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Why AI will Disrupt Company Inc.



With all the disruptive innovations we’ve produced over the past century, isn’t it quite remarkable (even a bit strange) that the traditional CEO-led “Company Inc.” structure – still is the go-to method of executing the mission of an organization?  Well, not really. Because, in order to reach success, a company needs managers to steer groups of utility-producing people toward the same goal. The sum is greater than the parts. Both are needed.


But what would happen if we could clone ourselves and create an AI that is both a manager and producer of customer value? In this research piece, we discuss the prospect of a groundbreaking transformation for how companies are created, structured, and operated. In the coming years, we’ll most likely see the normalization of personal AI employees, corporate project managers, autonomous coders, and even companies set on autopilot by ‘multipreneurs’.


 

If you're reading this on a desktop, we suggest you open the PDF-version, but if on mobile phone - continue reading below. You can also listen on Spotify.

 

 

More than a century ago, the ‘Chief Executive Officer’-title emerged and came to be the wildly proliferated way of both structuring and operating a company. The CEO executes what the board of directors decides an organization should do. And despite the exceptional past century in terms of scientific discoveries, societal progress toward democratization, incredible disruptive innovations, and even walking on the Moon – the organizational setup for an incorporated endeavor is still very much the same.


The traditional way of building a company starts with a couple of founders having an idea to change a marketplace. They build a prototype and eventually reach an MVP for which customers are inclined to pay for. In this stage, they assemble a group of people that comprise the team tasked with executing the company’s mission statement. They are the executive team, with a Chief Executive having the last deciding word on things. And after a while, the founders set a board of directors together with the responsibility of choosing the right CEO and long-term strategy.


And then the company lives on, executing on the set-out strategy, with the selected group of people. And while there are different ways to operate (waterfall, agile systems, etc.) – the foundational structure is still very much the same now as in the middle of the 20th century.


But things could be about to change, and substantially so. Because, for the very first time, we’re very close to having the audacity to clone ourselves. Well, at least digitally and for many of the capabilities we possess, certainly not all of them. And while this cloning rhymes with the past three hundred years of automating both digital and physical tasks away from humans and into the hands of machines – AI is on a completely other level.



An AI Agent, which essentially means AI in the form of a digital entity, able to execute tasks – is the first time we’ve created something that automate our thoughts, decision-making, and even the creation of complex output. This is not a future scenario anymore, this is already happening, and the impacts of this are no doubt intriguing to explore. They will both be disruptive for how we live our personal lives and how society structures itself.


But instead of continuing writing a general analysis on how AI will transform society, let’s go through four tangible pathways for how AI could start restructuring the way we organize companies in the coming five years. It’s always useful to tackle complexity by trying to simplify its’ prospective impacts.


1) People building their personal AI employee team


The first pathway (among many more of course), is already initiated and one where people start employing their own AI agents. Already now, these agents help with everything from researching, writing, coding, communicating, and brainstorming. Examples of these AI agents (for lack of a better word) include ChatGPT, Claude, Gemini, Grok, and Perplexity. Essentially, they’re raising human productivity by an order of magnitude.


But so far in time and predominantly, these agents have not been part of people’s everyday workflow. This is now coming in hot. Tools like LangChain and Auto-GPT let people build multi-step AI workflows that research, write, and execute decisions on their behalf. And for non-technical users, platforms like Zapier, Make, and Pipedream enable AI automation, integrating AI with emails, databases, and customer interactions effortlessly.


The ability to create custom AI workflows means people can now outsource research, brainstorming, and even coding to AI-powered assistants. AI is quickly evolving from a single assistant to a team of specialized AI workers, with distinct agents handling finance, customer support, and content creation. This leads to substantially increased personal productivity.


Take me for example, I’ve cloned my voice to be able to produce podcasts at any given time without the need for a microphone, a quiet room, and manual editing. I’m now able to produce a podcast episode with my own voice sitting on the subway (by simply providing a text). I’ve also created agents that are really good at specific tasks, for example producing high quality music, creating visual illustrations and videos, exploring recent events and distilling news, and even writing research (I receive a research piece every 20 minutes in my mailbox). The next chapter is to connect all of these together.


Building agent systems for personal workflows will no doubt mean that some are way quicker than the general competitor, while some are way behind. Having AI integrating seamlessly into your work environment, through writing or even by voice command – is no less than a workflow revolution in the early making. If you haven’t started experimenting, now is the time.


2) Using AI is the only way to adapt for companies


Then we have the second pathway, which is the one where companies are, instead of employing humans, deploying AI to conduct tasks of all kinds. This is quickly releasing costs and improving their customer value. Many companies are already replacing entire business functions with AI, shifting from human-managed workflows to AI-driven automation.

For example, Klarna’s AI-powered customer service assistant now handles two-thirds of all support requests, equivalent to 700 human full-time staff, while Salesforce and Walmart have embedded AI in their operations, with AI managing everything from predictive sales to supply chain logistics.


In these cases, AI allows companies to become much more productive, enabling them to speed up decision-making, improve demand forecasting, optimize HR functions, and even manage legal risk. The rise of AI-powered corporate tools also means fewer middle managers, as AI agents oversee projects, coordinate teams, and track performance. In many companies, AI is already writing e-mails, analyzing customer data, and generating market insights (much) faster than humans.


Furthermore, integrating AI that helps developers code has shown to increase productivity by upwards of 40% (according to IBM). And for Google, AI systems are now generating more than 25% of new code for their products (humans are their supervisors), according to CEO Sundar Pichai.


So, in a future where AI is an integral part of business operations, companies that fail to integrate AI will surely be outperformed by AI-native competitors. In practise, it means that people will have to upskill themselves into being managers of AI agents and build agentic systems that jack into different ecosystems in order to create a desired output. People will become managers of AI.


3) Anybody becoming a coder – Democratizing entrepreneurship


And then thirdly, we have the pathway of people not being able to code, now being given the ability to produce code and software applications that people are inclined to both use and pay for. This means a massive democratization of entrepreneurship.

So far in time, it’s been quite the hassle to get an idea into fruition. Building a prototype is not easy, as it requires finding the right person to code your idea into something that someone could get utility from. But now, people can simply tell an AI what to code, what to connect, or what to publish.


From lines of code, to conversations.


This means that anybody with an idea and the strive for building something, will be able to do so. Few things in life are easy and thinking that simply telling an AI to code for you and expecting monetary results in an ever-more competitive marketplace, is ludicrous. It’ll continue to take hard work and determination.


However, being able to start, get off the ground and get your hands dirty – should definitely be considered a renaissance for entrepreneurship. Being able to get things off the ground and then learn as you go is, for many, a key enabler for becoming an entrepreneur – either full-time or on the side of their regular job. And in a few years, there will be millions of people loving the rush of creating new companies (in different fields even) which effectively means that the traditional path of building a career gets in competition with having a set of professional engagements.


From career paths, to career portfolios.


Examples of companies offering people the ability to create code by simply using natural language include Lovable, Bolt, Replit, Cursor, among others.


These companies are growing like crazy.


Take Swedish Lovable for example, which now is considered as one of the fastest-growing startups in Europe ever. They’ve reached ARR (Annual Recurring Revenues) of USD 17m in a matter of months.


But Bolt and Cursor have grown even faster, reaching ARR USD 20m and USD 100m respectively.


Crazy.


Essentially, over the course of the past five years, we’ve gone from a world where raising capital and learning to code were prerequisites of setting up shop (more or less), to the current state of things where simply describing your idea, the business case, the customer value, and the theoretical user experience – is enough to create a working prototype.


And quite soon, likely by the end of 2025, we’ll see AI management teams that operate digital applications autonomously. In practice, people will create digital applications, with AI capabilities on both the front- and backends, and then set up a team of AI agents that becomes the application's operators. Initially, it’ll take a little while to get the application and management team going.


Because building an automated system with immensely powerful AI agents working together, creating an output that runs on autopilot (to a certain degree) – is a very complex thing. Everything needs to work in tandem with seamless workflows in order to not get stuck and break the whole operation down.


But once the creation of a digital application and the AI-driven management team are relatively easy, it means that the bar of entry for becoming an entrepreneur – has been lowered to basically an unimaginably low level. And when this is a reality for the mainstream, we’ll see a lot of people out there creating multiple companies, enabling multiple passive income streams.


In our view, this could lead to a collective unlocking of people amassing the bravery of starting their own companies, either on the side of their regular jobs or it becoming their regular job.


Now, if you regard the massive entrepreneurial effect from platforms such as Youtube, Instagram, TikTok, Etsy, Amazon, AirBnB, Spotify, and hundreds of other platforms, as a substantial collective unlocking of the human spirit of entrepreneurship – you haven’t seen nothing yet.


Being able to create digital applications and have a professional management team at your fingertips – could become one of the biggest mega themes on the planet in the coming decade.


When Anton Osika, co-founder and CEO of Lovable, says that their mission is for Lovable becoming “the last piece of software” and that they want “the 99% who don't code to have superpowers and build tech companies” – it speaks volumes to the importance of their product. They want to empower all people to create any type of software simply by using their natural language.


4) Competitive landscape requires new customer value


And now lastly, the fourth pathway, is one where the combination of the three prior leads to a significantly more competitive world than before. A world where ‘anyone’ being able to code anything simply by using their ability to speak and creative depth – opens the floodgates for a period of creative destruction of historic proportion.


When we’re able to “clone ourselves” (only speaking of the digital world here), it’ll enable hundreds of millions of people to compete with big corporations, on their very own. What happened with legacy companies when digital platforms arrived (i.e. Youtube, Instagram, etc.), will no doubt happen for a big chunk of the software landscape.


More people in a given marketplace always leads to pricing-pressure. Time and time again, this is severely underestimated before a marketplace undergoes such transformation.

And to withstand this, incumbents will require taking their product offering to another level. They’ll need to replace the successful strategy that has made them into what they are today, with something new, something better. Throughout history, this is a very difficult feat as most companies regrettably (in hindsight) aren’t that good at rejuvenating themselves.


In the coming 10 years, there is a quite good likelihood that any digital application will be able to be copied with a single prompt, or close to it at least, and when this happens – companies need to deliver new customer value. And one of the most obvious novel tool in the customer value toolbox are personal agents for customers to use, advice, and build on their own.


Practically, and without going into deep here – it means that the mission of many digital application companies, will be to build super-complex AI applications that are tailored around the customer and fully understand whatever the challenge or opportunity outstanding. It won’t be enough to solely build applications for customers to use as a tool. The winning recipe will be to build AI applications that are good enough for customers to outsource entire departments and leave all the complexity for it to solve.


For example, instead of customers employing a lot of people to run an HR-department (both strategic and operational tasks), they’ll employ much fewer people and mainly focus on the strategic tasks while AI takes care of all the operational stuff. We’ll no doubt see individuals running entire departments that previously took 20 people to operate.


These individuals will build their team of AI agents to constantly solve tasks and come up with the best strategic paths forward.


In our view, this transition could be likened to that of the emergence of the internet, where new technology completely disrupted entire markets of the course of a decade. We’ll see a billion knowledge workers around the world having to evolve in order not to become obsolete.


And furthermore, in a steady-state future, we won’t even acknowledge that AI is the backbone for many of the tasks we need to solve every day. We’ll employ third-party software applications which will  have millions of AI agents in the backend constantly helping you to solve problems. It’ll be seamlessly embedded into everything. This means that every company on earth needs to become an AI-native company, or face complete obsoletion.



Conclusions – Company Inc. will be disrupted


Let’s conclude this discussion. What’s currently happening in society is the early innings of a complete transformation of its’ foundational structure and how everything operates. AI enables frictionless automation of data, knowledge, and decision-making. It’ll be embedded into every consumer and business application on earth.


Going forward, it’ll be possible to clone humans (digitally) and in effect, disrupt the way companies are structured and operated. “Company Incorporated” will transform from its’ current state. The core reason for this is that people will go from being workers solving problems, to builders creating solutions.


In this dawning AI-economy that’s currently forming, anyone will be able to write code, create customer value, and arguably scale these abilities to infinity. Anyone will be able to spin up a digital application and create a company over a weekend.


And when this is the case, a meaningful share of the global population will be inclined to do this. To build their very own company, either as their main source of income, or a side-hustle.


Furthermore, when people are empowered by AI to the fullest extent, we’ll likely see the death of middle-management, corporate AI management teams, autonomous companies run entirely without humans, AI agents monetizing themselves, and ultimately – we’ll see AI migrating from being a general-purpose technology, to being part of the workforce itself.


My bet is that in five years, as AI will be able to clone ourselves – we’ll seen the creation of a new type of Company Inc., and subsequently an explosion of single-person companies and side-hustles. People will increase their personal productivity by an almost infinite number and spur a substantial increase in both competitive challenges and opportunities.


In distillation, AI going from being a novel platform technology, to being part of the global workforce – will, in hindsight, make the creation of the assembly line into an antiquated form of organizing a company.


The playbook for how to best run an organization will be rewritten.



Until next time,


Christopher Lyrhem

Chief Future Officer, Sircular






 

Additional research from Sircular:



#8) The Playbook for Venture Capital – 10 Paradigm Shifts for VC Investors

Report on how the playbook for VC investors could change over the coming decade. 10 future paradigm shifts are compiled – spanning investment approaches, research, execution, way of working, value chain changes, and more. Link


#7) The New Manufacturing Tech Stack – The Path to Reshoring and Circularity

AI holds the potential to upend the linear economic model that’s still growing, through a path to reshoring manufacturing capacity and a circular future. This piece includes a list of >200 pioneering companies. Link


#6) Software 3.0 – The Rise of Autonomous Software Companies

The software world is on the cusp of radical transformation. AI is moving faster than most  could’ve predicted, and we’re about to enter the era of Software 3.0, where software companies moves from using AI – to becoming AI. Link


#5) Humanoid Robots – The Trillion Dollar iPhones of the Physical World

General-purpose robots hold the potential to become a multi trillion-dollar market and the biggest product category ever, while also enabling the next big platform economy (after smart phones). Link


#4) Just A Rather Very Intelligent System (J.A.R.V.I.S.) – Your Second Brain

Investors having their own “Jarvis” enables proactive advice and brainstorming, real-time insights about events, and exploration of new investment opportunities hidden deep in their datasets. This will become a game changer for the industry. Link


#3) AI Agents – With License to Win

In 2025, we’ll move to “Level 3” in the progression scale for AI, where AI agents, and systems of these agents, take form and are able to execute tasks for their owners. For investors, employing AI agents will become a license to win. Link


#2) Streaming the Physical World – The On-Demand Revolution is Broadening

Over the past 20 years, on-demand services have become the most successful business model in the digital world. With the help of AI, this streaming business model will take a bite of the physical world as well. Link


#1) Introduction to Welcome to the Future – Autonomous mobility, retail stores in wheels, etc.

Our introductory research piece highlights several intriguing spaces; including autonomous mobility, retail stores on wheels, and general-purpose humanoid robots. Link





Welcome to the Future is a thought-provoking research letter, providing investors with long-term theses on how society could change in profound ways. This research letter is meant as informational purposes only, not advice, and is not the opinion of Sircular.



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