# Rekha Thomas

Rekha Thomas is a B2B marketing leader who leads the Forbes Communications Council CMOs Group and shares guidance on go-to-market strategy, content marketing, AI, and PR.

- Profile: https://b2binfluencer.marketing/creators/rekha-thomas/
- LinkedIn: https://www.linkedin.com/in/rekhathomas
- Topics: artificial-intelligence, leadership, content-marketing, go-to-market-strategy, ai-in-marketing, generative-engine-optimization
- Based on 14 dated posts, latest 2026-08-20

## Summary

Rekha Thomas is most useful for executive-level B2B go-to-market, content, AI, and PR guidance.

- Best for: A B2B SaaS campaign seeking senior practitioner attention on AI-era go-to-market strategy.
- Not for: A martech or consumer vendor seeking paid placement with fixed deliverable and audience guarantee.
- Check first: Confirm whether they accept paid work and ask for audience data.

### Takeaways

- AI adoption moves through three stages, and most teams are early.
- PR should help shape the story early because AI search rewards citations.
- LLM reference rate is presented as a new measure of category mindshare.

## Main ideas

- **The pre-GenAI content playbook no longer fits buyers, and no one has a proven replacement**: Rekha Thomas argues that content strategy written before generative AI no longer matches how buyers research and decide. They frame 2026 as an experimentation year, with senior marketers’ range of bets reflecting the state of the field.
- **PR should help shape the story early, because AI search rewards citations from elsewhere**: Thomas argues that as third-party citations matter more than a brand's own content for generative engine optimization visibility, PR shifts from a pitching service to a strategic function. The failure mode they identify: product marketing writes a launch narrative or thought-leadership piece and hands it to PR to pitch, with disappointing media interest. The better pattern is for PR to feed early intelligence on what is trending and where market buzz sits, then co-craft the story with product marketing at the intersection of industry interest and business relevance. Thomas recommends social listening for pattern recognition, including AI tools that scan public posts on LinkedIn, Reddit, Facebook, Instagram and X for rising negative signals. Ask whether the tools cover the public pages relevant to your audience.
- **A brand's 'LLM reference rate' is becoming the new measure of category mindshare**: Thomas argues that organic traffic has stopped working as a proxy for category mindshare, and that how often a brand is cited in topic-relevant AI answers is now a better leading indicator of down-funnel demand. The figures cited: organic SEO traffic down about 2.5% year over year, AI Overviews appearing in roughly 30% of searches, organic click-through rate dropping about 35% when those overviews appear, and AI-referred visitors converting far above traditional organic. Thomas recommends answer engine optimization built on clear, evidence-based, authoritative content, plus one narrative carried across PR, content marketing, product marketing and demand generation instead of siloed calendars.
- **AI adoption in go-to-market moves through three stages, and most teams are early**: In a write-up of a Neythri.org GTM Roundtable discussion among South Asian women go-to-market leaders, Thomas organizes AI maturity into three stages. Stage one is individual experimentation, where content creation is the lowest-hanging fruit and prompts grow more prescriptive about brand, messaging and voice to avoid generic output. Stage two is team-level workflows—scalable design systems, intake agents, customer support agents—which bring governance, company-sanctioned tools, protection of IP and data, and human-in-the-loop review before anything ships. Stage three is cross-functional AI architecture, which requires data cleansing and consolidation across systems, as well as people work, including AI councils that bring go-to-market and technical leaders together. Thomas notes that wins still feel hard to prove and that measurement is shifting from activity to impact metrics.
- **Convening senior peers is part of the method, not a side activity**: Most of Thomas's published guidance comes out of forums they run or join rather than solo commentary. They grew the Forbes Communications Council Content Marketing Group past 100 members, then took over the CMOs Group. Its stated mission is to give curious CMOs and senior marketing executives a forum to debate go-to-market, leadership, organizational design, cross-functional alignment, campaigns, metrics and AI innovation, publishing through Expert Panel articles.

## Work to read

- [Three stages of AI maturity across sales, marketing, and CX](https://www.linkedin.com/posts/rekhathomas_ai-gtm-leadership-activity-7432916106438414336-_vBt)
- [AI search metrics and the shift to LLM reference rate](https://www.linkedin.com/posts/rekhathomas_ai-search-seo-activity-7429958044467482624-sT0Y)
- [Seven marketing leaders on the post-GenAI content playbook](https://www.linkedin.com/posts/rekhathomas_forbes-cmo-content-activity-7415453064435949568-MFJv)
- [PR's strategic shift as third-party citations drive GEO visibility](https://www.linkedin.com/posts/rekhathomas_forbes-pr-communications-activity-7422343522164486144-nhvl)
- [Leading the Forbes Councils CMOs Group](https://www.linkedin.com/posts/rekhathomas_cmo-marketing-gotomarket-activity-7423104801774882816-EHFQ)

## Brand relationships

- **Forbes Communications Council** (mention)
- **Neythri.org** (mention)

## Partnerships

Thomas’s five posts from January and February 2026 cover go-to-market leadership roundtables, Forbes Communications Council group work, AI-era content strategy, PR and social listening, and AI search visibility. They describe their leadership roles—they lead the Forbes Communications Council CMOs Group and previously built its Content Marketing Group—and quote them as a source in Forbes articles. The posts don’t mention partnerships, sponsorships, or commercial integrations, or provide a branded-content format, sponsored-series placement, rate card, audience-deliverable specification, or official inquiry route. Ask Thomas directly about partnership options and any named format before committing budget.

## Alternatives

- Courtney Damji: Courtney Damji is the better choice when a B2B SaaS campaign prioritizes content operations, cross-functional sourcing, and community curation over AI-search measurement and executive AI-maturity frameworks. Rekha Thomas's posts show a practical method for finding resonant language: bring in sales and customer-success conversations, record customer calls, and use those notes to reshape copy. One example describes a Hightouch ad-copy reset after listening to customer calls. The posts also show a curator’s instinct for naming blogs, newsletters, and podcasts worth following—useful for a brand seeking a practitioner-led reading list, an editorial sourcing system, or a content team that can borrow credibility from an established network rather than build a new framework.
- Randy Likas: Randy Likas is the better choice when a B2B SaaS campaign focuses less on content calendars and PR alignment and more on why AI pilots fail to change the operating model. The posts address how pilots can succeed under contained conditions with dedicated people and resources, then stall when leaders face disrupted workflows, role changes, incentives, and executive sponsorship tests. They bring in named practitioner perspectives on product-centered design for RevOps, systems, and data engineering; an R&D-like operating model for AI transformation; and the need to understand how work gets done before deciding where AI belongs. A second post adds a planning-season lens: budget pressure, questions about where team time goes, and the use of meeting-quality analysis across churned, renewed, and expanded accounts to redesign playbooks. This suits a B2B SaaS company whose AI-era GTM problem is really an operating-model and RevOps problem.
- Sim Aulakh: Sim Aulakh is the better choice when a B2B SaaS campaign prioritizes third-party validation, media placement, and authority-building to earn enterprise trust. The posts detail a signal-based PR method: track reporter coverage trends, funding, regulatory updates, and workforce or margin-pressure stories; spot topic velocity; reframe a product story around the buyer’s financial or operational tension; and pitch with a recent article reference, a specific stat, and timing. The second post makes the underlying argument directly: buyers and AI systems ask whether anyone has heard of the company, whether it has credible features, and what industry experts say; paid ads, outbound, and events do not create that trust. For a B2B SaaS company selling into risk-averse enterprise procurement, especially in healthtech or another vertical where trade publications matter, this is a more specific match than a general content-strategy voice.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/