1. Executive Summary
When you ask, “What is an AI agent and how does it work?” today’s AI answer engines (like ChatGPT, Google AI Mode, and Perplexity) give you definitions that rely mostly on big enterprise tech brands and analyst sources—not consumer products.
- ChatGPT gives you its own answer. It does not cite external sources.
- Perplexity cites 10 external sources. Most come from:
- Big cloud and enterprise tech brands: AWS, Google Cloud, Microsoft, IBM, UiPath, GitHub
- Strategy consulting: McKinsey, BCG
- Community sources: Reddit (2 threads)
Each source acts like a product competing to be the leading authority for “AI agent” definitions.
Big AEO trends you need to know:
- Enterprise brands—especially major cloud providers—dominate visibility in AI answers.
- Consulting firms (McKinsey and BCG) boost the credibility of the overall definition and focus on business impact.
- GitHub and UiPath rank for practical or technical context, not for core definitions.
- Reddit threads appear as supporting discussion, showing the term is still new and debated.
If you want your company’s views on AI agents to appear in LLM answers:
You need a clear definition, well-structured content, and reliable citations that can compete with the likes of AWS, Google, Microsoft, IBM, and top consultancies.
2. Methodology
2.1 Queries and Tools Used
The main question: “What is an AI agent and how does it work?”
- ChatGPT ([Reference 1])
- Google AI Mode (no sources provided for this query)
- Perplexity ([Reference 2], with explicit citations)
2.2 Data Collected
- ChatGPT provides an in-depth explanation—without URLs.
- Google AI Mode gives a short answer—without citing sources.
- Perplexity cites 10 external sources and summarizes from each.
2.3 How We Judged Source Visibility
We rated each brand’s “AI agent” page (found by Perplexity) on five things:
- Clarity: How clearly does the page define “AI agent”?
- Structure: Does the page use schema, clear headings, or glossary formats that are easy for machines to read?
- Citations: How often do AI engines (or other sites) refer to the page?
- Freshness & Depth: Is the content up to date and deep enough to cover subtopics and uses?
- Authority: How strongly does the brand connect to AI or enterprise automation?
Scores run 1–5 (5: best), based on:
- Source’s use in Perplexity’s answer.
- Domain authority.
- Usual content style and structure on that brand’s site.
3. Overall Rankings: Top Source Pages
We focus on the pages Perplexity actually cited for “What is an AI agent…?”
| Rank | Brand / Source | Type | Clarity | Structure | Citations | Freshness | Authority | Notes/Citation |
|---|---|---|---|---|---|---|---|---|
| 1 | AWS – “What are AI Agents?” | Official definition / explainer | 5 | 4 | 5 | 4 | 5 | [1] |
| 2 | Google Cloud – “What are AI agents?” | Official definition / explainer | 5 | 5 | 5 | 4 | 5 | [3] |
| 3 | Microsoft – AI agents explainer | Editorial / thought leadership | 4 | 4 | 5 | 4 | 5 | [4] |
| 4 | IBM – “What Are AI Agents?” | Glossary / topic hub | 5 | 4 | 4 | 4 | 5 | [5] |
| 5 | McKinsey – “What is an AI agent?” | Explainer / management brief | 4 | 4 | 4 | 4 | 5 | [6] |
| 6 | BCG – “AI Agents: What They Are…” | Thought leadership / POV | 4 | 4 | 4 | 4 | 5 | [8] |
| 7 | UiPath – “What are AI Agents?” | Product-angled explainer | 4 | 4 | 3 | 4 | 4 | [7] |
| 8 | GitHub – “What are AI agents?” | Developer article | 4 | 4 | 3 | 4 | 4 | [9] |
| 9 | Reddit – AI Agents: What and How? | Community Q&A | 3 | 1 | 3 | 3 | 3 | [2] |
| 10 | Reddit – What even is an AI agent? | Community Q&A | 3 | 1 | 3 | 3 | 3 | [10] |
Note: Google’s LLM answers align with its Cloud explainer ([3]).
4. Brand Breakdown: What Makes Each Page Rank?
4.1 AWS – “What are AI Agents?” [1]
Why AWS ranks #1:
AWS sets out a clear definition and shows how businesses use AI agents.
Its page has good structure and appears in technical documentation all over the web.
AWS regularly updates these pages and people trust AWS on AI topics.
What you can learn:
Give a precise definition and explain business use right away. Use clear headings.
Expand schema (like FAQ or HowTo) and link a short glossary definition across your site.
4.2 Google Cloud – “What are AI agents? Definition, examples, and types” [3]
Why this ranks #2:
The title says exactly what users search for.
Google Cloud’s docs use clear headers and, often, schema markup.
Many sites and tutorials quote Google’s definitions.
Tip for you:
Add FAQs and diagrams that clearly spell out what an AI agent is (and is not).
Include bullet points and alt text for clarity.
4.3 Microsoft – “AI agents — what they are, and how they’ll change the way we work” [4]
Why it shows up:
Microsoft focuses on how AI agents will change work.
Its article uses an accessible format and its messaging is widely quoted.
Advice:
Place a simple, two-sentence definition at the top.
Use structured data (FAQ) to boost visibility.
4.4 IBM – “What Are AI Agents?” [5]
IBM gets cited because:
It gives a short definition.
IBM’s coverage includes benefits, challenges, and use cases.
It gains trust from its long history in AI.
Improve by:
Adding technical diagrams and using more structured metadata for product pages.
4.5 McKinsey – “What is an AI agent?” [6]
Why McKinsey shows up:
Strong business focus, with clear structure.
Heavy use in management and business media.
Weakness:
Less technical depth. Add more product architecture or implementation detail.
Link out to technical guides for follow-up questions.
4.6 BCG – “AI Agents: What They Are and Their Business Impact” [8]
BCG’s strength:
Ties definition directly to business value.
Offers narrative analogies for easy LLM summarization.
Improve by:
Adding a concise, standalone definition and more structured FAQ.
4.7 UiPath – “What are AI Agents?” [7]
UiPath’s advantage:
Explains how AI agents drive enterprise automation.
Try this:
Start with a neutral, vendor-independent definition.
Clearly mark up your page as a software product in the schema metadata.
4.8 GitHub – “What are AI agents?” [9]
GitHub gets picked for:
Explaining how AI agents automate development work and improve code.
To expand reach:
Add a plain-language summary at the top.
Answer broader “what is” and “how it works” queries, not just developer-focused ones.
4.9 Reddit – Community Threads [2], [10]
Reddit’s role:
Shows confusion and debate on what AI agents are.
Confirms the topic is still evolving.
If you want to outrank Reddit:
Fill the gap: Write clear, jargon-free explainers aimed at users new to the topic.
5. Why These Brands Show Up
- Brands use definition-first titles (“What are AI agents?”) that exactly match common queries.
- They structure pages like FAQ or glossaries, which LLMs easily pull from.
- Their wide citation across the web builds “trust signals” for AI engines.
- Regular updates and new examples keep pages relevant.
- Content covers everything from core definition to technical and business details, letting LLMs answer a range of related questions.
6. What Leaders Get Right—and Where Gaps Remain
What they do well:
- They put definitions up front, using clear, trusted language (autonomy, acting for the user, etc.).
- They provide both concepts and practical “how it works” details.
- They link definitions to real use cases and business outcomes.
Gaps you can fill:
- Few use explicit FAQ schema, even if they structure content like FAQs.
- Little direct comparison between tools, frameworks, or vendors.
- Reddit’s presence shows the language and definitions are still fragmented, so you can help set the standard.
Who could break in next:
- UiPath and GitHub show if you make practical, how-to content, you can win future queries as users look up how to build or deploy agents.
- New players can rise if they post clear, neutral definitions plus in-depth implementation guides.
7. Winning Tactics: How to Get Your Page Ranked
To improve your brand’s answer-engine performance:
7.1 Build a Canonical “What Is an AI Agent?” Page
- Use a definition-led title.
- Start with a simple, two-sentence definition (covering autonomy, goal pursuit, and the agent loop).
- Lay out sections: how agents work, types, example use cases, business implications, and how your tools fit in.
7.2 Strengthen Your Entity Signals
- Use the term “AI agent” consistently throughout your site.
- Link every mention of “AI agent” back to your key page.
7.3 Add Strong Structured Data
- Use Article and FAQ schema.
- Add clear, machine-readable FAQs:
- What is an AI agent?
- How do AI agents work?
- How are they different from chatbots or RPA?
- If you offer tools, use appropriate schema for software products.
7.4 Build Citations and Mentions
- Write objective explainers that others want to cite.
- Release detailed case studies.
- Present at conferences and publish co-branded reports when possible.
7.5 Keep Content Fresh and Deep
- Update at least every quarter.
- Add new diagrams and real-world examples.
- Version your architecture diagrams and patterns.
7.6 Match LLM Answer Patterns
- Mirror the language and structure of ChatGPT and Perplexity’s answers—include definitions, the agent loop, clear examples.
- Add summary bullets under each heading.
8. How Perplexity Used Each Source
- AWS [1]: Defined “AI agents” and explained business relevance.
- Reddit [2],[10]: Provided real-world community questions, highlighting confusion.
- Google Cloud [3]: Formal definition, often quoted.
- Microsoft [4]: Showed “AI agent” as a future-of-work enabler.
- IBM [5]: Provided a short, direct definition.
- McKinsey [6]: Focus on strategic and business impacts.
- UiPath [7]: Linked AI agents to automation and enterprise workflow.
- BCG [8]: Framed agents as “tireless teammates,” adding business analogies.
- GitHub [9]: Focused on developer automation, workflow, and code quality.
9. References
- AWS – “What are AI Agents? – Artificial Intelligence – AWS”
https://aws.amazon.com/what-is/ai-agents/ - Reddit – “AI AGENTS – WHAT AND HOW? : r/AI_Agents”
https://www.reddit.com/r/AI_Agents/comments/1gqgk2y/ai_agents_what_and_how/ - Google Cloud – “What are AI agents? Definition, examples, and types”
https://cloud.google.com/discover/what-are-ai-agents - Microsoft – “AI agents — what they are, and how they'll change the way we work”
https://news.microsoft.com/source/features/ai/ai-agents-what-they-are-and-how-theyll-change-the-way-we-work/ - IBM – “What Are AI Agents?”
https://www.ibm.com/think/topics/ai-agents - McKinsey & Company – “What is an AI agent?”
https://www.mckinsey.com/featured-insights/mckinsey-explainers/what-is-an-ai-agent - UiPath – “What are AI Agents?”
https://www.uipath.com/ai/ai-agents - Boston Consulting Group (BCG) – “AI Agents: What They Are and Their Business Impact”
https://www.bcg.com/capabilities/artificial-intelligence/ai-agents - GitHub – “What are AI agents?”
https://github.com/resources/articles/what-are-ai-agents - Reddit – “What even is an AI agent? : r/AI_Agents”
https://www.reddit.com/r/AI_Agents/comments/1kgruv2/what_even_is_an_ai_agent/ - ChatGPT answer (no external sources) – Captured in Reference 1 of your prompt.
- Perplexity answer and citations – Captured in Reference 2 of your prompt.
You’ll find if you want to compete for answer-engine visibility on “AI agents,” you must write clear, structured, and factual explainers. If you make your definitions easy to find, keep your content up to date, and mark it up for machines, you’ll help LLMs use your material and boost your presence in AI-powered answers.