How to Use Blogging to Get Found in AI Search
Guest post by Michelle Eshkeri, professional services copywriter at Let ME Write
My blogging client Robert, an accountant at Green & Peter, told me a few days ago that he’s getting lots of enquiries through AI search now. We’re witnessing a fundamental shift in how people search for businesses and suppliers. Instead of typing ‘accountant North London’ into Google or Bing and scrolling through pages of results, they’re asking ChatGPT, Claude, or Perplexity: ‘Find me an accountant in North London who specialises in creative businesses.’ The AI results recommend specific firms based on the content it has analysed across the web.
This shift isn’t coming next month or next year; it’s already here. For businesses who’ve relied on traditional SEO for traffic, this represents both a massive opportunity and a potential threat.
In this guide, I’ll show you exactly how to optimise your blogging strategy so when someone asks an AI tool to recommend a professional in your field, your name pops up as the first obvious choice.
Understanding AI search vs traditional search
How traditional SEO works
Traditional search engine optimisation has been the foundation of digital marketing for years. You research keywords, optimise your content around those specific terms, build backlinks, and hope to appear on the first page of Google search engine results (also known as SERP). Success is measured by rankings or where you appear when someone searches for ‘mortgage broker Manchester’ or ‘tax accountant small business.’
The SEO game has always been about matching keywords and pleasing the algorithm overlords. You’d write content targeting “best pension advice” or ‘self-employed tax tips’, ensuring these phrases appeared in your headings, meta descriptions, and throughout your text. Google would crawl your pages, assess their relevance and authority, and slot you into position 3, 7, or hopefully 1 for your target terms. Job done.
How AI search optimisation works differently
AI search operates on different principles. When someone asks ChatGPT ‘Who should I speak to about pension planning for freelancers?’, the AI doesn’t just match keywords. Instead, it collates and synthesises information from across the web, considering context, expertise, and relevance before making a recommendation.
The AI evaluates the depth of your knowledge, the specificity of your expertise, and how well you’ve demonstrated your ability to solve similar problems. It looks for evidence of real-world experience, client success stories, testimonials and comprehensive understanding of the subject matter.
Rather than presenting a list of links for users to evaluate themselves, AI tools provide direct recommendations with explanations.
Why this matters for your business
This shift changes everything about how potential clients discover and evaluate potential suppliers. AI search users aren’t browsing through multiple websites to compare options anymore. In some cases, they aren’t even clicking through to your website at all. They’re getting curated recommendations from a tool they feel they can trust. When an AI recommends your firm, it brings context and built-in credibility (rightly or wrongly, depending on your viewpoint).
And more importantly, these users are typically further along in their decision-making process. They’re looking for specific solutions to identified problems – in other words they are bottom of the marketing funnel and much closer to that all-important buying decision. This means higher conversion rates and more qualified enquiries -exactly what Robert has been experiencing with his accountancy practice.
The foundation of what AI tools look for
Authority and expertise signals
As I mentioned before, AI tools evaluate the depth and authenticity of your expertise rather than simply scanning for keywords. This means you need to be consistently publishing in-depth content that covers your specialist area comprehensively. When I optimise blogs for clients, I ensure they demonstrate real-world experience through specific examples, client case studies (anonymised, of course), and detailed explanations that only someone with genuine expertise could provide.
For instance, rather than writing a generic ‘pension planning tips’ post, a financial advisor should share insights from actual client scenarios: ‘Recently, I helped a 45-year-old freelance graphic designer who’d never paid into a pension. Here’s the strategy we developed…’ This kind of content signals to AI tools that you’re sharing genuine professional experience rather than simply regurgitating generic tips.
Context and relevance
AI tools are top notch at understanding context. They recognise when your content addresses specific niches, locations, or situations. If you’re a mortgage broker in Manchester specialising in first-time buyers, your content should reflect this specificity. Write about local market conditions, amenities and communities, reference local estate agents you work with, and address the particular challenges Manchester first-time buyers face.
The AI understands that someone asking ‘find me a mortgage broker who understands the Manchester property market’ needs location-specific expertise, not generic mortgage advice.
Fresh, current information
AI tools prefer recent, up-to-date content because they’re designed to provide current information. So, it’s even more important now to regularly update existing content with fresh examples, recent regulatory changes, and current market conditions. A blog about corporation tax rates written in 2022 needs updating for 2025 changes to remain valuable to AI search algorithms.
Content strategies that work for AI search
Write for conversational queries
People don’t type ‘mortgage broker services Manchester’ into ChatGPT like they would with Google. Instead, they’re having a conversation with the AI, asking, ‘Who’s the best mortgage broker in Manchester for someone with a low deposit?’ Your content needs to address these natural, conversational queries. Instead of optimising for ‘pension advice,’ write content that answers ‘How much should I be putting into my pension at age 35?’
Start by listing the actual questions your clients ask during consultations. These real-world queries are exactly what people are asking AI tools. Transform each question into comprehensive content that provides thorough answers.
Create comprehensive, authoritative content
AI tools prefer depth over breadth. Rather than writing ten 300-word posts about different aspects of tax planning, create one comprehensive 2,000-word guide that covers everything a small business owner needs to know about tax planning. Include multiple scenarios, address common misconceptions, and provide step-by-step guidance.
This approach serves two purposes: it demonstrates your expertise more effectively, and it gives AI tools substantial content to analyse and cite. When someone asks for tax advice, the AI can recommend your comprehensive guide with confidence.
Focus on problem-solution content
Structure your content around specific client problems and detailed solutions. Write about ‘How I helped a contractor avoid IR35 issues when their client wanted to extend their contract.’ Include the problem, your approach, the solution, and the outcome.
This format works because AI tools are trying to match user problems with proven solutions. When you demonstrate that you’ve successfully solved similar problems, you become the obvious recommendation.
Use the ‘Query Fan-Out’ strategy
When someone asks an AI tool ‘Should I remortgage?’, the AI breaks the query into related sub-questions: ‘What are current interest rates?’ ‘What are the costs involved?’ ‘How do I know if it’s the right time?’ ‘What documents will I need?’ You’ve probably noticed that AI is always looking to continue the conversation with you.
Create content clusters that address every angle of your core topics. This comprehensive coverage increases your chances of being recommended regardless of how someone phrases their query.
Demonstrate local expertise
AI tools understand geographical relevance too. If you’re an estate agent based in Edinburgh, include content about Scottish property law differences, local market trends, and region-specific considerations. Reference local landmarks, business districts, and community issues that resonate with your target audience.
This local specificity helps AI tools recommend you for location-based queries while also building trust with potential clients who recognise your genuine understanding of their area.
Technical optimisation for AI search
Content structures AI understands
AI tools process information more effectively when it’s clearly structured. Use descriptive headings that summarise each section’s content. Instead of ‘Section 1’ or ‘Part A,’ use ‘Understanding Buy-To-Let Mortgage Requirements’ or ‘How to Calculate Rental Yield.’ These headings helps AI tools understand your content’s hierarchy and purpose.
Break up long paragraphs with bullet points and numbered lists for key information. Create bite-sized summaries that AI can easily cite in its answers to user questions. When explaining a process, use step-by-step formatting. AI tools often extract this structured information directly when providing recommendations and can show up in Google AI summaries too.
The importance of context
Never assume knowledge. Explain industry acronyms (BTL means Buy-to-Let), provide background information, and connect concepts clearly. AI tools need this context to understand when your content is relevant. If you mention ‘stamp duty changes,’ explain what stamp duty is and how the changes affect different buyer categories.
This approach also improves user experience. Someone asking an AI tool for financial advice may not be familiar with industry terminology.
Building brand mentions and authority
Why brand mentions matter more than backlinks
Traditional SEO focused heavily on getting other websites to link to yours. AI search operates differently, so it looks for contextual mentions of your brand across the web. When industry publications mention your expertise, when clients reference your services in forums, or when colleagues cite your insights, AI tools interpret these as authority signals.
Quality matters more than quantity. One mention in a respected industry publication carries more weight than dozens of generic directory listings. AI tools evaluate the context surrounding your brand mentions. They are looking to see if you’re being referenced as an expert, a solution provider, or a trusted advisor.
Strategies for building mentions
Getting brand mentions can be challenging though. Focus on thought leadership activities that naturally generate brand mentions. Write guest articles for industry publications, speak at professional events, and participate in industry panels. Collaborate with complementary professionals. For example, accountants can partner with financial advisors, mortgage brokers can work with estate agents.
Build relationships with trade journalists and industry bloggers. When they write about market trends or regulatory changes, you want to be the expert they quote. Offer insights for industry surveys and research reports as these often generate multiple mentions across various platforms.
Measuring success in AI search
Tracking AI-generated traffic
Identifying AI-driven traffic requires looking beyond traditional referral sources. Monitor direct traffic increases because people who’ve been recommended by AI tools often visit your website directly. Look for visitors who land on specific service pages rather than your homepage, as AI tools often recommend specific content.
Key metrics to watch
Focus on lead quality rather than just quantity. AI-recommended prospects typically arrive with a clearer understanding of their needs and your expertise. They are more ready to buy. Track conversion rates from initial enquiry to consultation, and from consultation to client.
Monitor the specificity of incoming enquiries. AI-recommended leads often reference particular services or expertise areas, indicating they’ve received targeted recommendations rather than generic suggestions.
Your AI search blogging plan
Start with one comprehensive piece of content that demonstrates your expertise in your core service area. Make it thorough, specific, and genuinely helpful. Then build systematically, creating content clusters that address every aspect of your specialty.
Remember, this is about genuinely demonstrating your expertise in a way that AI tools can understand and recommend. The same content that works for AI search also builds trust with human prospects and establishes your authority in your field, so it can also work well for traditional SEO where Google is looking for Expertise, Experience, Authority and Trust (E-E-A-T).
Ready to start optimising your content for AI search? My AI-assisted content packages help professional services businesses, especially those in finance, create the comprehensive, authoritative content that AI tools recommend.
Frequently Asked Questions
Q: How long does it take to see results from AI search optimisation? A: Unlike traditional SEO which can take 3-6 months, AI search optimisation often shows results more quickly. I’ve seen clients like Robert getting AI-generated enquiries within 4-6 weeks of publishing comprehensive, expert content. However, building consistent authority takes 3-4 months of regular, high-quality content publication.
Q: Do I need to stop doing traditional SEO if I’m optimising for AI search? A: Absolutely not. AI search optimisation builds upon good SEO foundations. The same comprehensive, expert content that AI tools recommend also ranks well in traditional search engines. Think of AI optimisation as an enhancement to, not a replacement for, your existing SEO strategy.
Q: What’s the difference between AI search optimisation and regular content marketing? A: AI search optimisation requires deeper, more comprehensive content that demonstrates genuine expertise through real examples and case studies. While traditional content marketing might focus on keywords and search volume, AI optimisation prioritises authority, context, and problem-solving depth that AI tools can confidently recommend.
Q: How do I know if my content is working for AI search? A: Monitor direct traffic increases, branded search growth, and the quality of enquiries you receive. Prospects who find you through AI search often arrive with specific questions and a clearer understanding of your expertise. Track how enquiries reference your specific services or knowledge areas mentioned in your content.
Q: Can small businesses compete with larger companies in AI search? A: Yes, and often more effectively. AI tools favour specific expertise over company size. A small firm that consistently demonstrates deep knowledge in a particular niche can outperform larger generalist firms in AI recommendations for their specialty area.
Q: Should I write about the same topics my competitors are covering? A: Write about the same broad topics but from your unique perspective and with your specific expertise. If competitors write generically about ‘pension planning’, you might focus on ‘pension planning for creative freelancers’ or share detailed case studies that only you could write based on your client experience.
Q: How often should I publish content for AI search optimisation? A: Consistency matters more than frequency. Publishing one comprehensive, expert piece monthly is better than several shallow posts weekly. Focus on creating substantial content (1,000+ words) that thoroughly addresses client problems and demonstrates your expertise through real examples and detailed solutions.
Michelle Eshkeri is a content and copywriter specialising in financial services, with 23 years of finance industry experience including 18 years at GSK plc. She helps accountants, financial advisors, and mortgage brokers create AI-optimised content that gets recommended by ChatGPT, Claude, and other AI tools, combining traditional expertise with cutting-edge AI-assisted content strategies.