Selling Shovels in the AI Gold Rush

There is a famous story from the California Gold Rush of 1849. While thousands of prospectors rushed west to pan for gold, the people who made the most reliable fortunes were the ones selling picks, shovels, and denim jeans. Levi Strauss did not dig for gold. He outfitted the people who did.

I run a small AI consulting company. When I first described what I do to a friend, he smiled and said: “So you are selling shovels in the gold rush.”

He meant it as a compliment. And on the surface, the analogy works. AI is the gold. Companies are rushing to find it. I help them get equipped. But the more I thought about it, the more I realized the analogy breaks down in one important way, and that difference is exactly why my work matters.

The Shovel Seller Did Not Care If You Found Gold

The original shovel sellers of 1849 had a clean transaction. You paid for the shovel, they wished you luck, and that was it. Whether you struck gold or went broke was not their problem. Their business model was indifferent to your outcome.

That is not what I do. And it is not what any honest AI consultant should do.

My mission is to help my clients take advantage of the opportunities created by AI technology. If they do not find their gold, I have not done my job. The transaction does not end when the workshop is over or the invoice is paid. It ends when the client’s team is actually using AI in a way that saves them time, money, or competitive ground.

This distinction matters because it changes everything about how the work is structured. A shovel seller optimizes for volume. A guide optimizes for outcomes.

The Real Barriers Are Not Technical

When I started Kunke Consulting, I assumed the main obstacle for companies would be technical. I thought they would need help choosing the right tools, configuring APIs, building workflows. And yes, that is part of it.

But after working with law firms, marketing agencies, architects, medical clinics, and manufacturing companies across Poland, I have learned that the technical gap is usually the smallest one. The real barriers are four others that rarely get discussed.

The skill gap is the one everyone talks about. People do not know how to write effective prompts, how to verify AI outputs, or how to integrate AI into their existing workflows. This is real, and training addresses it directly. But it is only one piece.

The knowing-what-is-possible gap is bigger than most people realize. The majority of professionals I work with have tried ChatGPT once or twice for something basic, maybe drafting an email or summarizing a document. They have no idea that AI can help them analyze contracts, build financial models in excel, generate market research that goes for a long time, automate repetitive reporting, or prototype ideas in minutes. They do not lack access to the technology, yet they lack imagination about what it can do for their specific work. This is the inspiration gap.

The inspiration gap is closely related but distinct. Even when people know AI can do something, they often cannot picture how it fits into their Tuesday morning. They need to see it applied to their industry, their documents, their problems. Abstract capability demonstrations do not stick. What sticks is watching AI draft a response to the exact type of client email they deal with every day, using their company’s tone, in their language.

The legal and compliance gap is increasingly urgent and widely underestimated. Since February 2025 (6 days ago at the time of writing), the EU AI Act requires companies to ensure AI literacy among their employees. GDPR has always applied to how company data flows through AI tools, but most SMEs have no internal policy governing AI use. Their employees are already using ChatGPT, Claude, Gemini, and Copilot, often with client data, often without any guidelines. This is not a hypothetical risk. It is happening right now in most offices across Europe, and this is why the legal and compliance work done by Justyna Surwiło-Rutkowska is so important.

Every Technology Revolution Created the Same Pattern

This is not the first time a transformative technology arrived and the biggest challenge turned out to be adoption, not invention.

When electricity became available to factories in the early 1900s, the technology existed for years before most manufacturers figured out how to use it properly. The first factories simply replaced their central steam engines with central electric motors and kept the same floor layouts, the same belt-driven systems, the same workflows. They got modest efficiency gains at best. It took a generation of industrial engineers and consultants to help factories realize that electricity allowed completely different factory designs, with machines placed according to workflow logic rather than proximity to a power source. The real productivity revolution came not from the technology itself but from reimagining work around it.

The same pattern repeated with personal computers in the 1980s, with the internet in the late 1990s, and with cloud computing in the 2010s (I’m old enough to remember some of it, and I can imagine the rest). In every case, the companies that gained lasting advantage were not the ones who adopted first. They were the ones who adopted well, with proper training, clear legal strategy, and someone helping them see possibilities they could not see on their own.

AI is following this pattern precisely. The technology is available to almost everyone. The tools are increasingly affordable and accessible. ChatGPT has close to a billion users, Gemini too. The competitive advantage does not come from having access to AI. It comes from knowing how to use it in ways that genuinely transform how your business operates.

Where I See My Value

Given all of this, my role as a consultant is not to sell shovels and forget about my clients. It is closer to being a guide who has already mapped parts of the territory.

I help close the skill gap through hands-on workshops where teams work with AI on their actual business problems. I help close the knowing-what-is-possible gap by bringing examples, case studies, and live demonstrations tailored to each client’s industry. I help close the inspiration gap by showing professionals how AI fits into the work they already do, in their language, with their documents. And I help close the legal and compliance gap by working with legal experts to ensure that AI adoption does not create regulatory exposure.

This combination of practical training, industry-specific insight, regulatory awareness, and implementation support is what SMEs (and bigger companies) actually need. They do not need another tool. They need someone who can help them use the tools they already have access to.

A Lasting Advantage for Companies Who Move Now

I am optimistic about AI. Not in the breathless, “this changes everything overnight” way that dominates LinkedIn, but in the grounded sense that this technology genuinely creates new opportunities for companies willing to invest in learning how to use it - ask my father Janusz Kunke a business owner, who is often my “first client”.

The Anthropic Economic Index, published by the company behind Claude, found that the largest share of AI usage falls into augmentation rather than automation. People working alongside AI, using it as a thinking partner, produce better results than either humans or AI working alone. This is not about replacing workers. It is about making the workers you have significantly more capable.

For SMEs in Poland and across Europe, this is particularly meaningful. These companies cannot compete with corporations on technology budgets, but they can move faster, adapt quicker, and implement more decisively. A 15-person firm that trains its entire team on AI-assisted work and research gains an advantage that a 500-person firm with bureaucratic procurement processes cannot match for months or years.

The window for this advantage is open now, but it will not stay open forever. As AI literacy becomes standard, the early movers will have compounding benefits: better workflows, more experienced teams, and a culture that treats AI as a normal part of work rather than a threat or a novelty.

The Mission

I started ^Kunke Consulting because I saw a gap between what AI can do and what companies are actually doing with it. That gap is not about technology. It is about skills, imagination, awareness, and compliance.

My mission is to help my clients take advantage of the opportunities created by AI technology. Not to sell them tools they do not need. Not to promise golden miracles. But to help them build real, practical capability that translates into measurable business results.

If there is a gold rush happening, I would rather be the experienced guide who helps you find the right spot to dig than the merchant who sells you a shovel and waves goodbye.

That is the difference. And that is why this work matters.

Blazej Kunke is the founder of ^Kunke Consulting (https://kunkeconsulting.pl), an AI consulting company helping Polish and European SMEs implement AI through practical training, workshops, and strategic consulting. He previously spent over 10 years at global companies including McKinsey & Company and Franklin Templeton Investments. Text was written by Blazej Kunke with the help of 3 AI models: Opus 4.6, Chat GPT 5.2 and CODEX.