Can a Factory Do AI Search Optimization In-House?

The answer isn't "yes" or "no" — AI search optimization splits into three blocks: one a factory can do itself, one that needs sustained manpower over time, and one better handed to outside support. Seeing that division clearly is more useful than agonising over "in-house or outsourced".

One caveat up front: there is no zero-cost shortcut here. Anyone telling you "publish a few articles and AI will recommend you" deserves a raised eyebrow. What follows is how to get this done with a reasonable investment.

First, split the work into three blocks

When owners ask "can we do it ourselves?", they're treating a complex job as a single action. Break it open and it gets clear.

• Block one — diagnosis: find out where your brand currently stands in AI;
• Block two — content production: write in an AI-friendly way and lay out sources;
• Block three — ongoing monitoring: review regularly and adjust course.

The three differ in difficulty, investment and how far they can be outsourced.

Block one, diagnosis: you can absolutely do this yourself

This block has the lowest bar, and I'd suggest doing it yourself once — not to save money, but to know where you're heading.

How: fix on 5 to 10 questions your customers ask most ("which factories in Shenzhen make X", for instance), put each to Doubao, DeepSeek and ChatGPT, and save screenshots of the answers. Then tally: how many answers mentioned you, where you ranked, how often competitors appeared.

This takes a day, costs nothing, and instantly breaks the illusion that "we're doing fine". Many factory owners only discover at this point that they are virtually invisible in AI.

Block two, content production: it depends on your manpower

This block carries the most work — and decides success or failure.

If you have a content team, you can do it in-house

But three conditions have to hold.

• Someone can write industry content: not product selling points, but informational pieces on "how to choose in this category, what the pitfalls are";
• Output can be sustained: AI's understanding is built by accumulation, and stop-start effort does nothing;
• You understand AI-friendly writing: conclusion first, structured, backed by evidence — all three are hard requirements.

Without dedicated people, this content is hard to carry alone

Because writing this content needs two abilities stacked: knowing the industry (what customers ask) plus understanding AI's citation logic (how to write so you get lifted into an answer). Most factories have the first and lack the second. That's why many hand this block to outside help.

One data point by the way: CAICT's white paper shows that by the end of 2025, over 68% of China's large and mid-sized enterprises had put GEO (Generative Engine Optimization) into their annual marketing budget (cited via People's Daily Online). So it's no longer a question of whether to do it, but of how to prioritise it.

Block three, ongoing monitoring: at minimum, keep a light in-house watch

There are two routes for monitoring.

• A light in-house watch: ask the same questions once a week and log mention rate and position changes. Zero cost, but it takes a person;
• Tools or outside support: continuous tracking through a tool or a vendor. More efficient, but it costs money.

My advice: at the start, test it yourself and establish a baseline. Even if you later hand it over, you need your own yardstick — otherwise you can't tell whether the numbers you're given are real.

A decision framework: three questions set the division of labour

Here's the whole thing boiled down to three questions.

• Can anyone sustain writing industry content? — If not, block two needs outside help.
• Does anyone understand AI-friendly writing? — If not, close that knowledge gap first, or bring someone in to run it once.
• Does anyone have two hours a week for monitoring? — If yes, carry block three in-house; if not, consider a tool.

A company that answers "no" to all three will most likely give up halfway on its own — not for lack of ability, but for lack of sustained investment.

Three questions about outsourcing, answered

1. Does hiring a vendor mean it's sorted for good?

No. GEO is ongoing operations, not a one-off project. Any "done and dusted" claim is false — AI models update, competitors move, and the way customers ask changes.

2. How do you judge whether a provider is reliable?

Three things: ① does he diagnose before acting (be wary of anyone quoting a package straight away); ② does he offer probabilities or promises (anyone saying "we guarantee AI will recommend you" isn't being truthful); ③ does he hold a compliance line (whether he explicitly refuses "poisoning"-style mass posting).

3. If we do it ourselves, how soon will it work?

No timeline is promised. What can be said clearly: AI has to crawl first, then understand, then build trust. It's about accumulating something, not buying ads — which is why continuity matters more than one-off spending.

In closing

To wrap up: AI search optimization isn't a yes-or-no choice — it's a question of allocation: which blocks you keep and which you hand over. Do diagnosis yourself first (zero cost, quick education), judge content by your manpower, and at minimum keep a light in-house watch on monitoring.

If you do only one thing, do the diagnosis — it's the starting point for everything else, and your own yardstick for judging whether a provider is any good.

Have you tested how your company shows up in AI? How far off was the result from what you expected? Tell me in the comments.

Yihang Network, based in Shenzhen, previously worked in cross-border B2B and Alibaba.com-related services, and expanded into GEO from 2024. Our own service also starts with diagnosis — acting without diagnosing is a good way to waste effort.

Data and scope note: The CAICT figure comes from its "2025 Generative Engine Optimization Industry White Paper", cited via People's Daily Online. The methods described raise the probability of being retrieved and cited; they do not guarantee a company will appear in AI answers, and no timeline or business result is promised. The criteria for judging a provider are practical suggestions and do not constitute an assessment of any specific organisation.

1. China Academy of Information and Communications Technology (CAICT), "2025 Generative Engine Optimization Industry White Paper", cited via People's Daily Online, March 2026
2. China Internet Network Information Center (CNNIC), "Generative AI Application Development Report (2025)", October 2025
3. Google Search Central, "AI features and your website"