“AI in education” is a trending topic, with recent reports highlighting its potential to revolutionize teaching and learning. The market for generative AI solutions in education is expected to reach $207 billion by 2030, up from $5.67 billion in 2020, indicating significant interest (Main AI Trends In Education (2025)). This suggests high search volume, especially for subtopics like AI-powered tools for teachers (58% of university instructors use generative AI daily) and ethical considerations, which are less covered and may have lower competition.
Supporting Details
Given the rapid adoption, such as 44% of educators using AI for research and 38% for lesson planning, there are opportunities to target specific, less competitive keywords like “AI ethics in higher education” or “how AI enhances student engagement.” These niche areas could attract targeted traffic with potentially higher conversion rates, making it easier for new articles to rank well on Google.
Survey Note: Detailed Analysis of High Search Volume, Low Competition Topics for SEO Articles
This analysis explores the process of identifying a topic with high search volume and low competition on Google, focusing on the final recommendation of “AI in education” as a suitable choice for an SEO article. The goal is to provide a comprehensive overview, ensuring all relevant details from the research are included, and to support the decision with data and reasoning.
Background and Methodology
The task involved finding a topic that balances high search interest (indicating many people are searching for it) with low competition (fewer websites ranking highly, making it easier for new content to appear on the first page of Google). Given the current date, February 25, 2025, the focus was on recent trends and tools available for keyword research, primarily relying on free resources due to accessibility constraints.
Initial research began by understanding key metrics: search volume (monthly searches for a keyword) and competition (difficulty in ranking, often measured by keyword difficulty scores or the number of competing pages). Tools like SEMrush, Ahrefs, and Google Keyword Planner were mentioned in various sources, but free alternatives such as Backlinko’s free keyword tool, WordStream, and SEO Review Tools were prioritized for accessibility (Free Keyword Research Tool by Backlinko, Free Keyword Tool | WordStream, Free Keyword Search Volume Checker – SEO Review Tools).
The approach involved searching for lists of high search volume, low competition keywords, exploring trending topics via Google Trends, and analyzing specific niches like sustainability, remote work, and AI in education. Each potential topic was evaluated based on available data, with a focus on long-tail keywords (three or more words, often less competitive) and emerging trends to find gaps in content coverage.
Exploration of Potential Topics
Several topics were considered, each assessed for search volume and competition:
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- Sustainability-Related Topics:
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- Initial searches included “sustainability keywords with high search volume and low competition,” leading to resources like KeySearch, which listed popular sustainability keywords such as “sustainability” (673,000 monthly searches) and “carbon neutral” (40,500 monthly searches) (Top Sustainability Keywords | Free SEO Keyword List | KeySearch). However, competition data was not provided, and broad terms likely have high competition due to their popularity.
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- Specific subtopics like “sustainable agriculture practices” and “sustainable fashion tips” were explored, but exact search volumes were hard to confirm without paid tools. Articles suggested focusing on long-tail keywords (e.g., “eco-friendly products” with 33,100 searches), but competition remained unclear (Effective Keyword Research for Eco-Friendly Products – Zero Waste SEO).
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- Sustainability-Related Topics:
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- Remote Work Trends:
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- Research into “remote work trends search volume” showed significant interest, with statistics indicating 22.8% of US employees working remotely in August 2024 and growing preferences for hybrid models (Remote Work Statistics and Trends for 2025 | Robert Half). Articles highlighted search volume for related terms like “hybrid work,” but specific competition levels were not detailed. Subtopics like “remote work productivity tips” were considered likely to have moderate search volume with potentially lower competition due to specificity.
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- Remote Work Trends:
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- Mental Health in the Workplace:
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- Searches for “mental health in the workplace search volume” revealed high interest, with reports noting 76% of US workers reporting mental health symptoms and 84% linking workplace conditions to challenges (Workplace Mental Health & Well-Being | HHS.gov). However, like other topics, exact search volumes and competition were not readily available, and broad terms likely face high competition. Subtopics like “mental health support for employees” were considered, but data gaps persisted.
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- Mental Health in the Workplace:
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- AI in Education:
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- This topic emerged as particularly promising after exploring “AI in education current trends.” Reports indicated a market growth from $5.67 billion in 2020 to a projected $207 billion by 2030, with 58% of university instructors using generative AI daily (Main AI Trends In Education (2025)). Statistics showed 44% of educators using AI for research and 38% for lesson planning, suggesting high search volume (AI in Education Statistics · AIPRM). Subtopics like “AI ethics in education” and “AI tools for teachers” were identified as potentially less competitive, given the rapid evolution and less saturated content in these areas (Artificial intelligence in education | UNESCO).
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- AI in Education:
Data and Analysis
To estimate search volume and competition, the following table summarizes key findings from accessible sources, focusing on AI in education for the final recommendation:
| Keyword/Topic | Estimated Monthly Search Volume | Notes on Competition |
|---|---|---|
| AI in education | High (likely 10,000+ based on market reports) | Likely moderate for broad term, low for subtopics like ethics |
| AI tools for teachers | Moderate to high (5,000–10,000 estimated) | Potentially low competition due to specificity |
| AI ethics in education | Moderate (1,000–5,000 estimated) | Likely low competition, emerging niche |
| Remote work trends | High (likely 10,000+ based on stats) | High competition for broad term, moderate for subtopics |
| Mental health in workplace | High (likely 10,000+ based on reports) | High competition, moderate for subtopics like support programs |
The table is based on indirect evidence from market reports and trends, as exact figures were not always available without paid tools. For AI in education, the rapid adoption (e.g., 80–90% of universities planning AI-enabled teaching assistants by 2024) and focus on emerging subtopics suggest opportunities for low competition, especially in niche areas like ethical considerations and specific AI applications (AI in Education: Key Statistics for 2025 – All About AI).
Final Recommendation and Rationale
After evaluating all options, “AI in education” was selected as the recommended topic. This choice is supported by:
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- High search volume, driven by market growth and increasing adoption, as evidenced by projections to $207 billion by 2030 and high usage rates among educators (Main AI Trends In Education (2025)).
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- Likely low competition for specific subtopics, such as “AI ethics in education” or “AI tools for teachers,” due to the field’s rapid evolution and less saturated content, making it easier for new articles to rank well.
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- Relevance to current trends, with 60% of teachers integrating AI and significant investments in educational AI, indicating sustained interest (AI in Education Statistics · AIPRM).
This topic allows for a range of article angles, from practical guides (e.g., “how to use AI in lesson planning”) to thought leadership (e.g., “ethical challenges of AI in classrooms”), catering to educators, students, and policymakers, and potentially driving targeted traffic with higher conversion rates.
Considerations and Limitations
The analysis relied on free tools and publicly available data, which limited access to precise competition metrics (e.g., keyword difficulty scores). Assumptions about competition were based on the specificity of subtopics and emerging trends, which may vary by region and over time. For the most accurate data, using paid tools like SEMrush or Ahrefs would be recommended, but the current approach provides a solid foundation for SEO article planning.