We are inside the biggest technology shift of our lifetime

Access to AI is no longer the differentiator. Every business can buy the same models on the same day for roughly the same money. What separates the companies capturing value from the ones filing invoices is narrower and less glamorous: whether anyone inside the business is measuring what the tools produce.

That gap is why Breaking Trail exists.

01 / The pace

Adoption is climbing, steadily and unspectacularly. It is neither the collapse one camp describes nor the transformation the other camp sells.

21.8 percent of U.S. businesses used AI in a business function in July 2026, up from 17.7 percent in December 2025. Another 9.6 percent did not know whether they had used it.

Source: U.S. Census Bureau, Business Trends and Outlook Survey. Reference period 13 to 26 July 2026, released 13 August 2026. Approximately 1.2 million businesses; standard error 0.33 percentage points.

Among the businesses we actually serve, the picture is sharper. 46 percent of U.S. small employer firms report that the business or its employees use AI. 7 percent of those users have fully integrated it into the business.

Source: Federal Reserve Banks, 2026 Report on Employer Firms: Findings from the 2025 Small Business Credit Survey, published 3 March 2026. 6,525 firms with 1 to 499 employees, all 50 states and DC.

Forty six percent bought something. Seven percent built it into how the work gets done. The distance between those two numbers is the entire job.

02 / The pattern

The companies that missed the last shift saw it coming. They had the data. They had the warnings. Some of them invented the technology that ended them.

Blockbuster watched streaming arrive and could not pivot fast enough. It filed for bankruptcy in 2010. A Kodak engineer, Steven Sasson, built the first digital camera in 1975; the company could not execute against the shift because the new business cannibalised the profitable old one, and it filed for bankruptcy in 2012. Borders handed its online business to Amazon in 2001 to focus on physical stores and was liquidated in 2011.

The companies that struggle most with shifts like this are not the ones that miss them. They are the ones that see them and cannot change.

Paraphrasing Clayton Christensen, The Innovator’s Dilemma, 1997.

Seeing the future arrive is not the same as adapting to it.

03 / The gap

Almost every business now has access to AI. Far fewer can say what it produced.

56 percent of CEOs say AI has delivered no significant financial benefit to their business to date. 33 percent report gains in either cost or revenue.

Source: PwC, 29th Annual Global CEO Survey, published 19 January 2026. 4,454 CEOs across 95 countries and territories; fieldwork 30 September to 10 November 2025.

The more revealing number is the one about knowing. More than a quarter of organisations using AI, 26 percent, do not know whether it changed their profitability over the past year. Only 36 percent say it improved.

Source: McKinsey & Company, The State of AI in 2025, as published in the Stanford HAI Artificial Intelligence Index Report 2026, April 2026. 1,993 respondents across 105 countries; fielded 25 June to 29 July 2025.

The same split shows up one level down, at the desk rather than the board room. 55 percent of U.S. workers say they have used AI on the job. Among those who used it in the week they were surveyed, 31 percent finished one to two hours faster and 15 percent saved more than four. But 10 percent saved no time at all, and a further 3 percent said AI made the work take longer.

Source: U.S. Census Bureau, Renee Stepler, “About a Third of Workers Who Used AI in the Last Week Said They Completed Tasks One to Two Hours Faster”, 11 August 2026, drawing on the March 2026 Household Trends and Outlook Pulse Survey. Comparisons tested at 90 percent confidence.

That is the whole problem in one dataset. The same category of tool returns half a day a week to one worker and takes time away from another. Nothing about the tool tells you which one you bought.

A quarter of the market cannot answer the question at all. Not “it did not work.” Not “it worked.” They do not know. That is a measurement failure, not a technology failure, and it is the one we are equipped to fix.

04 / The stakes

While most companies are stuck, a small group is pulling away.

The 5 percent of companies BCG classifies as future built post 1.7 times the revenue growth and 3.6 times the three year total shareholder return of laggards, alongside 40 percent greater cost savings.

Source: BCG press release, 30 September 2025, “AI Leaders Outpace Laggards with Double the Revenue Growth and 40% More Cost Savings”, reporting the study The Widening AI Value Gap: Build for the Future 2025. 1,250 senior executives and AI decision makers across 9 industries, assessed against 41 foundational capabilities.

Read that honestly: it is a cross sectional association, not a causal finding. Future built firms may outperform for reasons that also cause them to adopt AI well. We publish it with the hedge attached because a firm that sells measurement does not get to launder a correlation into a promise.

05 / What we are against

AI is not the edge. How you use it is. That is the belief, and it carries a corollary that is less comfortable to print.

A great deal of AI work is unmeasured. Not badly measured. Unmeasured. The system goes live, somebody screenshots it working, an invoice follows, and no number is ever attached to it. That is what section 03 above is describing when a quarter of organisations cannot say whether AI changed their profitability, and it is what we find in almost every stack we audit. It is the thing we are against, and it is worth being exact about what “it” is, because the easy version of this argument is the wrong one.

The enemy is not agencies. We build systems that digital agencies deliver under their own brand, and the good ones are the people most frustrated by this. It is not consultancies either, or software vendors, or the client’s own team. Unmeasured work happens in all four, for the same unglamorous reason: measuring is slower than shipping, and nobody asks for the number until long after the person who could have captured it has moved on.

So the enemy is the practice, wherever it comes from. Including from us. The refusals further down this page are how we hold ourselves to that, and they have cost us work.

06 / What we are for

There is a version of this capability that already works, and large companies buy it by hiring for it. Someone who owns the measurement. Someone who writes the code. Someone who runs the channel. Same room, same number.

A business doing between $500K and $5M in revenue is not going to hire that room. That is not a failure of ambition, it is payroll arithmetic. Our reason for existing is that the room can be rented rather than hired, and that the rented version does not have to be the worse one.

That is what we mean by making this kind of technology accessible. Not that everyone should have access to AI. Access is no longer the scarce thing, which is the argument at the top of this page. What should not be reserved for companies large enough to staff a department is the ability to tell whether any of it is working.

07 / Why we exist

We started this company because we kept meeting the same business. It had the ChatGPT subscription. It had read the articles and sat through the webinars. What it did not have was a way to make any of it produce something measurable inside its own walls.

The agencies it hired ran playbooks. The consultants it paid handed over roadmaps and left. The tools it bought sat unused after the first month. Nobody was inside the business, measuring what worked, fixing what did not, and staying long enough for the systems to compound.

That is the gap we built Breaking Trail to close. We are forward deployed. We embed inside the businesses we work with. We measure everything we deploy. We stay through the phase most agencies skip, the part where systems become assets instead of expenses.

08 / The goal

A firm that sells measurement and cannot measure itself is telling on itself. So here is ours, in a form that can be checked rather than admired.

By the end of 2027, twenty five businesses in the $500K to $5M band can each produce a defensible number for what their AI and automation systems returned, reconstructed from source data on demand.

Note what that is not. It is not twenty five clients, which we could reach by selling well. It is twenty five businesses that can answer the question, which requires the work to have actually landed. We will publish the count, and we will publish it in the years it is behind.

09 / Who does the work

Breaking Trail was built out of three disciplines that usually live in three different companies: marketing, software engineering, and the restless habit of pulling new technology apart to find out what it actually does. An engagement here holds all three at once.

That matters more than it sounds. Measurement usually fails not because it is difficult but because it falls between briefs. The people running the channel do not own the data layer. The people who own the data layer did not choose the channel. The developer builds what the ticket describes. Everyone is doing their own job correctly, and the number still does not exist at the end of it.

We do not solve that by being large. We solve it by keeping the marketing decision, the measurement and the code inside one engagement, so there is no brief for the number to fall between.

What we refuse

Refusals cost something, which is why they are worth publishing.

• We do not claim results we cannot reconstruct from source data on demand.
• We do not take a retainer for a system we cannot attach a number to.
• We do not publish only the numbers that flatter us.
• We do not promise that a system we build cannot make a mistake. We tell you what it is allowed to do without a person, and we test it against your own cases before it goes anywhere near a customer.

The signoff

We help businesses make AI work. We measure everything we deploy. We stay through the last mile. We are tool agnostic, and we mean it.

We break the trail. You walk it with confidence.