Looking back, 2025 wasn’t about one breakthrough. It was about a handful of shifts that changed how AI and growth actually work:
Search stopped rewarding effort and started rewarding clarity. Rankings still exist, but AI-driven answers favor brands that are easy to understand, trust, and reference.
Content velocity exploded. AI made it easy to publish more, faster. What it exposed was judgment. The winning teams were more selective. Human judgment is still on top.
Creative moved from handcrafted to orchestrated. Automation didn’t kill creativity. It punished weak briefs, unclear signals, and sloppy feedback loops. When iteration is cheap, structure matters.
AI skills decentralized, whether leadership planned for it or not. The biggest gains came from teams rebuilding workflows in real time, not waiting on roadmaps or centers of excellence.
And underneath it all, trust became the constraint. Buyers feel it. Platforms measure it. Machines amplify it or expose its absence.
With 2026 on the horizon, this is a good moment to step back, take stock of what actually worked, and decide what you’re carrying forward instead of reacting to what’s loud.
We’ll be back in the new year with a fresh signal, fewer distractions, and a clearer point of view.
Until then, enjoy the break and this week's articles.
Patrick Patterson
CEO at Level Agency
What's interesting this week
AI Search Is Forcing SEO Teams to Rebuild Themselves Backlinko’s guide gets very practical about what “AI-ready SEO” actually means. It breaks down the new roles, skills, and workflows teams need as search shifts toward AI answers and content velocity increases. Success depends on tight alignment between content strategy, technical SEO, analytics, and AI-assisted production. If those functions operate independently, performance breaks down fast. Read more
SEO Experts Are Aligning on What Actually Matters for 2026 This roundup of 20 SEO experts shows surprising consensus. Keyword-first tactics are giving way to topic depth, intent clarity, and content that is structured for both humans and machines. Several contributors emphasize brand signals, internal linking, and content consolidation over net-new volume. The takeaway: fewer pages, stronger authority, cleaner structure. Read more
AI Skills Are Being Built Inside Real Work, Not Training Programs MarTech outlines how individuals and teams are developing practical AI skills without waiting for executive mandates. The article focuses on small, repeatable behaviors: using AI inside existing tools, documenting wins, sharing prompts, and learning in public. This is how AI capability actually spreads. Read more
Google Is Trying to Make AI Agents Less Wasteful This VentureBeat piece covers Google’s new framework for helping AI agents manage compute and tool usage. Instead of calling every model and API by default, agents are guided to reason about cost, relevance, and sequencing. While technical on the surface, the implication is practical: future agents should be cheaper, more predictable, and easier to trust in production workflows. Read more
KOLs Outperform Influencers When Credibility Matters Hootsuite’s breakdown clarifies the difference between influencers and key opinion leaders. KOLs bring subject-matter authority, smaller but more engaged audiences, and higher trust, especially in B2B and regulated industries. The article also outlines how to identify, vet, and work with KOLs without turning them into paid mouthpieces. This is influence built on expertise, not reach. Read more
UGC Continues to Outperform Brand-Made Content Heading into 2026 Influencer Marketing Hub pulls together performance data showing why user-generated content still beats polished brand creative across social and paid channels. The practical angle is how brands are combining AI tools with UGC to speed up editing, testing, and distribution without losing authenticity. Read more
Deep dive: AI
What actually drives brand visibility inside AI answers
Ahrefs analyzed 75,000 brands to understand which factors correlate with visibility in ChatGPT, Google AI Mode, and AI Overviews. What they found isn’t mystical, but it is eye-opening.
Brands that appear more often in AI answers tend to have strong traditional SEO foundations, especially branded search demand, authoritative backlinks, and consistent topical coverage. AI systems still rely heavily on the same signals search engines use, but they weight them differently. Clear brand entities, recognizable expertise, and consolidated content matter more than sheer page count.
One important nuance: AI visibility is uneven across platforms. A brand that performs well in Google’s AI Overviews may not show up nearly as often in ChatGPT. Each system builds its view of the web differently.
For growth leaders, this means two things. First, AI visibility is measurable today, not theoretical. Second, improving it looks a lot like doing the unglamorous work well: tightening topical authority, strengthening brand demand, and reducing content sprawl. AI isn’t inventing a new internet. It’s just being more selective about which parts of it to trust.
Digiday’s visual breakdown of media expectations for 2026 focuses less on bold predictions and more on structural shifts already underway. The dominant theme is efficiency under pressure.
Media buying is moving toward fewer intermediaries, more automation, and faster feedback loops. That puts pressure on inputs. Creative, data quality, and measurement have to be cleaner because there’s less room to hide inefficiency. When algorithms optimize in real time, weak signals get exposed quickly.
The piece also highlights how media formats are converging with commerce. Shoppable units, retail media, and performance-oriented placements continue to blur the line between branding and conversion. At the same time, marketers are being asked to justify spend with clearer outcomes, not just reach.
The practical takeaway is that media planning is becoming less about channel mix and more about system design. Teams that treat media as a connected operating model, where creative, data, and distribution reinforce each other, will adapt faster. Teams that rely on static plans and manual optimization will struggle to keep up.
2026 doesn’t reward louder media strategies. It rewards cleaner ones.
Gamma is an AI-powered design tool for creating decks, documents, and presentations without starting from a blank slide. You give it a structured prompt or outline, and it generates a clean, on-brand draft that’s easy to edit and refine.
Where Gamma stands out is speed without sloppiness. It handles layout, hierarchy, and visual structure well enough that teams can focus on thinking instead of formatting. We’ve used it for whitepapers and slide decks as a fast first draft, then layered in edits to polish the final output.
For growth leaders, Gamma is useful because it shortens the distance between idea and artifact. Strategy decks, internal docs, client presentations. All move faster when the design work doesn’t slow you down. It doesn’t replace taste, but it removes friction, which is exactly where AI should sit.
Ready to turn AI visibility into pipeline?
AI platforms are shaping how buyers discover and vet brands. But most marketers don’t know if their brand even shows up.
Level’s AI Visibility Scorecard shows how often your brand appears in ChatGPT, Gemini, and Perplexity, how you’re described, and how that compares to your competitors.
You'll get:
A visibility score and share of voice vs top competitors
Sentiment analysis of how your brand is framed in AI answers
A tactical roadmap to improve your citations, content structure, and authority signals
Used by leading brands and fine-tuned across real buyer prompts, this scorecard is your opportunity to drive real visibility in the zero-click search environment.
