The global economy is in constant transformation. Every sector, every company, and every profession out there – is always battling to reach a new steady-state where market participants reach an equilibrium where customers are content. In other words, there is constant disruptive innovation happening, above and below the surface of what’s seen and reported. And for investors, this constant transformation is both a challenge and an opportunity.
In the coming decade, there is a high probability of unprecedented transformations for most sectors, companies, and professions. As a general-purpose technology, Artificial Intelligence, will embed itself in everything and flip the script for how to create business value. Things could change faster and more from the core than ever before.
As a consequence, the game of investing in this transformative future, e.g. Venture Capital, will likely be more difficult than ever. In this research piece, we’ve put together a list of 10 future paradigm shifts we foresee VC investors need to tackle and include in their playbook for the future – to continue generate competitive returns.
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In the history books of human civilization, each decade past usually registers higher level of disruption than the previous decade. This is because past innovations both build on top of each other, and converge into each other, to create a new steady-state equilibrium where doing business is faster, more connected, more fluid, and frankly – better.
For example, since the invention of the transistor and the emergence of the digital age in the 1950s, the pace of change has only gone higher and higher. Disruptions for most sectors have occurred in both higher frequency and to a bigger magnitude. The internet, smart phones, the cloud, industrial robots, etc. – are tangibles of an ever-changing society.
But with all of the incredible inventions of the past, we’ve never had a general-purpose technology that can both automate human labor and intelligence at the same time. AI is something else. Something that truly could change everything.
Now, with a statement like that, I’m sure you're thinking: “well, people have said that for a long time and so far, everything has not changed”. No doubt and granted, “everything” doesn’t usually change that often. Usually, there is a multiple-decades long period of novel technologies that together changes everything – or recalibrates society.
Historically, we’ve had three distinct so-called industrial revolutions – and each of them have been preceded by a set of disruptive innovations converging into a new platform for society. A platform for manufacturing, logistics, construction, housing, retail, and labor services, etc. – to conduct business on top of. And with each new platform, both the upsides and downsides, in terms of running a business or investing into one – were much larger than the decades prior.
The point here, by connecting the past with the present, and the future, is that every now and then there are decades that are much more transformative than others – and that we most likely are heading toward such transformative decade where prior truths are flipped on their heads.
A BRAVE NEW WORLD FOR INVESTORS
Our thinking is that the 2020s could become the decade where AI really starts embedding itself into society and offer glimpses of its’ transformative powers for a range of industries. And then in the 2030s, which obviously is a game of scenarios more than predictions – we’ll experience a decade of a profound recalibration of society. Or in other words, new equilibriums for a range of sectors.
To exemplify this, we’re currently seeing the emergence of autonomous vehicles on our streets, general-purpose robots in our factories and buildings, reasoning models for knowledge workers, and energy storage in novel batteries around the globe. We have a set of disruptive innovations coming online and amassing scalability to create future examples of creative destruction.
Now, you might think that these examples must prove themselves before we judge them on their transformative powers – i.e. that it’s still too early to judge the book by its’ cover. Meaning that autonomous vehicles are not yet perfect, general-purpose robots are not yet faster or more capable than humans, reasoning models cannot reason as good as a human being – and energy storage is still only in its infancy.
In general, these things are true, however, their respective progresses are exponential and improving significantly every month passed. This is why the valuations of companies building these transformative powers are valued as such (transformative).
However, you haven’t seen nothing yet. These types of transformative companies represent entirely new value chains forming, entirely new applications forming, entirely new ways to create customer value. They’re building the next big infrastructure foundations for society to place its companies and its people on top of. We’re clearly seeing the foundation of a fourth industrial revolution taking place, and the speed is only going to pick up. What we’re seeing is a brave new world for investors.
PAST FINANCIAL PARADIGMS
When you’re looking for viable scenarios for the future, it’s extremely important to first take in the learnings of the past. There are always critical lessons to be learnt, that will guide us and provide clarity. And in the financial world, there certainly are plenty of learnings we need to acknowledge to best create scenarios for the future.
First off, when digital technologies proliferated in society and enabled seamless transfer of information – it made real-time transactions a reality through electronic stock exchanges. This enabled an explosion of transaction volumes, which consequently led to new brokerage platforms emerging, and the creation of the massive global financial sector of today. In distillation; fluid information enabled a new global financial system.
And secondly, with a significantly more global, cost-efficient, and fluid financial system overall – it meant that the possibilities to scale, acquire, trade, and IPO companies, improved by a billion miles. This created the financialization of previously non-fluid financial assets.
Currently, there are roughly 55,000 publicly traded companies worldwide, up from around 13,000 in the late 1970s. And the market capitalization of these companies have gone from a few trillion dollars and 30% of global GDP, to above 120 trillion and a few percentages above global GDP. This means that when financial transactions and instruments went from being regional, complex, and expensive, to being global, seamless, and cheap – the financial system grew massively.
And not only that, but new financial verticals came about, new ways to research companies were adopted, and novel financial instruments exploded across the board. No doubt, we’ve seen a large set of transformative paradigm shifts in the financial world over the past decades.
For example, in the publicly traded markets of debt and equity, these paradigm shifts have enabled billions of people to get access to corporate earnings in ways previously more or less impossible. Through the aggregation of equities into pension funds, mutual funds, and ETFs, we’ve seen a major democratization of investing, and a more equitable society overall. We’re now able to purchase a single stock or investment fun through a few clicks on our phones from anywhere on earth.
The main point here is that when novel general-purpose technologies proliferate, the financial industry transformed significantly as complexities were eliminated. This means that we should expect more of the same, when AI and cryptographic protocols proliferate. We should see future paradigm shifts arising.
PARADIGMS FOR VENTURE CAPITAL IN EARLY INNINGS
For the Venture Capital investment vector, we’re most likely in the very early innings of a decades-long period of profound transformation stemming from AI and cryptographic technology (among other disruptive innovations).
In our view, these two massively disruptive innovations will, on a 10-year horizon, completely transform the way VC investors operate, how they create value for both the companies they’ve invested into, as well as their own investors (Limited Partners, etc.) – and prospectively even democratize the ability to invest in startup companies.
Until then, meaning until 10 years from now when we’ve prospectively seen an overall transformation of the Venture Capital landscape – we foresee a number of paradigm shifts that investors need to acknowledge and start adapting to. Some of these have already started, while others have not even left the station.
Now, the current state for many of the 40,000 Venture Capital firms out there is that there are brilliant researchers, deep domain experts, and seasoned investors with distinguished track records in finding extremely capable startup companies. Researching, analysing, and investing into successful startups is extremely difficult, which is why it is highly impressive when VC investors build long-term successful track records.
However, things can always improve, and things will always change. This is true for any sector and profession. And for these reasons, we’ve compiled our best theses on how VC investors could upgrade themselves and become even better at what they do – based on 10 future paradigm shifts we foresee in the next 10 years. Essentially, we believe there a new playbook to be used for investors.
10 FUTURE PARADIGM SHIFTS FOR VC INVESTORS
First off, this playbook will have to adhere to new standards for the way we make, power, move, speak, and pay, for economic activity in society overall. These aspects of conducting business will undoubtedly change substantially over the coming decade, much due to the embedding of AI into both the digital and physical fabrics of society.
1) FROM SECTORS TO SYSTEMS DISRUPTIONS
The first paradigm shift is called “From sectors to systems disruptions”, meaning that investors will increasingly have to deal with more systems-wide disruptions as opposed to singular disruptions (for a specific sector or product category). For example, we could see several sectors joining forces and together changing the way we make, move, and consume physical products.
For example, from the factory physical products are made, to the way we move them to distributors, and how we consume them – the manufacturing arena today is like a chain of links that adds a value a of some kind to a specific product and then pushes it forward to the next market participant. But with the advent of AI, there is a good likelihood that this chain converts into a circle instead, one where all market participants are aligned in a new system. Or in other words; from a linear economy, to a circular economy.
Another example is how the current world of software could get upended with novel AI models able to produce any type of application and code – and do it to a very low cost. This could mean that many of the value chains we’ve built over the past couple of decades would cease to exist in favor of new value chains, that are much more connected and part of a new system.
In distillation, AI is currently leading us to a fourth industrial revolution and for every industrial revolution past – there are more systems-wide transformations than before. As a consequence, we could see much more binary outcomes when it investing into startup companies – either much better or worse, compared to today. Investors need to be prepared.
2) FROM STATIC APPLICATIONS TO DYNAMIC MACHINES
And then we have the second paradigm shift; “From static applications to dynamic machines” – which essentially means that we’ll see both physical and digital products solving a lot more customer problems than the products of today. For example, a general-purpose robot in a factory able to move stuff, weld metal, clean floors, do precision cutting, and many more tasks – will outcompete machines that only solve one problem each. This will also go for robots in our homes, autonomous vehicles, drones, etc.
And furthermore, companies that today are structured for building a single-utility product (physical or digital) and are by design not built for an ever more dynamic future, will go head-to-head with a new breed of companies that are built (by design) with an ever-changing world in mind. Or in other words, built like dynamic machines instead of static applications, able to change both their tactical and strategic planning swiftly.
Prospectively, they’ll be built with the ability to self-improve much faster than is the case today for most companies. They’ll have the ability to ship code changes on a daily basis instead of building projects that lasts weeks. They’ll be able to implement partnerships on a weekly basis instead of several months. And finally, they’ll be able to change strategic course in months, instead of years. All because they are structured like dynamic machines.
Our view is that investors need to evaluate potential investment opportunities (startups in this case) based on their ability to quickly adapt to new market conditions. This adaptability will be much more sought-after in 10 years from now, compared to today, because AI will speed up the time from idea to creation by several hundred times. AI agents that constantly, day and night, are working for humans and never take a break in trying to outcompete competitors – will no doubt be a game changer.
Invest in “dynamic machines”, instead of static application companies, in other words.
3) FROM BROAD INDIVIDUALS TO EXPERT NETWORKS
And then the third paradigm shift and part of our future playbook for VCs, is called “From broad individuals to expert networks”. Essentially, we foresee a continued shift toward domain expert networks supporting investors to get deeper understanding of market dynamics and novel technologies. This has been exacerbated in the public equity research field during the past 20 years – but it’s still a long ways to go before all analysts are deep experts in their respective fields.
Now, this is already the case for many VC investors out there (though certainly not for all), but the difference from today and 10 years from now – could be that expert networks become a lot cheaper and a lot more accessible. And furthermore, on the demand side (from the investors’ perspective), having easily accessible expert networks ready to provide quality research support will become a more critical aspect of investing going forward.
This is because advancements in novel technologies are so much faster now and, in the future, than in the past. You simply cannot afford to do all research on your own if you’re a generalist investor. You need fast and quality research support “on-call”.
4) FROM INCREMENTAL TO SCENARIO RESEARCH
And then we have the fourth paradigm shift; “From incremental to scenario research”. What this somewhat of a confusing title means is that conducting research in an incremental way will not be as lucrative as in the past. The world moves so much quicker than ones’ ability to be constantly aligned with all the novelties that’s heading our way. And with the all-seeing AI research tools emerging, the competitive landscape of investing will only get tougher.
Since the turn of the millennium, having had a scenario-based research approach to investing has been incredibly rewarding. Practically, “scenario research” means to create a list of prospective scenarios that may or may not materialize over the coming decade (or at least a long-term period), and then constantly calibrate these scenarios and consequently be much more prone to be successful in playing these scenarios correctly. This is in stark contrast to incremental research where you analyze more predictable trends where the return on investments is more quantifiable.
To be clear, both the incremental- and scenario-based research approaches will continue to be lucrative. And this is not a binary thesis, instead, we believe the scenario-based approach will become more critical to sustain competitive investment returns – with the foundational reason that AI holds the key to unlock much greater transformations than in the past.
In short, investors need to look beyond the horizon more than in the past, in order to find the best investment cases.
5) FROM SCATTERED TO CONNECTED DATA
Then we have “From scattered to connected data” on the fifth place on our list. And this is not a prediction or advice that’s particularly difficult to include. However, it is a substantial difficulty and complexity for investors today. Currently, most of us carry our data in a plethora of storage containers – be it in excel or writing documents on our computers, presentation-slide files, in physical notebooks, as links in our browsers, or reports stored in the cloud.
The combinations of storing data are endless and as such, the cross-pollination (meaning insights) of the data we all store at different places is not happening to extent it could. We believe that, in 10 years from now, almost all investors will have connected all of their data through a variety of ways. Either they will gather everything and store it in one place, or they will connect all nodes of data into a network that’s constantly finding valuable insights.
6) FROM MANUAL TO AUTONOMOUS RESEARCH
Then we arrive to the “From manual to autonomous research“ paradigm, which is one of the most intriguing ones on this list – and a topic that has gotten both quicker and longer legs at the start of the new year. We’ve seen new Large Language Models (LLMs) emerging with new ways to create insights, along with new AI research agents that can explore any topic and provide human-quality conclusions. We can now seek and research deeper.
Today and in the past, doing deep research to analyze with quality inputs, is not an easy task, and it takes time. Currently, most of the time spent to decide if to investing into a startup (or not), goes into researching all relevant inputs. While analysing is in the minority. In general, this is certainly the case.
But what happens when we have AI agents that are swiftly able to scour the internet and all the relevant databases out there – and then deliver reports on how any sector (or specific thesis) is evolving? Most likely, it means that investors will be able to employ AI agents that do the mundane research tasks and focus more on what truly matters, meaning digging really deep and answering the question “is this the right company to invest in?”.
7) FROM CAPITAL TO (MORE) VALUE-ADD
The seventh paradigm shift spells “From capital to value-add”. Here, our thinking is that with diminished time spent on mundane research (e.g. gathering data, sources, etc.) and administrative tasks (compiling case materials, etc.), there will be more time for VC investors to guide and provide expertise to their portfolio companies.
This means that the lines between VCs, accelerators, venture studios, etc. – could blur a bit as investors are freed up to add more value. VCs sit on a breadth of experience, networks, and domain expertise, and sharing these valuables to founder teams will make their VC firms more attractive.
Founders are always looking for long-term attractive owners, not only from an investment standpoint – but also in terms of operational strategy. VCs that are able to provide more value-add than strictly providing capital – will likely attract more intriguing investment opportunities.
8) FROM LIMITED TO UNLIMITED PARTNERS
Then we have “Limited to unlimited partners” as the eight paradigm shift in the VC landscape. Our thesis here is that with AI-based research tools, scoring models (judging how attractive investment opportunities are), and more seamless ways to finance startup companies – the startup-VC-Limited Partner value chain could go from being rigid, to fluid.
In particular, this means that the current “limited” part of Limited Partners (LPs) could morph into an “unlimited” future state instead. Meaning that LPs could gain the ability to more seamlessly execute direct-investments into startups.
And furthermore, owners of a startup company oftentimes have quite different needs compared to one another. Founders, angles, and VC firms invest on different cycles and time-horizons. Enabling more seamless capital table could change the financing mechanism – and prospectively even introduce new business models (e.g. fee structures, etc.). From limited, to unlimited, investment opportunities.
9) FROM CLOSED TO BROAD ACCESS
With new cryptographic protocols that enable more seamless financial cap tables, and improved ways to bundle financial ownership of startup companies – we could see a ninth paradigm shift materializing, name “From closed to broad access”.
Here, our thinking is that with ease of structuring an ownership cap table, comes the ability to broaden the investor base for both VCs and LPs. Over the past 50 years, this has been a gravitational learning (meaning that nothing has defied it) in terms of publicly traded companies. Through technological advances, we’ve seen the number of public companies explode, leading to improved access for all types of investors.
With cryptographic protocols (e.g. blockchain), we could see this gravity attract otherwise not relevant investors to invest into startup companies – through both VCs and LPs that structure their ownership to suit such investors. Essentially, through a prospective wave of ‘tokenization’, we could see startup companies go public much earlier than in the past, consequently – VCs could become an important part of the mechanism that enable this broader access of startup investment opportunities. Maybe we’ll see a lot more thematic funds and ETFs?
10) FROM INVESTMENT THESES TO AUTONOMOUS SIMULATIONS
And finally, the 10th and last paradigm shift in the new playbook for VCs, named “From investment theses to autonomous simulations”. Now, this is a very long-term thing and will surely not go mainstream in the coming handful of years. However, we could see a novel branch of research that, instead of building theses of what might transpire in the future – go further and actually tries to travel into the future and see how theses perform.
What we’re talking about here is a shift from theses to simulations. Because when AI agents can conduct tasks based on a certain set of instructions and stored memory – who says they won’t be able to simulate how market actors behave when new settings are plugged in?
An analogy would an AI creating a music album, deploying it to Spotify in stealth-mode (only a few thousand listeners can access it) and getting the engagement data to see if it’s something it should release more broadly. In our investment-related scenario, the listeners would be AI agents representing all market actors.
But let’s do a full stop here now. Do contact us if you want to discuss this paradigm shift in more detail. It’s undoubtedly the by-far most intriguing thesis on the list…
All the best and until next time,
Christopher Lyrhem & Daniel Isaacs
Contact: christopher@sircular.io
Additional research from Sircular:
#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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