AI Content Creation: Best Practices That Keep You Ranking

Both statements are true at once. AI content dominates the web, and AI content gets publishers deindexed. The difference between those two outcomes comes down to a set of practices that are now measurable, replicable, and non-negotiable for any team serious about scale. This guide unpacks them, with the data behind each one.

Google's 2025-2026 Stance on AI Content Has Hardened, Not Softened

Google's public position has been consistent since Danny Sullivan and Chris Nelson's February 2023 Search Central post, which still sets the baseline. Appropriate use of AI or automation is not against Google's guidelines. Using automation to generate content whose primary purpose is manipulating search rankings is. What has changed over three years is enforcement.

Three milestones matter most. In March 2024, Google rolled out a core update alongside three new spam policies, including a rebranded scaled content abuse rule with a deliberately broad definition. The policy covers many pages generated to manipulate rankings and not help users, no matter how they were created. Google said the combined effort would reduce low-quality, unoriginal content in search by 40 percent. The actual reduction came in at roughly 45 percent, the largest single cleanup we have seen from a core update.

In January 2025, Google updated its Search Quality Rater Guidelines to instruct raters to flag AI-generated main content as Lowest quality when it is copied, paraphrased, auto-generated, or reposted with little effort, originality, or added value for visitors. John Mueller confirmed the shift at Search Central Live Madrid in April 2025. Rater ratings do not set rankings directly, but they train the systems that do.

In June and August 2025, a wave of manual actions citing scaled content abuse hit sites that had been publishing AI output at volume. The August 2025 spam update integrated more advanced SpamBrain detection specifically targeting mass-produced AI text. December 2025's core update extended E-E-A-T scrutiny beyond YMYL into e-commerce reviews, SaaS comparisons, and how-to content, raising the bar for categories that had been relatively untouched. If your team publishes long-form content in any of these verticals, that update was your wake-up call.

The spam policy documentation now lists specific violations worth reading carefully. Using generative AI to produce many pages without adding value counts. Stitching or combining content from different web pages without adding value counts. Creating multiple sites to hide the scaled nature of content counts. The policy is method-agnostic on purpose. Google does not want to argue about which tool made the page. It wants to argue about whether the page deserves a spot in the results.

E-E-A-T Compliance for AI-Assisted Content

The operational answer to "how do we publish AI content without getting penalized" runs through Google's E-E-A-T framework: Experience, Expertise, Authoritativeness, Trustworthiness. Experience was added in December 2022 specifically because Google wanted to reward first-hand, real-world knowledge that large language models structurally struggle to produce. That last part is doing a lot of work for content teams now.

In practice, E-E-A-T compliance for AI-assisted content breaks down into a handful of concrete signals.

A real human byline with verifiable credentials. Quality raters look for detailed author bios that explain who wrote the piece, how their experience qualifies them (testing hours, career history, certifications), and why the content exists. They also look for dedicated author URLs with a professional photo, social links, and a portfolio of prior work. If you are serious about this, treat the author page as a ranking asset, not an afterthought.

Schema markup that ties content to identifiable entities. Roughly 68 percent of top-ranking sites use author and article schema, and pages implementing comprehensive structured data are about one-third more likely to be cited or surfaced in AI-generated answers. For AI-assisted content, your Article schema should include author as a Person, publisher as an Organization, datePublished, dateModified, mainEntityOfPage, and sameAs links to your author's LinkedIn, speaker pages, and other identity verification sources. This is one of the places where technical implementation matters more than copy polish.

Evidence of first-hand experience. NoFluff's 2025 testing found that unedited GPT-4o drafts bounced 18 percent higher and held visitors 31 percent less time than human-tuned versions. Injecting live GA4 dashboards and real screenshots into a CRO post materially raised dwell time. Google's own guidance places lived-experience evidence above textbook expertise. Screenshots, original datasets, and product walkthroughs are unambiguous Experience signals that no model can fabricate.

Original research, proprietary data, case studies. Launchcodex's analysis of post-March-2024 performance data found that pages with strong E-E-A-T signals had 30 percent higher odds of ranking in the top three positions compared to weak-signal pages. If your team has client data, account benchmarks, or audit findings, publishing summaries of them is the highest-ROI E-E-A-T move available to most businesses.

YMYL niches demand more. The updated quality rater guidelines single out health, finance, and legal content for stricter treatment, and the December 2025 update extended that scrutiny into adjacent categories. In October 2025, OpenAI restricted ChatGPT from providing tailored legal, medical, or financial advice. The direction of travel is clear: AI is not the last line of defense in high-stakes content, and Google expects humans with credentials to be.

The 2025-2026 AI Writing Tools Landscape

The AI writing tool market has consolidated around a handful of functional categories. Most premium tools are wrappers on the same underlying large language models, primarily GPT-4 and GPT-5 class, Claude, and Gemini. What you pay for is workflow.

General-purpose assistants

ChatGPT has the broadest ecosystem, the strongest third-party plugin community, and the best ideation feel for conversational drafting. Claude has a 200,000-plus token context window that makes it the strongest option for long-form research synthesis and editing, and it tends to produce more natural prose than GPT by default. Gemini integrates natively with Google Workspace and pulls live web data, which is useful for topical content. Most serious content teams use at least two of these, not because they do different things, but because each model has slightly different failure modes worth checking against.

SEO-native writing tools

Surfer AI and Surfer SEO score drafts against the live SERP for a target keyword. Surfer's own internal data suggests its Content Score correlates more strongly with rankings than backlink counts. Frase automates research, extracts SERP questions, and builds content briefs. MarketMuse, NeuronWriter, and Clearscope focus on topical coverage scoring and competitive gap analysis. Jasper is the marketing-focused platform of choice for teams that need a Brand Voice feature, 80-plus templates, and direct Surfer integration. It starts at $49 per month.

Short-form and bulk tools

Copy.ai has 90-plus templates and workflow automation with a free tier and a $49 per month Pro plan. Writesonic bridges marketing copy and SEO with a free tier and paid plans from $15 to $49. For bulk work, Hypotenuse handles the e-commerce teams producing 1,000-plus product descriptions, and SEOWriting pushes full blog posts with AI images directly into WordPress.

Editing Workflows That Actually Work

This is the section that separates ranking AI content from deindexed AI content. The data is unambiguous. Semrush's 2025 analysis of 42,000 blog pages across 20,000 keyword SERPs found that purely human-written content is roughly eight times more likely than AI content to rank at position #1. AI content still appears in the top ten, just lower on the page. In other words, AI can rank, but the top slot consistently goes to content with visible human fingerprints.

Ahrefs' 879-marketer survey backs up the hybrid winner. 97 percent of companies apply human oversight to AI output. AI users publish about 42 percent more content per month than non-users. The teams saving 20-plus hours per week (the top 20 percent, per Tech.co) actually spend more time reworking AI output, not less. Workday calls this the "AI tax on productivity" and pegs it at roughly 37 percent of the time saved. Read that number again. More than a third of what AI gives back in hours gets spent on cleaning up what AI did. This is not a failure of the tools. It is the price of admission for publishing AI-assisted content that ranks.

A production-grade human-in-the-loop workflow looks like this.

Originality and plagiarism checks. Originality.ai's Turbo 3.0.2 model reports 99 percent accuracy on flagship LLM output with a 1.5 percent false-positive rate. Its plagiarism checker V2, released May 2025, handles paraphrased content better than Copyscape or Grammarly in third-party benchmarks. We run every draft through both before it goes anywhere near publish.

Expertise injection. The editor's most valuable role is adding what AI structurally cannot produce: first-hand examples, proprietary data, practitioner quotes, contrarian opinions, case studies. This is where Experience signals enter the document. If your editor is just fixing grammar, you are leaving most of the ranking lift on the table.

Brand voice alignment. Custom GPTs or Jasper Brand Voice models trained on your best historical content will flag inconsistencies before human review. For agencies managing multiple client voices at once, this is the only realistic way to keep tone consistent as you scale a content program past two or three writers.

Final editorial sign-off. No piece publishes without a named human editor's approval logged against it. This is both a quality gate and an audit trail you will want if a client asks questions later.

The Numbers That Matter for 2026

Pulling the relevant statistics into one place, because you will need them in client decks and internal cases.

Adoption and usage

91 percent of marketers actively use AI in 2026. 85 percent use AI writing or content creation tools specifically. In Ahrefs' 879-marketer survey, 87 percent use AI to help create content. HubSpot's 2025 State of AI Report has 55 percent of marketers naming content creation as the top AI use case, up 12 points year over year. Content Marketing Institute data puts the expected 2025 usage rate at 90 percent, up from 83.2 percent in 2024 and 64.7 percent in 2023. The adoption curve is basically vertical.

Web prevalence

Ahrefs' April 2025 analysis of 900,000 newly indexed pages found 74.2 percent contained AI content and 86.5 percent of top-ranking pages did. Originality.ai puts the share of top-20 Google search results that are AI-generated at 17.31 percent as of September 2025. LinkedIn is further along: 53.7 percent of long-form posts in 2025 were classified as Likely AI. A 2025 University of Maryland study found roughly 9 percent of newly published newspaper articles are partially or fully AI-generated. The web is already past the tipping point on AI assistance. The question is who does it well.

Ranking and performance

Ahrefs' own data shows no correlation between AI content percentage and search ranking. Sites using AI grew organic traffic 5 percent faster year over year (29.08 percent vs. 24.21 percent median). Semrush says human content is eight times more likely than AI content to rank #1 for informational queries. In their practitioner survey, 72 percent of SEOs using AI say it performs as well as or better than human-written content, up from 64 percent in 2024. Ahrefs reports AI Overviews now reduce organic CTR at position #1 by 58 percent as of December 2025, up from 34.5 percent earlier that year. 91.4 percent of pages cited in AI Overviews contain some AI-generated content. Being cited in the Overview is the new first-place ranking for AI search visibility.

Productivity and cost

AI can cut blog-production time from 3.8 hours to as little as 9.5 minutes in structured workflows. The St. Louis Fed estimates GenAI saves workers 2.2 hours per week on average, or about 5.4 percent of work hours. MIT research documents a 40 percent boost in writing speed specifically. Ahrefs' cost survey pegs AI content at $131 per piece vs. $611 for fully human output, a 4.7x gap, and 38 percent of AI users say they have reduced spend on freelance writers. One documented agency case saw cost per article drop from $800 with outside production to $180 with AI plus internal edit, while volume tripled from four to twelve articles per month.

Trust and perception

A 2025 cross-market Statista survey found 70 percent of respondents struggle to trust online information because they cannot tell if AI wrote it. 64 percent fear elections are being manipulated by AI content. Reuters Institute identified "AI slop" as a top 2026 newsroom concern and found 48 percent of respondents would not trust AI to help create factual content at all. Motion Invest's 12-month study of website transactions showed human-content websites sold for 39 percent more than sites with disclosed AI content. Disclosure is honest. It is also expensive.

What Actually Ranks: The Operational Playbook

The best-performing AI-assisted content has observable structural traits. Synthesizing findings from Ahrefs, Semrush, Launchcodex, and CXL:

The edit ratio that matters. Launchcodex's analysis of post-March-2024 deindexations found that sites keeping AI-authored content below roughly 30 percent of total output, combined with consistent editorial review, minimized penalty risk. Sites at 80 percent or more unedited AI faced the highest deindexing rates. 90-percent AI sites were deindexed within three to six months. 30 percent is the practical safe harbor. Not a rule, a ceiling.

Original insights on every page. Google's systems reward Experience signals specifically, the lived-in detail that models cannot fabricate. GotchSEO's 2025 controlled experiment swapped 100 percent AI content for human-rewritten versions on the "SEO training Houston" query. Result: reindexing within hours, top-10 rankings shortly after. Pages that ranked before ranked again, once a human showed up in the text.

Topic clusters, not one-off posts. HireGrowth's 2025 analysis found content grouped into clusters drives about 30 percent more organic traffic and holds rankings 2.5 times longer than standalone pieces. Moz 2025 data shows sites implementing topic clusters see an average internal PageRank increase of 34 percent for cluster pages within 60 days. Google's June 2025 core update explicitly reinforced topical authority as a rewarded signal. One-off SEO posts are the weakest unit of production in 2026.

Internal linking that reflects entity relationships. Clusters work because link equity flows between semantically related pages in a way that AI systems (both Google's and the LLMs) can read. Use AI to audit gaps in your link graph. Use humans to decide which pillar pages deserve the flagship links. For local businesses, this is where local SEO content should tie back to city-specific pillar pages instead of drifting into generic territory.

Refreshing, not just publishing. Ahrefs' analysis of 17 million citations found AI search platforms prefer content that is 25.7 percent fresher than content cited in traditional organic results. Use AI specifically to update existing content with new data, new examples, new screenshots. For most sites, this is the highest-ROI AI use case available.

Multimedia enrichment. Charts, original screenshots, embedded dashboards, and video function as Experience signals and get disproportionately cited by AI Overviews. Surfer's AI Citation Report found YouTube alone accounts for roughly 23 percent of AI citations in finance queries. FAQ blocks with FAQPage schema are 3.2 times more likely to appear in AI Overviews. A good design system that makes it easy to embed custom charts and screenshots pays back in ranking visibility now.

Structure for extraction. Semrush found AI Overviews appear in 88 percent of informational-intent queries. Leading with a direct answer in the first 100 words, keeping paragraphs to two or three lines, using clear H2 and H3 hierarchies, and adding tables all materially increase citation probability. Listicles account for 21 to 60 percent of AI citations depending on the platform. Your content does not need to be shorter. It needs to be more extractable.

Structured data. Article, Person, Organization, and FAQ schema collectively do more SEO work in 2026 than they did five years ago. Sites with comprehensive JSON-LD are about a third more likely to be cited in AI-generated answers. If you do not have a schema audit scheduled in the next quarter, schedule one.

The Pitfalls That Get AI Content Deindexed

Google's March 2024 spam update produced the clearest ledger of what does not work. Of the 1,446 sites hit with manual actions after March 5, 2024, all of them contained some AI content, and roughly half were 90 percent or more AI-generated. The cumulative traffic loss across deindexed sites came to approximately 20 million monthly visitors. Named casualties included EquityAtlas, which had been getting over 4 million monthly organic visits before the crash, and Casual.App. Izoate.com saw an 89.14 percent traffic drop in March 2025 after a similar enforcement pass.

The recurring patterns are worth memorizing.

Scaled publication without human review. Templated pages where only a city name or keyword changes. The documented travel-site case spun up 50,000 "hotels in city" pages and lost 98 percent of them to deindexing within three months. If your program looks like that on a spreadsheet, it probably looks like that to Google too.

Hallucinated facts and fake citations. Ars Technica retracted a February 2026 article after a senior reporter used an AI chatbot to summarize notes and published hallucinated quotes attributed to a real person. The reporter was fired. The Chicago Sun-Times published an AI-generated Summer Reading List for 2025 in which 10 of 15 books did not exist. Wired and Business Insider both removed work by a writer who fabricated AI-sourced quotes. These are not edge cases. They are what unverified AI output produces by default.

Thin, generic content with no original value. Google's guidelines now explicitly equate AI content "with little to no effort, little to no originality, and little to no added value" with Lowest-quality ratings. The threshold is lower than most teams assume.

Keyword-stuffed prompt output. LLMs over-index on the keywords you give them. Unedited output often reads as dense repetition of a target phrase. This is a textbook "primary purpose of manipulating search rankings" signal to Google. An editor reading the draft aloud catches it in ten seconds.

Site-reputation abuse and parasite placements. The AdVon Commerce case used AI-generated product reviews with fake bylines and AI headshots across Sports Illustrated, USA Today's Reviewed, LA Times, Miami Herald, and Us Weekly. Terminations followed. Sports Illustrated's CEO Ross Levinsohn and multiple C-suite executives were fired. Partnerships were canceled. Union backlash was swift. For agencies building digital PR and link programs, the lesson is that content placed on authority sites is not a shortcut around quality. The host sites will get burned with you.

Undisclosed AI authorship in YMYL niches. Bloomberg News issued dozens of corrections to AI-generated summaries that published without editing. Gannett's AI-written local sports recaps in 2023 were widely ridiculed before being retracted. In health, finance, and legal, undisclosed AI is a reputation bomb waiting to go off.

AI Content and AEO/GEO: Writing for the LLMs That Read You

There is a recursive irony embedded in 2026 SEO. AI content teams are increasingly optimizing for AI-powered search engines (Google AI Overviews, AI Mode, ChatGPT, Perplexity, Claude) that themselves synthesize answers from other AI content. Ahrefs found 91.4 percent of pages cited in AI Overviews contain at least some AI-generated content. Originality.ai found 10.4 percent of AI Overview citations are themselves AI-generated. AI writes, AI reads, humans try to show up in both pipelines.

Three implications for content teams.

AI visibility is a distinct KPI now. AI Overviews appeared for 6.49 percent of US desktop queries in January 2025, spiked to 24.61 percent by July, and stabilized around 15.69 percent in November 2025. They trigger for 88 to 99.9 percent of informational queries. Being cited in the Overview is now more valuable than ranking #1 below it, because the Overview cuts organic CTR by up to 58 percent. Most teams have not yet updated their reporting to reflect this.

Good SEO is good GEO. Danny Sullivan's line, repeated in May 2025's Search Central post and at WordCamp US 2025, is Google's official position on Generative Engine Optimization. On January 8, 2026's Search Off the Record podcast, Sullivan explicitly discouraged fragmenting content into bite-sized chunks aimed at LLMs, arguing it would not survive ranking-system improvements. The fundamentals still win.

The formatting that earns citations is real. Airops' April 2026 data shows comparison pages with three tables earn 25.7 percent more ChatGPT citations. Validation pages with eight list sections earn 26.9 percent more. FAQPage-schema'd content is 3.2 times more likely to appear in AI Overviews. Brand search volume shows a 0.334 correlation with LLM citations, stronger than backlinks, per The Digital Bloom's 2025 visibility study. SE Ranking found domains with profiles on Trustpilot, G2, Capterra, or Yelp have three times higher odds of being chosen as a ChatGPT source. This is where SEO and conversion start merging into the same practice.

Practical Playbook for Agencies and Businesses

Team structure

The emerging "Editorial Mesh" pattern assigns five specialized roles at agencies scaling AI-assisted content. A researcher handling the human plus AI RAG pipeline, scored on accuracy and source quality. A writer handling AI drafting and prompt engineering, scored on voice adherence. An editor handling argument tightness, originality, and expertise injection. An SEO specialist handling keyword coverage and search intent alignment, usually with Surfer or Frase. A QA reviewer handling claim-by-claim fact verification.

For smaller teams, the minimum viable setup is one prompt engineer or strategist plus one senior editor, supported by a brief template, a style guide, an AI detection tool, and a plagiarism checker. Anything less and you are not editing, you are rubber-stamping.

How to brief AI tools effectively

Good prompts include target audience and ICP, tone, three must-include proof points (data, quotes, or examples), explicit source constraints (the "use only the attached research" instruction), target keyword with long-tail variants, the single most important question the piece must answer, and a word count. Bad prompts ask for "a 2,000-word SEO article about X." The brief is where the humanizing starts, not the edit.

Quality assurance at scale

Workday's research showing 37 percent of AI time savings goes to rework is not a failure. It is the insurance premium. Build the rework into the workflow explicitly. A realistic QA stack includes an AI-as-Judge prompt scanning drafts for unsupported claims and style violations, an AI detector like Originality.ai for client reports, a plagiarism checker, and a named human editor sign-off logged per piece. If you cannot name the person who approved a given URL, you do not have a quality process.

Client-side considerations

Transparency clauses are increasingly standard in agency contracts. So are indemnification provisions for manual actions caused by agency-produced content. Motion Invest's study showing disclosed-AI sites sell for 39 percent less is a data point worth surfacing in client conversations about risk. For YMYL clients in health, finance, or legal, get explicit sign-off on which workflow stages AI touches, require named human experts as bylines, and keep an audit log. If a client wants more volume than your human editorial capacity can review, push back on the brief or change the pricing. Do not loosen the review.

Scaling without becoming spam. The inflection point, based on the data above, is roughly 30 percent AI share of main content as a safe ceiling if rigorous human editing is applied. Anything approaching 80 percent unedited AI is a material penalty risk. A useful heuristic: if your volume target exceeds your team's ability to verify claims on every published piece, the answer is not to reduce verification. It is to reduce volume, raise prices, or hire.

Case Studies: What Success and Failure Look Like

What failure looks like

Sports Illustrated and The Arena Group (November 2023). Futurism exposed AI-generated product reviews bylined to fictional writers with AI-generated headshots. CEO Ross Levinsohn, COO Andrew Kraft, media president Rob Barrett, and corporate counsel Julie Fenster were all fired. Content was pulled.

AdVon Commerce (2024). The third-party vendor that supplied Sports Illustrated was found placing similar AI-generated reviews at LA Times, Miami Herald, Us Weekly, USA Today's Reviewed, and McClatchy outlets. McClatchy removed all AdVon content after seeing Futurism's evidence.

CNET and Bankrate (Red Ventures, 2023). After 77 AI-generated stories required corrections for factual errors, both sites paused the program under public pressure. Internal meetings leaked to The Verge revealed plans to resume once coverage cooled.

Ars Technica (February 2026). A senior reporter used an AI chatbot to summarize notes and published fabricated quotes attributed to Matplotlib maintainer Scott Shambaugh. Retraction came within two hours. Termination followed.

Microsoft Start (2023). An AI-generated Ottawa travel guide recommended the Ottawa Food Bank as a tourist hotspot. Content was pulled amid public embarrassment.

Deindexed niche sites (March 2024). At least 1,446 sites, including EquityAtlas and Casual.App, received manual actions and went to zero organic traffic. Combined: roughly 20 million monthly visits lost.

What success looks like

Ahrefs' two-site experiment. One site ran raw unedited AI output. One site ran edited AI output. Both ranked in Google. The edited site performed materially better. The result is consistent with Google's stated position that AI is a tool, not a replacement.

Semrush's 42,000-page SERP analysis. AI and mixed content appears widely in the top ten, but human-led content dominates position #1 by an 8x margin. Hybrid workflows with strong human editorial win the top slots.

Series B SaaS case (2025). Moved from four to twelve monthly articles with the same two-person team using an AI plus human-edit workflow. Organic traffic up 40 percent in six months. Cost per article fell from $800 to $180. The math still works when the editing is real.

Dynamic Mockups (Omnius case study). Programmatic SEO at scale, paired with conversion-focused structure and tight long-tail intent, drove monthly signups from 67 to over 2,100. That is a 3,035 percent increase. Organic traffic up 850 percent. The contrast with the deindexed travel-hotels-by-city example is that Dynamic Mockups added real utility per page. Programmatic is not the problem. Thin is.

Gotch SEO's reindexing test. Replacing a 100 percent AI page with upgraded human content on "SEO training Houston" drove reindexing within hours and a top-10 ranking. The takeaway is the cleanest in the dataset: when you put a real person into the content, Google treats it like real content again.

The Bottom Line for 2026

The best practices that keep AI-assisted content ranking are no longer a matter of opinion. They are documented in Google's own spam policies, in the Search Quality Rater Guidelines, in public statements from Sullivan, Mueller, Gary Illyes, and Elizabeth Reid, and they are corroborated by the largest independent datasets we have. Ahrefs' 900,000-page crawl. Semrush's 10-million-keyword AI Overviews study and 42,000-page SERP analysis. Originality.ai's detection benchmarks. The 1,446 deindexed sites from March 2024.

Distilled to seven rules:

1. Use AI, but never publish unedited output. Keep unedited AI share of main content under 30 percent. 80 percent or more is a statistically demonstrated penalty zone.
2. Lead with E-E-A-T. Real author bios, schema, credentials, first-hand examples, and original data do more for rankings in 2026 than they did in 2022 because they are now scarce.
3. Humans add the Experience layer. Screenshots, proprietary datasets, quotes from named practitioners, case studies, contrarian opinions. These are the signals LLMs cannot produce and that both Google and AI Overviews reward.
4. Build topic clusters and refresh relentlessly. Topic clusters increase organic traffic by about 30 percent and hold rankings 2.5 times longer. AI search platforms prefer content 25.7 percent fresher than traditional organic results.
5. Structure for humans and machines. Direct-answer leads, clear hierarchies, FAQ schema, JSON-LD, named authors.
6. Disclose when appropriate, always in YMYL. Audiences are skeptical. 70 percent struggle to trust online content because of AI. 48 percent distrust AI-assisted factual content. Google's quality raters read disclosure as a trust signal.
7. Treat the 37 percent rework tax as a feature, not a bug. The teams getting the biggest productivity gains are the ones spending the most time on human review. That review is what separates a ranking asset from a deindexed one.

The agencies and businesses winning at AI-assisted content in 2026 are not the ones producing the most. They are the ones whose output is indistinguishable from the best human content in the category, because the human fingerprint is still there. Just applied at a different point in the pipeline. That is the whole game.

Author

Michael Timi

Partner & Marketing Manager, eMac Media

Drives strategic partnerships and revenue growth through high-impact marketing initiatives, business development, and lead generation.

Editor

Princess Pitts

Director of Communications Strategy, eMac Media

Specializes in editorial strategy, content governance, and brand communications at scale.