The Emotional Arc of AI: Why Indifference Turns to Agency (and What Happens In Between)
The End of Professional Services as We Know It: How the “Information Factory” Will Insource Everything
Introduction: A Rude Awakening for Professional Services
A century ago, if you needed new shoes, you went to the local cobbler. If you needed nails or a horseshoe, you went to a blacksmith. The world ran on a local, human scale. Skilled craftspeople-“artisans”-were essential to daily life.
But then came the Industrial Revolution.
Factories sprouted in brick and steel. Machines and assembly lines broke down these artisanal tasks, standardizing and automating them at unprecedented scale. The artisan class didn’t vanish completely, but they dwindled and migrated into new roles. We collectively decided that speed, cost, and consistency mattered more than one-of-a-kind craftsmanship.
Fast-forward to the 21st century.
Artisans are back-except now they operate in the realm of information rather than physical goods.
Strategy consultants charge exorbitant fees for what amounts to specialized knowledge and carefully polished advice. Marketing agencies pump out campaigns that only they “know how” to design. Fractional executives parachute into companies to lend skill sets that small or midsized businesses can’t-or won’t-build in-house.
We might call these roles “consultants,” “agencies,” or “fractional pros,” but they really are the modern version of the blacksmith or cobbler: talented, knowledgeable, but expensive, specialized, and ultimately finite.
Yet we’re on the cusp of a new revolution. Just as steam engines and assembly lines disrupted the physical artisans, AI-particularly large language models (LLMs) like ChatGPT, Claude, or Gemini-is poised to disrupt the information artisans.
The game-changer is that AI can systematically replicate knowledge work in minutes, often with near-zero marginal cost.
Now, instead of paying for an outside expert, a company can “build” an information factory entirely in-house-no capital expenditures, no complex machinery. All you need is a laptop, an internet connection, and an LLM. With that, you can produce plans, content, and strategy docs that once cost five or six figures on the open market.
This article is about why this shift is happening, how it follows a clear historical pattern, and why it will almost certainly spell the end of professional services “as we know them.”
Of course, a small fraction of niche or extremely innovative professional service firms will adapt-or remain valuable for highly specialized tasks. But the broad swath of consulting and agency activity we see today? It’s about to be consumed by the same forces that turned blacksmith shops into museum curiosities.
Brace yourself: the changes will come quickly. Unlike the first Industrial Revolution, which required huge amounts of capital and physical machinery, this revolution only requires a cloud login and a browser tab. That means it can (and will) happen virtually overnight.
I. The Historical Pattern: Artisan → Factory → New Artisan
1. Physical Artisans in a Pre-Industrial World
Before the Industrial Revolution, nearly everything was handcrafted. The local blacksmith hammered out each nail, one at a time. The cobbler measured feet, cut leather, and produced shoes in small batches. Furniture makers, tailors, weavers-each possessed unique, almost sacred skill sets. This craftsmanship made sense in a world where mass production and rapid distribution didn’t exist. You got what you needed from an individual artisan who had painstakingly honed their craft for years, often in a familial or guild tradition.
From a modern perspective, it’s easy to romanticize those times as simpler, more human. But “handmade everything” was also slow, inconsistent, and expensive. Artisans had a monopoly on skill. If you wanted well-made goods, you had no choice but to pay the blacksmith or the weaver their asking price-or make do without.
2. Factories Reshape the World
Then came the mechanical loom, the steam engine, the assembly line. Factories emerged, reorganizing labor and capital around a systematic “workflow” approach. One machine could do the weaving previously handled by a dozen people. One assembly line could churn out hundreds of shoes far faster than ten cobblers combined.
This was standardization on a revolutionary scale. Instead of one artisan carefully performing each task from start to finish, factories broke down tasks into discrete steps. Each machine operator became responsible for a specific stage. The machine replaced or augmented artisanal skill. Productivity skyrocketed, costs plummeted, and output quality became more uniform-if less unique.
The shift was painful for many artisans whose livelihoods evaporated. Some adapted by learning to operate machines. Others persisted in artisan niches. Still others left the craft entirely. But for society as a whole, the shift was unstoppable. The economic advantage was too large to ignore.
3. From Physical to Information Artisans
Over time, people’s abilities migrated to new frontiers. Once factory-produced physical goods became cheap and abundant, we found new ways to deliver value.
We transitioned from brawn to brain, from forging and weaving to accounting, marketing, design, writing, consulting, coaching, and more. In the post-industrial era, the skilled “artisans” in society increasingly became those selling knowledge, ideas, or creativity.
Like the physical artisans of old, these modern knowledge workers command high fees precisely because they hold specialized expertise.
Consultancies promise frameworks, strategic thinking, or best practices you supposedly can’t replicate on your own. Marketing agencies have “secret sauce” for creativity or brand-building. Executive coaches have unique processes for unlocking leadership potential. Fractional executives fill a knowledge gap you can’t afford to hire for full-time.
They are the 21st-century blacksmiths, forging intangible goods: information, insight, execution capacity.
II. Information Artisans and Their Vulnerabilities
1. The Professional Services Economy
Look around, and you’ll notice that the professional services sector has ballooned into a multi-trillion-dollar industry.
We have giant consultancies with global footprints. We have small boutique agencies with hyper-specific specialties. We have entire job boards dedicated to fractional CFOs, CTOs, and CMOs. There’s a massive demand for specialized knowledge, presumably because building it in-house is too difficult, slow, or expensive.
But that’s the key vulnerability: outsourced knowledge is valuable only as long as it’s too cumbersome or slow for a company to cultivate that capability internally.
The moment you can replicate the external expert’s deliverables in-house-cheaper, faster, or at a higher level of quality-outsourcing collapses. The external vendor no longer has an advantage.
2. The “Slow” Factor
Consulting projects are famously slow-moving. You might have a three-month contract, culminating in a strategy deck. Agencies often require multi-week lead times to develop creative assets.
Fractional executives might onboard over several weeks, then gradually implement changes. Meanwhile, the client is left waiting, coordinating, holding countless meetings, dealing with a complex chain of communication.
Speed is not the hallmark of professional services. Nor is transparency. Often, you have limited visibility into how the agency or consultant is performing their magic.
3. The Cost Factor
Professional services aren’t cheap. Even a modest-size consultancy or agency might charge tens of thousands of dollars per month. A brand identity project or a market research initiative can cost hundreds of thousands.
That was once tolerable because it was deemed “too hard” to do all of that in-house-especially for smaller companies without the budgets to hire deep internal experts. So we collectively accepted that renting high-priced knowledge was the best (or only) option for certain tasks.
But that logic works only until a new method emerges that can produce the same or better results for a fraction of the cost. Once cost drops dramatically, inertia flips sides: companies that keep paying large fees for external knowledge look wasteful, while those who adopt the new method get immediate ROI.
III. The Rise of the Information Factory
1. AI as the New Assembly Line
Enter AI-especially large language models. These powerful systems can parse vast amounts of data, generate text, create images, summarize information, and even propose strategies. A prompt like, “Build me a 90-day marketing plan for a SaaS product targeting CFOs,” can yield a structured plan with outreach channels, messaging angles, budget guidelines, and detailed timelines in seconds.
That’s the “factory” effect. One of the biggest reasons physical factories were so transformative was their ability to produce consistent, standardized output quickly.
Instead of waiting a week for a blacksmith to craft a set of hinges, a factory could churn out thousands. Now, instead of waiting weeks for a marketing agency to deliver a content calendar, an AI model can deliver multiple versions in minutes. The cost: near-zero. The wait time: negligible.
2. Why Zero Capital Changes Everything
You might be thinking, “Factories were expensive to build and maintain.” Historically, yes. Only those with significant capital could afford to construct a plant, buy machines, and pay a workforce.
But the “information factory” we’re talking about has almost no capital requirements. There’s no need to buy expensive hardware or lease giant industrial sites. You just open your laptop, log into an AI system (or host one if you have the resources), and start operating your “assembly line” of knowledge production.
This drastically reduces the barrier to entry. In the 1800s, capital was the limiting factor for who could own a factory. In 2025, the only limiting factor is your awareness and willingness to adopt AI. If you have an internet connection and a monthly subscription to an AI platform, you can replicate large chunks of knowledge work previously outsourced to consultants or agencies. This is the kind of shift that can happen fast-because nothing stands in the way of immediate adoption.
3. Speed as the Ultimate Advantage
In any competitive market, speed is a huge advantage. Factories decimated artisans by delivering high volume at consistent quality-faster and cheaper. Now, AI can generate a strategic plan, test marketing copy, or build a product roadmap in a fraction of the time it takes a professional service firm to do the same. This means that each cycle of iteration compresses.
What used to require weeks of back-and-forth with an agency can be accomplished internally in a single day of AI-augmented brainstorming.
Businesses that adopt AI insourcing can respond instantly to new market conditions, test 10 versions of a landing page in a single afternoon, or pivot brand messaging by tomorrow’s board meeting. This level of velocity makes external vendors-who must juggle multiple clients, gather context, and staff the right people-look painfully slow.
If the external vendor’s advantage was specialized expertise, it’s overshadowed by the capacity to produce an equally robust solution (or at least “good enough” for most needs) at lightning speed.
IV. Why This Spells the End for Traditional Professional Services
1. Review, Replicate, Replace
It’s straightforward for a business to test whether they can replace a consultant or agency with an AI workflow. They just look at the deliverable they got from the vendor and ask: “Can we replicate something at this level using an LLM?”
If the answer is yes-and it increasingly is-then they replicate it, review for quality, and if it checks out, they never need that vendor again.
This dynamic is lethal for professional service firms. Once a single big deliverable (say a strategic plan, a content marketing calendar, or a leadership development framework) can be reliably produced in-house via AI, the rest will follow. The moment a company sees success in one area, they’ll ask, “Why not replicate the rest?”
That’s the factory effect: it’s not about one output, but about building a system that can produce all the outputs you used to buy from external vendors.
2. Killing the Old Excuses
For years, the professional services industry has leveraged the following arguments to justify their fees:
| “We have a proven methodology.”
But an LLM can quickly ingest documented methodologies, frameworks, and best practices.
| “We bring a team of specialists.”
Yes, but an AI can generate specialized knowledge from a broad training corpus. And with prompt engineering, we can replicate or approximate a team’s knowledge base.
| “We create custom-tailored solutions.”
Yet AI can tailor outputs to any prompt in real time-faster and more iteratively.
The reality is that, as AI’s capabilities grow, these differentiators get weaker. Companies need to pay an external premium only if the vendor is doing something AI can’t do internally-or if the vendor is orchestrating AI better than the client can. But those cases are quickly becoming the exception, not the rule.
3. Speed of Adoption and the Domino Effect
Unlike the Industrial Revolution, which required years or decades to build out factories and railroads, the Information Factory revolution can happen in a matter of months. All the infrastructure for global adoption is already here: the internet, cloud computing, and proven AI platforms.
So let’s say one competitor in your market invests in AI workflows for marketing. Their cost to produce high-quality campaigns drops. Their time to launch new campaigns plummets. Their marketing overhead shrinks dramatically. Meanwhile, you’re still paying big fees to an external agency that takes weeks to deliver.
Who do you think gets ahead in the market?
Before long, you’ll be forced to adopt the same approach just to keep up. That’s how a domino effect works. One or two early movers show the advantage, everyone else rushes in. Professional service firms, which rely on stable, high-margin contracts, get blindsided.
V. Examples: How the Information Factory Dismantles Specific Service Sectors
1. Consulting (Strategy, Operations, Management)
Management consulting might be the most venerable domain in modern professional services. Whether it’s big names like McKinsey, Bain, and BCG, or boutique firms in specialized niches, they all promise to guide leadership decisions. But a large chunk of their value-add is delivering frameworks, data analysis, and recommendations.
AI is already capable of:
Summarizing large sets of data to identify trends.
Applying known frameworks like SWOT, Porter’s Five Forces, or “Playing to Win.”
Generating slide decks or strategic plans based on queries and organizational data.
Sure, there’s a question of intangible insights or “hands-on experience” that top consultants bring. But if 80% of your consulting project is “analysis + frameworks,” then an LLM-based workflow can cover that 80% at near-zero marginal cost. Once a company sees they can get a “first draft” of strategy from AI, do they really need to pay $500,000 for a consultant’s polished version?
2. Marketing and Creative Agencies
Marketing agencies thrive on the promise that they’re more creative, more up-to-date on trends, or have deeper subject-matter expertise. But consider how AI can:
Generate 10 or 20 versions of a marketing campaign theme in minutes.
Produce images, copy, slogans, social media posts, or email sequences on demand.
Analyze SEO data or consumer sentiment automatically.
Agencies typically budget weeks to develop creative concepts, run them by account managers, refine, and re-present. AI can spin up multiple concepts instantly, and you can A/B test them in real time with a fraction of the overhead. As for brand strategy or big ideas-yes, agencies claim unique thinking.
But “big creative leaps” can also come from in-house teams using AI as a brainstorming partner. The speed advantage alone is enough to topple the old model.
3. Fractional Executives (CFO, CMO, COO)
Fractional executives have exploded in popularity. Small or medium-sized businesses pay part-time experts to bring specialized knowledge-like a fractional CFO for finance or a fractional CMO for marketing. These roles are valuable because the business doesn’t want or can’t afford a full-time hire, yet needs strong domain expertise. But AI reduces the need for deep domain knowledge. I
If an LLM can do the initial drafting of your financial plan, marketing plan, or operations manual, you no longer have to pay a part-time CFO or COO to do the same.
Moreover, “operator-level” tasks-like maintaining spreadsheets or analyzing budgets-are well within the scope of AI automation. The result? Instead of paying a fractional CFO $5,000 a month, a single business operator can feed data and context into an AI workflow that replicates 80% of the CFO’s job. Over time, that 80% may climb closer to 95%.
VI. The New Frontier: What Happens to the People?
1. People Will Still Find New Ways to Create Value
Just as blacksmiths didn’t all vanish in the Industrial Revolution, knowledge artisans in the professional services space won’t vanish entirely. Some will adapt by mastering AI themselves.
They’ll become the “AI-savvy consultants” who orchestrate advanced workflows and integrate them into larger strategic or cultural transformations. Others might pivot into more specialized or creative domains that AI can’t yet replicate-things like visionary leadership, high-level negotiation, or extremely nuanced, relationship-driven roles.
2. A Smaller, More Elite Professional Services Sector
When mass production took over, artisanal goods didn’t disappear but became niche luxuries. The same pattern is likely for professional services: we’ll have a smaller, possibly more elite group of specialized consultants and agencies for truly novel, innovative, or high-stakes challenges that AI can’t handle alone. But the mainstream day-to-day tasks that feed the giant service economy-like routine strategy docs, marketing campaign creation, or standardized frameworks-will be insourced and automated.
3. The Rise of the “AI Operator”
Instead of a large workforce of knowledge artisans, the new wave of roles will be “AI operators,” “workflow designers,” or “prompt engineers.” They’ll be the ones who know how to quickly shape queries, interpret outputs, refine them, and slot them into the business’s daily routine. If that role sounds less glamorous than being a partner at a consulting firm, it’s also more immediately essential. The impact could be extraordinary for businesses that master it. Over time, these operators will see their skills commoditized as well-leading to an ever-continuing cycle where humans find new edges that technology hasn’t fully automated yet.
VII. Why It Will Happen Faster Than Ever
1. The Zero-Capital Argument
Historically, capital spending slowed each industrial transition. If you wanted to build a steam-powered factory, you needed massive financing, raw materials, and a workforce to run it. That took time-often decades-to scale. In contrast, building an “information factory” is almost instantaneous. You can sign up for an AI platform in minutes, feed it your data, and start producing in-house deliverables. That minimal friction means entire industries can flip from external to internal execution in the span of a year or two.
2. The Internet Is Already Here
In the early Industrial Revolution, you needed new infrastructure-rail lines, power grids, roads. In the knowledge revolution we’re seeing now, the entire planet already has an advanced digital infrastructure. High-speed internet, cloud services, and readily available computing power are ubiquitous. This existing platform allows AI capabilities to spread virally, with no geographic limitations.
3. Market Competition Fuels Rapid Adoption
All it takes is a handful of early adopters to demonstrate that insourcing knowledge tasks via AI is drastically cheaper and faster. Once they show they can outpace or outmaneuver their competitors, it sparks a chain reaction. Every CEO or board of directors starts asking, “Why are we still paying these fees if we can do it ourselves with AI?” The wave hits from multiple directions-startups, scale-ups, large enterprises-and before you know it, entire segments of professional services see demand dry up.
VIII. What Should Professional Service Firms Do?
1. Embrace the Factory, Don’t Fight It
The worst strategy is denial. If you’re in a service firm, you can’t just hope the hype goes away. The fundamental economics of AI are real: near-zero marginal cost, instant iteration, unstoppable scale. Fighting that shift is like a blacksmith refusing to acknowledge the factory. Instead, your best move is to incorporate AI deeply into your own processes. Offer solutions that come from your “man+machine” synergy. Provide new angles that AI alone can’t deliver-maybe advanced workshop facilitation, organizational change management, or high-level interpersonal nuance.
2. Specialize in the Extreme
One route is to become a hyper-niche provider who can handle the truly unique corner cases. That means focusing on the top 5% of challenges that an AI-based workflow might not handle elegantly-like extremely complex, uncertain, or high-stakes strategy moves that require subtle contextual knowledge. But note: this is not a stable position for the entire industry-only a small fraction of service firms can survive at this rarified level.
3. Transition to Teaching AI Insourcing
Another pivot is to become the guide who helps companies set up their internal “information factories.” Instead of charging for deliverables, you charge for training employees how to use AI tools effectively. You become a short-term accelerator. Once they’re up to speed, they might not need you on a retainer-so you’ll have to keep rotating among new clients or build a membership model for continuous updates. That’s still a feasible business, but it’s a far cry from the old days of months-long retainers for routine tasks.