How Small Businesses Are Using AI Automation to Scale Smarter – Part 3

Pelle Sundin

Website | LinkedIn

I’d say summarizing information like transcripts with ChatGPT has been incredibly beneficial for me.

Dorota Mleczko

Website | Website | LinkedIn

Here’s a recent example that perfectly illustrates how AI literacy transforms “impossible” tasks:

Process Transformed:

Government research and localization for EU regulatory compliance

The Challenge:

A Polish government forestry official needed to research hundreds of Latin species names from EU directives and find their authentic Polish scientific names (not just translations) for official documentation. Manual research would have taken “a thousand years” as he put it.

The Solution:

Instead of basic translation, I used strategic AI research methodology: Perplexity Research mode with Academic sources only (crucial for verified scientific data) ChatGPT Deep Research with specific prompts targeting authoritative Polish scientific literature

The Result:

15 minutes instead of potentially weeks of manual academic research. But here’s the key – this wasn’t about the AI tools themselves, it was about AI literacy: understanding which tools to use, how to configure them properly, and how to structure research queries for complex, domain-specific challenges.

Bonus:

We also applied 2 follow-up steps (Claude Sonnet 4 and Gamma) to simplify complex forest management plans for public consultations – turning dense technical documents into accessible citizen-friendly slide deck presentations in minutes.

Bottom line:

Most professionals try AI once, get poor results, and give up. The difference between failure and breakthrough is fundamental AI literacy. Most businesses skip the AI Training step and jump straight to complex projects wasting time and money.

Uppugundla Sairam

Website | LinkedIn

We’ve modernized how we support students by integrating AI into our training ecosystem. We use ChatGPT to power a 24/7 virtual assistant that helps learners solve coding doubts, understand complex topics, and get real-time feedback on assignments. This has drastically reduced our support team’s workload and improved student satisfaction. What used to take hours like resolving common Python or Java errors, now happens instantly. It’s helped us scale personalized learning without scaling operational costs.

Himanshu Sharma

Website | LinkedIn

At UAE Startup Story, we’ve integrated AI to streamline the process of discovering, curating, and publishing stories about emerging startups. Using tools like ChatGPT and Claude, we’ve automated parts of our editorial research, interview prep, and content structuring—turning what used to take hours into minutes. This not only increases our publishing frequency but also helps us surface more under-the-radar founders and innovations across the UAE. AI hasn’t replaced storytelling—it’s simply made the process smarter, faster, and more scalable.

Metehan Yeşilyurt

LinkedIn

Internal Linking for SEO at Scale

How AI Made It Efficient: Managing internal linking across hundreds of blog posts was time-consuming and inconsistent. I developed a custom WordPress plugin with Cursor that uses the OpenAI GPT-4o API to analyze the context of existing articles and automatically suggest or insert relevant internal links based on semantic similarity. This significantly improved crawl depth, reduced orphan pages, and enhanced topical authority, all while cutting manual workload by over 80%.

Tool Used:

OpenAI API (ChatGPT 4o) + Custom WordPress Plugin

Kayla Williams

Website | LinkedIn

One business process I’ve streamlined using AI, though it’s not one you hear about often, is writing RFP responses. These proposals used to eat up hours of my time. Each one required carefully pulling together past work, technical language, and detailed formatting. It felt like reinventing the wheel every time. Now? I use a combination of ChatGPT and a Notion database where I’ve stored past responses, useful phrases, and industry-specific info. When a new RFP comes in, I copy the key requirements into ChatGPT and reference content from my Notion library. The AI helps me sketch out a rough draft that’s surprisingly close to done. I still go through and tweak it, of course, but I’ve cut the time from 8+ hours down to about 2 or 3. It’s not flashy, but it’s made a huge difference. And it’s a reminder that AI isn’t just for the big-picture stuff, it can seriously help with the day-to-day grunt work, too.

Exact RFP Workflow (Now with AI in the Loop)

1. Intake & Initial Review

As soon as an RFP comes in:

• I skim for scope, deadlines, eligibility, and submission requirements.
• I tag it in Notion under a template titled “RFP Intake” with basic info (client name, due date, type of services, file link, etc.).
• If it’s a repeat type (HR services, consulting, AI training), I already know which past proposals I can reuse or pull from.

2. Create a “RFP Snapshot”

I write a quick summary of the RFP in plain language, such as who it’s for, what they want, and what they care about. I’ve trained myself to write this as if I were explaining it to a colleague who’s never seen it (it’s important to practice prompt engineering and to even ask your AI tools “Ask me questions that may help because xxx is my goal”) This goes into ChatGPT as the starting input, with a prompt like: “You’re helping me draft a response to an RFP. Here’s the summary: [insert snapshot]. I’ll provide past proposal content next. Please wait to respond.” This helps the AI understand context before we go deeper.

3. Pull Relevant Content

I go into Notion where I store:

• Past proposals organized by service type
• Paragraphs I’ve written for team bios, approach to work, DEI, etc.
• Common attachments (insurance docs, company overviews, etc.)

I paste selected chunks into ChatGPT and say: “Here are reusable content blocks I’ve used in similar proposals. Use the same tone and format where possible in this draft.”

4. Generate a First Draft

Once ChatGPT has enough background, I give it a final prompt like: “Based on the RFP summary and the materials above, write a response to the following section: [e.g., ‘Company Background’ or ‘Methodology for Execution’]. Keep it specific, professional, and in first-person plural (we/our). Don’t overhype, just clear and confident.” I do this section by section. That way, I can edit in real-time. No one should ever just copy and paste answers from Chat. It needs the human eye and revision.

5. Edit & Polish

This is where my brain takes over:

• I fact-check every stat or claim
• I smooth out overly generic phrasing
• I insert client-specific examples, case studies, or testimonials if I have them
• I review formatting requirements (fonts, file types, etc.)

Sometimes I’ll drop the full draft into Claude if it’s a longer proposal and I want to restructure or tighten wording.

6. Final Touches

• Proof in my Google Docs
• Cross-check the RFP for formatting/submission rules
• Package attachments (W9s, insurance certs, resumes, etc.)
• Submit via email or portal

Prompts & Templates I Reuse Often

Here are a few I copy-paste often: For company overviews: “Write a 2-paragraph company overview for a proposal. We’re a consulting firm focused on [insert], with a mix of strategy, training, and implementation services. Professional tone, no fluff.” For methodology: “Draft a response for ‘Methodology and Approach.’ The RFP is for [service]. Here’s our typical process: [bullet list]. Expand this into 2-3 paragraphs that sound client-ready.” For bios: “Turn this bio into a polished 1-paragraph summary for a proposal. Include title, specialties, and relevant past experience.”

The Most Frustrating RFP I Ever Handled (Pre-AI)

I still think about this one…It was a government RFP with a 70-page spec. The formatting rules alone were insane: line spacing, font, labeled tabs, signed forms, digital signatures that couldn’t be typed, 15 attachments, and it was due in 3 business days. The part that drove me nuts? The “Experience with Similar Clients” section had a strict word count and wanted proof of impact with metrics, client names (with permission), and references… but we weren’t allowed to contact them during the review period. It felt like threading a needle underwater.

What I Enjoy Now

Now, I actually like the challenge of tailoring proposals. AI clears the clutter so I can focus on strategy and storytelling. I love:

• Crafting a narrative that shows we get the client
• Dropping in little credibility nuggets (awards, quotes, data)
• Seeing the whole proposal with my thoughts, goals, etc. all brought together easily and cohesively.

The proposal is still me with my information and voice, the tools make it so I can be more organized and thoughtful in my approaches. I still take pride in the final draft, but now it feels like creating, not just surviving.

Cyrus Shepard

Website | LinkedIn

Creating content briefs for clients is a significant part of my consultancy, and AI has significantly enhanced this process by better analyzing user intents and topic coverage. I particularly like the AI Content Helper by Ahrefs, which, while not perfect, raises the bar for content optimization tools.

Andy Crestodina

Website | LinkedIn

I use AI to build a persona, then I give it full page screenshots of the key conversion pages and ask what’s missing from the visitor’s point of view. This kind of gap analysis is often very very insightful. And here’s a video showing the method. I hope this is helpful!

Nikita Andriievskyi

Website | X

Definitely the fulfillment process . We use n8n, airtable, gpt, Claude, Gemini, etc. Here are 5 automation ideas most businesses STILL haven’t implemented:

• Stage Tracking: know exactly where projects slow down
• Auto Reporting: weekly summaries without touching a spreadsheet
• Onboarding: quick & consistent onboarding matters
• Draft Fulfillment: AI generates first drafts of posts, designs, emails, etc.
• Internal Notifications: make your team aware of progress and upcoming deadlines

None of this is complicated. But when implemented right, it adds hours of focus time back every week.

Sivanandan (Shiva) N

Website | LinkedIn

For us at Shaynly, while we leverage AI across many marketing facets, the single most transformative business process we’ve made profoundly efficient with AI is the rapid conceptualization and initial foundational build-out for launching a brand completely from scratch. Before AI, the journey of brand creation – from market research and niche identification to defining brand identity, generating initial content frameworks, and developing core messaging – was a heavily manual, iterative, and time-intensive endeavor. It often involved multiple specialists and took months to reach a viable launch point. The tool we’ve used most effectively for this is a custom-integrated AI Brand Blueprinting System. This system combines advanced large language models (LLMs) with sophisticated data analytics and generative AI for design, allowing us to accelerate the core brand definition phases dramatically.

Here’s how it works:

Our AI system rapidly processes vast datasets to identify market gaps, analyze competitor strategies, and pinpoint target audience demographics and psychographics. Based on these insights, it can then:

• Generate brand name and slogan options with domain availability checks.
• Draft initial value propositions and core messaging frameworks.
• Suggest comprehensive tone-of-voice guidelines.
• Propose visual identity elements like color palettes and typography, even generating initial logo concepts and visual assets.
• Outline initial website structures and core content briefs (e.g., for homepages, about us, service pages), all pre-optimized for SEO.

This doesn’t replace the critical human strategic oversight or creative refinement, but it acts as an incredibly powerful accelerator. It allows our brand strategists and designers to move from concept to a robust, AI-generated foundational brand blueprint in a fraction of the traditional time. They can then focus their expertise on adding unique human insight, emotional depth, and intricate design details that truly make the brand distinctive, rather than spending weeks on preliminary ideation. This efficiency has not only allowed us to experiment with and launch new brand concepts much faster but also enables us to demonstrate to clients how AI can significantly de-risk and speed up their own ventures into new markets. It fundamentally changes the timeline and resources needed for initial brand incubation, making it an incredibly powerful application of AI in marketing.

Ronnie Parsons

Website | LinkedIn

I run 3 solo-led businesses. Here are the exact AI tools I use daily. (And how they keep me sane and profitable) Because here’s the truth: Most people are drowning in AI tools, but nothing connects or actually saves time. Here’s what actually works for me: Tool: Claude What I use it for:

• Analyze sales calls automatically
• Extract pain points, objections, buying signals
• Summarize conversations

How it fits into my system: It’s part of my Client Intelligence Loop: a system that turns raw conversations into structured insights and faster follow-ups. Tool: ClickUp What I use it for.

Adriana Tica

Website | LinkedIn

I saw the best ROI from using AI for voice-of-customer reframing. Here’s how it works: you feed real audience language into AI to rework hooks, headlines, or posts using actual customer phrasing. Why: It keeps your messaging grounded in what your people actually say, not what marketers think sounds good. These days, I mostly use Convertly Lab, my custom GPT, to make sure that all my content is aligned with actual pain points my audience experiences.