output while staying authentic.’ That wins investment.”
“Rankings and citations still matter, but I focus on what those metrics mean,” Lloyd-Martin shares, watching for these behavioral indicators: “Is the content attracting qualified visitors? Are they taking the next step, or bouncing? Traffic without reader resonance doesn’t drive revenue.”
She also pays close attention to how content shows up in conversations. “When sales teams mention prospects referencing our articles, that’s impact. For clients with limited rankings, especially local or service-based businesses, we analyze which pages are already positioning (often blogs) and expand visibility for queries that matter most.”
She notes that the goal is creating content that converts and builds authority. “AI can help you write faster, but it takes an experienced writer to understand if the output is any good and how to improve it.”
Adam Riemer demonstrates impact through contrast and accountability. He explains, “Some clients want to see the before and after, so we share examples of sites that got tanked because of the AI content. In other cases, accuracy becomes the deciding factor. “We send the non-factual content to legal for review, and that puts an end to it.”
For his clients who want to use AI for content, he sets up policies in place for “fact-checking, conversion testing, and other controls that require human assistance.”
“This helps keep humans employed until companies realize AI should not be writing and generating content without human intervention.”
Our experts share what they believe will define content success next year. Hint: The loudest or the fastest won’t win. It’s value, depth, and authenticity that will set the bar.
“Nothing new, it’s the same as it always has been,” says Riemer, describing the current landscape. He sees an opportunity created by declining content quality. “It’s just easier now to compete since a lot of companies are creating spammy AI and LLM-generated content.”
In his view, the core dynamic hasn’t changed. “Same as it was after article spinners lost their time in the spotlight for the same thing. You could take articles from 10 sites or have 10 writers write them, add the macros to insert and spin them, then spit out new content. Same quality as we’re seeing here with AI.”
Alves notes the saturation AI has created, but audiences and search engines will reward content that proves real-world insight can only be produced by humans. “This will look like data from proprietary sources, first-hand interviews, unique frameworks, or any content that demonstrates lived experience.”
But ultimately, she believes visibility will be tied to originality.
“Differentiation will be key and will hinge on human touch … Your content should sound unmistakably human in a sea of sameness.”
Lloyd-Martin believes “high-performing content will still be measured by the same timeless standard: business impact.” For her, the right questions remain constant: Does it attract the right audience, support the buyer journey, and drive conversions? Is that AI citation making you money, or is it just a vanity metric?
“Clarity, credibility, and conversion power will always define content success.”
For Betts, “high-performing content will be strategically directed and authentically executed, AI- AI-assisted but human-guided.”
He foresees big companies course-correcting. “Expect those who cut experienced strategists and relied on AI writing to come back hiring content leaders.” For him, the differentiator is not speed but “strategic wisdom: knowing what to say and ensuring it reflects genuine human creativity and judgment.”
He also predicts: “The scarcest resource will not be content; it will be experienced judgment. Writers who master directing AI while maintaining creative integrity will command premium value.”
AI may have changed how content gets discovered, but not what makes it valuable. The experts agree: The edge now lies in structure, strategy, substance, and human judgment.
LLMs surface what they can understand. Readers choose what they can trust. High-performing content in this era succeeds when it satisfies both.
A huge thank you to our contributors for sharing their time, experience, and insights.
Editor’s note: All interviews have been lightly edited for clarity, brevity, and adherence to our Editorial Guidelines. The views expressed by the interviewees in this column are theirs alone and do not necessarily represent the view of Search Engine Journal.
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