Short answer. In July 2026 the delivery model met in one room. A three-week working residency at Lifewood's Kuala Lumpur office brought together the country heads of China, the Philippines, Bangladesh and Indonesia, along with their team leaders and top leadership, to align how AEO, GEO and AIGC are delivered across a distributed operation. This is what came out of it — the decisions, the disagreements, and what changed afterwards.
Key takeaways
- Lifewood held a three-week working residency in Kuala Lumpur in July 2026, bringing together country heads and team leaders from China, the Philippines, Bangladesh and Indonesia.
- Lifewood's CEO Ronald Cheung, CKO Eric Kang and COO Wilson joined the sessions in person alongside client meetings that ran in parallel.
- Lifewood runs a follow-the-sun delivery model across 40+ delivery centres in 30+ countries, staffed by 56,000+ registered contributors.
- AI agents and AI search drove roughly 20% of 2025 U.S. holiday retail sales, worth about $262 billion, which is why brands now treat AI visibility as a revenue question.
- AEO and GEO work depends on distributed, native-speaker teams because accuracy has to hold in 50+ languages, market by market.
What happened at the Kuala Lumpur meeting in July 2026?
Country heads and team leaders from four countries — China, the Philippines, Bangladesh and Indonesia — spent three intensive weeks together at Lifewood's Malaysia office instead of meeting over video calls.
Lifewood's top leadership joined them for the meeting: CEO Ronald Cheung, CKO Eric Kang, and COO Wilson. Teams ran working sessions on the AEO/GEO services and the AIGC pipeline, aligning methodology, sharpening quality standards, and pressure-testing how work moves between centres. They walked through other projects Lifewood is building, compared notes across markets, and mapped how each country's strengths fit the whole. Several client meetings ran alongside the internal sessions, which kept every discussion grounded in real briefs rather than theory. As one participant put it, nothing focuses a methodology debate like a client meeting waiting in the next room. What the country heads flew home with was more than alignment on process — colleagues who had been names on a screen became people they had argued with, laughed with, and solved problems with, and distributed teams still run on trust built in person.
Why does global collaboration matter for AI data work?
Global collaboration matters because every AI answer a user sees hides a human supply chain of collection, cleaning, labelling and verification, and that chain runs across borders.
Lifewood's country teams each answer to a country head who owns quality and delivery in that market, and the teams hand work to each other as the day turns. Follow-the-sun delivery is a model where work passes between time zones so a team in one region continues a task the moment a team in another region ends its day, keeping a project moving around the clock instead of pausing overnight. Lifewood runs this relay through 40+ delivery centres across 30+ countries, staffed by 56,000+ registered contributors. For a look at how that pipeline turns into content that AI engines will actually surface, see how AI-generated content affects search rankings.
Why does AI visibility matter for brands right now?
AI visibility matters because AI-driven commerce has moved past the experimental stage and into a measurable share of retail spending.
According to Salesforce, AI agents and AI-powered search drove about 20% of 2025 U.S. holiday retail sales, worth roughly $262 billion. When a buying decision starts and ends inside an AI answer, a brand that is absent from that answer loses a sale no analytics dashboard will ever record. That is the problem AEO and GEO programmes exist to close, and it is why a buyer's guide to multilingual AI visibility services is a useful next read for any brand starting from zero.
What are AEO and GEO services?
AEO and GEO are the disciplines of making a brand discoverable and accurately represented inside AI assistants rather than on a traditional search results page.
Answer Engine Optimization (AEO) is the practice of structuring a brand's content so answer engines such as ChatGPT, Perplexity and Google AI Overviews can retrieve and cite it correctly. Generative Engine Optimization (GEO) is the related practice of shaping content, structured data and third-party signals so generative AI models represent a brand accurately across languages and markets. Distributed teams are built for exactly this problem: making a brand quotable in 50+ languages is not a job for one office. Native speakers have to check, market by market, that the facts an AI engine extracts stay correct in every language a customer might use, with strategy set globally and evidence built locally. Readers comparing providers for this work can start with Lifewood's position among the best AEO and GEO agencies or an overview of what answer engine optimization actually involves.
How does Lifewood keep AIGC production reliable?
Lifewood keeps AI-generated content reliable by keeping humans in the loop at every stage: AI generates, people verify, and the loop itself is the product.
AI-Generated Content (AIGC) is content — text, image, audio or video — produced with AI tools and then checked and approved by human reviewers before it reaches a client. A concept drafted in one delivery centre can be localised in a second, quality-checked in a third, and delivered to a client on a fourth continent, powered by employees across Lifewood's countries of operation. The result is AI-generated, human-approved and globally assembled, which is the combination that makes it usable at enterprise scale.
Which AI data services does Lifewood provide?
Lifewood covers the full AI data lifecycle, from raw data collection through to answer-layer visibility, delivered by the same distributed teams that met in Kuala Lumpur.
The portfolio spans five areas. Data collection and annotation covers text, image, audio and video work across 50+ languages, including low-resource ones. LLM training data covers supervised fine-tuning, RLHF and evaluation datasets, held to a 95%+ accuracy SLA and checked against a customer-approved gold set. AIGC production delivers enterprise content and video verified by human reviewers, as described above. AEO/GEO programmes build brand visibility and accuracy inside AI assistants, market by market. Multilingual SEO extends search visibility across Southeast Asian and other Asian languages. Lifewood was founded in 2004 and has run this delivery model for over two decades, refocusing specifically on AI data work in 2018. Its LLM data practice runs a multi-stage, human-in-the-loop pipeline in which trained annotators create data, senior reviewers audit it, and automated checks flag outliers. For the GEO side of that portfolio in more depth, see the complete guide to generative engine optimization.
What should a brand do to build AI visibility across markets?
A brand should start with an honest audit of which markets and languages matter most, because AEO and GEO work is only as strong as the local evidence behind it.
The takeaway from three weeks in Kuala Lumpur applies to any brief: the strongest AI outcomes come from people who collaborate across borders and verify each other's work, not from a single office guessing at how a distant market speaks. A brand weighing whether to build that capability in-house or bring in a distributed team can compare the tradeoffs in a guide to AEO and GEO providers or read more on generative engine optimization strategy before deciding.