# Research enterprise generative AI adoption on LinkedIn

**Use case:** 

Explore how professionals discuss generative AI adoption in the enterprise. Export relevant public LinkedIn posts, author details and available engagement to identify themes for market research, reports and content planning. AI checks meaning rather than simple word overlap. Change the topic to explore your own technology niche.

## Input

```json
{
  "keywords": [
    "enterprise generative AI adoption"
  ],
  "maxPostsPerKeyword": 10,
  "country": "us"
}
```

## Output

```json
{
  "imageUrl": {
    "label": "Main image",
    "format": "string"
  },
  "authorName": {
    "label": "Author name",
    "format": "string"
  },
  "authorHeadline": {
    "label": "Author headline",
    "format": "string"
  },
  "text": {
    "label": "Post text",
    "format": "string"
  },
  "reactionsCount": {
    "label": "Reactions",
    "format": "integer"
  },
  "commentsCount": {
    "label": "Comments",
    "format": "integer"
  },
  "postedAt": {
    "label": "Posted at",
    "format": "string"
  },
  "postUrl": {
    "label": "Post URL",
    "format": "string"
  },
  "searchKeyword": {
    "label": "Search topic",
    "format": "string"
  },
  "isRelevant": {
    "label": "AI relevant",
    "format": "boolean"
  },
  "relevanceProbability": {
    "label": "Relevance probability",
    "format": "number"
  }
}
```

## About this Actor

This example demonstrates how to use [LinkedIn Post Search Scraper 2$/1K](https://apify.com/lofomachines/linkedin-post-search-scraper.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/lofomachines/linkedin-post-search-scraper.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/lofomachines/linkedin-post-search-scraper.md

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).