While headlines focus on enterprise AI breakthroughs, small businesses are quietly navigating their revolution and hitting familiar roadblocks. According to ServiceDirect’s 2025 Small Business AI Report, 62% of non-adopters cite a lack of understanding about AI’s benefits, while 60% point to limited in-house resources as the main barriers. Even among those adopting AI, 72% struggle with integration and day-to-day usage.
This gap between curiosity and execution reflects a deeper issue: small business owners are interested in AI but often overwhelmed by its complexity. To explore how they can move from hesitation to confident implementation, Hackernoon turned to AI adoption expert Katerina Andreeva.
Katerina is a data strategist with over a decade of experience and the founder of The Brained Inc., an EdTech startup that helps small businesses apply AI effectively. She also serves on the Executive Board of net4tec, the leading network for women in the STEM environment, and brings a unique interdisciplinary perspective as a coach and neurointegration trainer. Through dozens of customer development interviews and hands-on collaborations with entrepreneurs, she has uncovered the reasons adoption fails and the use cases that work.
This article explores why so many founders struggle with AI, highlights four practical and affordable workflows that drive real results, and explains why education is the missing link in making AI work for small businesses.
Three Gaps Holding Founders Back
Across more than 30 in-depth interviews, Katerina Andreeva set out to understand how founders and solo professionals actually approach AI in their daily routines. Participants included coaches juggling client sessions, consultants balancing delivery with sales, and business owners managing lean teams with little technical support. Each received a practical AI use case mapped to their business workflow in return for their time.
Most had already experimented with ChatGPT. They asked it to write emails, summarize articles, and brainstorm content. But beyond that first layer, Patterns began to emerge.
The first gap was prompt engineering—or rather, the lack of a structured approach. Founders described unpredictable results, frustration, and wasted time. The second was tool visibility. Aside from ChatGPT, few could name another platform. Automation tools, search optimization models, and audio processors—these weren’t even on their radar. The third was application mapping. Even those excited about AI struggled to tie it to their workflows. Ideas floated, but didn’t anchor to anything repeatable.
“The interviews spanned professionals from multiple segments, including neurointegration coaches, psychologists, solo consultants, small business founders, and executives managing operations at companies with annual revenues in the hundreds of millions,” says Katerina. “They all had motivation and curiosity. What they lacked was clarity.”
Operational Use Cases and Technical Configurations
After identifying consistent capability gaps during the interview phase, Katerina Andreeva developed a set of AI-enabled workflows tailored to participants’ operational models. Each solution was designed to be lightweight, secure, and executable without technical teams or vendor dependencies.
Katerina notes: “Every proposed setup had to meet three criteria: the solution had to be replicable, maintainable without external developers, and linked to a measurable business function. If they can’t apply it without hiring someone else, it’s not a real solution.”
Coaches and neuro integration specialists often spend 90 to 120 minutes preparing summaries, interpreting assessments, and drafting personalized proposals after each session. Katerina Andreeva developed an automated workflow combining transcription tools (such as Fireflies) with structured ChatGPT templates to streamline this process. The system generates a complete session summary and commercial proposal in under 15 minutes, significantly reducing manual workload.
- Large-Scale Call and Meeting Summarization
For larger teams to automate meeting summaries, Katerina proposed an advanced configuration to analyze sales call recordings at scale. Instead of manually reviewing 10 out of 100 calls, companies can now process 100% of recorded conversations to identify behavioral patterns, performance gaps, and growth opportunities. One business with approximately $300 million in annual revenue has already begun implementing this system.
- Automated LinkedIn Outreach for B2B Founders
Ms. Andreeva introduced a LinkedIn-based cold outreach automation workflow for business owners without a dedicated sales staff. The configuration allowed users to scale lead generation without hiring additional team members by automating personalized messaging sequences. In a recent case, she advised a B2B founder whose LinkedIn channel had been underutilized. Within one month, the business recorded a 30% increase in new leads entering the sales pipeline. A similar system is currently being implemented at net4tec, a nonprofit organization where Katerina volunteers. Operating under strict budget constraints, the team was able to deploy the outreach system using cost-effective AI tools.
- AI-Augmented Content Creation
AI-augmented content creation proved relevant to nearly all participants. Ms. Andreeva introduced a structured approach for generative AI to support the full content lifecycle—from idea generation to drafting and refinement.
“The method was applied to multiple formats, including social media posts, email campaigns, and blog articles. While technically accessible, the workflow emphasized consistency and template-based execution to ensure scalable output across channels,” says Katerina.
Enabling Independence Through AI Literacy
While AI tools continue to expand in number and capability, tool access alone does not lead to effective adoption. Across all interview segments, Ms. Andreeva observed that even well-resourced business owners often paused implementation due to uncertainty about how to apply them systematically.
“The goal is to design clear, repeatable systems that founders can operate and improve without external support,” Katerina shares. “When a tool fits into a well-defined workflow, it becomes part of how the business runs. Without that connection, most tools lose relevance once the novelty fades. Education turns short-term results into long-term capability.”
This principle forms the foundation of her EdTech platform, which is focused on practical AI literacy for small businesses. The same logic informs her volunteer work with net4tec, where automation systems are built with minimal resources and maximum transparency, enabling long-term ownership by internal teams.
Thus, effective AI adoption in small businesses depends less on access to tools and more on structured integration, applied context, and internal capability. Systems that align with daily operations—whether in sales, content, or client management—deliver measurable outcomes only when owners understand how to sustain them. As Katerina Andreeva says, “AI becomes a resource when it supports real business processes with clarity and consistency.”
