How AI Will Reshape The Economy In 2026 (a16z Big Ideas)

Welcome to part two of our 2026 Big Ideas. Ryan Macintosh explores the rise of what he calls the electro-industrial stack, a new foundation for how we build and power America's industrial future. Angela Strange identifies a critical turning point in financial services and insurance where decades old systems are finally ready for reinvention. And Sarah Wang reveals how a dynamic agent layer is emerging to overtake traditional systems of record fundamentally changing how enterprise software operates. These aren't just forecasts. their firsthand perspectives from investors driving change across American dynamism, financial services, and enterprise technology.

Ryan McIntosh: My name is Ryan McIntosh. I'm an investing partner on the American Dynamism team. My big idea for 2026 is that the electro-industrial stack will move the world. The next industrial evolution won't just happen in factories, but inside the machines that power them. This is the rise of the electroindustrial stack. Combined tech that powers electric vehicles, drones, data centers, and all of modern manufacturing.

Ryan McIntosh: I think there are common tropes people report on. People talk about China's so far ahead we can't catch up. And actually, you know, you go back a couple years ago and people were saying, you know, China's very far behind and America's incredibly fast. So, we've seen sort of like a whiplash and now it's the opposite.

Ryan McIntosh: I think the reality is that you know, the technology that China has, America can do. We're very good at engineering. We're very good at doing specific things. And in fact even like the you know recent stuff around rare earth for example rare earth separation and processing we know how to do this we can do this we can do it incredibly fast. The real challenge is building the ecosystem to do this industrially at scale and doing it at a low cost.

Ryan McIntosh: Another example you know people typically talk about is is companies like SpaceX or Android these large businesses that need to move incredibly fast and thus vertically integrate. In many ways they're vertically integrating by necessity not strategy. There just isn't an ecosystem of companies that can scale with them. That is not the case in China. There are tier one, two, three suppliers, components, raw materials that exist in those ecosystems as well as the, you know, the institutions and political bodies that allow them to move incredibly fast. Those are the things that might take years or decades for us to catch up to China.

Ryan McIntosh: We can do the technology, but everything else needs to grow with it, or else we're just moving the bottleneck. So if you want to build the electro-industrial stack or the core components that feed into these technologies in the United States you need to blend Silicon Valley software talent and culture with industrial veterans.

Ryan McIntosh: Even companies like SpaceX, they were pulling propulsion talent from people who worked on you know shuttle program and various old school contractors when Shawwell came from aerospace corporation. Like there there is a there is a world where you need this actual expertise. You need to know what's been tried before. There are smart people out there in these other companies, but you need to be able to move a lot faster. There's a lot of advantages of software today. So, you need to be able to get the software talent that may not exist in these companies previously.

Ryan McIntosh: You also want to colllocate engineering and manufacturing concepts like design for manufacturing are something that you know when you're tightly integrated on the same footprint or in the same ecosystem you can move a lot faster. And I think also you need to build prestige around the mission.

Ryan McIntosh: Um, for a lot of sort of traditional Silicon Valley talent, the smartest people can work on a number of problems and there are a lot of problems that are worthy of working on. Some of them pay more than others. So, you need to attach sort of a a prestige or a purpose to what you're working on and use that to attract the top talent. The way that software will affect the physical world is through these sort of embodied electrified components.

Ryan McIntosh: And it's not just, you know, not just a humanoid robot or an electric vehicle, but it's the batteries, it's the power electronics, it's the compute, it it's it's the motors. All these things we're going to need to either reshore or vertically integrate within the companies who are building the end product. These are, you know, very technical. These require a lot of expertise. These are very difficult problems to solve. But the companies who solve it and the countries who have the talent base to in order to support it are the ones who are going to win in the 21st century.

Ryan McIntosh: And as software and artificial intelligence get stronger and they start having you know more of a presence in in automation and industrial military owning these supply chains is going to become even more important. And I think as we you know look forward 50 100 years owning the supply chains today are going to have a lot of effects of who controls both the sort of economic and military powers in the future.

Angela Strange: I'm Angela Strange, a general partner on the AI applications fund. And my big idea for 2026 is there will be a dramatic turning point coming to financial services and insurance where finally the risk of not replacing legacy systems will exceed the risk of change. It's already happening. Major institutions will let long-standing contracts lapse and implement their newer AI native competitors. Why? The next generation of infrastructure doesn't just add AI. They unify the data from legacy cores, from external systems, from unstructured data into a new system of record, enabling FIS not only to scale, but to take full advantage of AI.

Angela Strange: When this happens, there are three major changes that are important for both customers and builders. One, workflows will finally become parallelized. No more bouncing between screens, cut pasting data. For instance, your mortgage team could see the 400 plus tasks that are needed to underwrite your loan, do them in parallel, and even have agents do some of the more mundane ones for you to check later. Second, the categories as we know them are going to expand. For instance, customer data from onboarding, KYC, KYB, transaction monitoring, even how those customers behave with your customer service team could all sit into a single risk platform. brings together fraud, risk, compliance much more effectively.

Angela Strange: And then third, most excitingly for the builders, the new winners here will be 10x bigger. Not only because those software categories are bigger, but because software is able to consume a lot of the labor that humans didn't want to do anyways or that banks or insurance companies couldn't hire for fast enough. So, as the saying goes, it's not AI that's the competition, it's your competitors using AI. So the best banks, the best insurance companies will fix their plumbing and enable them to take full advantage and be the most competitive going into the next decade.

Angela Strange: Companies have been talking about this for decades. Why is it different now? Primarily three reasons. One, we have to remember that many of these companies still live on mainframes, decades old mainframes, and their systems were already on the verge of breaking with the scale. Two, now companies see that they're leaving a lot of revenue on the table by not being able to take advantage of AI. For instance, in insurance, underwriters sometimes can't even get to the demand that they have because they're not able to process it fast enough. They can't bring in the documents. They can't scan them. This is a huge revenue upside that can be captured if you get the right system and you layer AI on top.

Angela Strange: Third, there are strong viable options of this next generation of AI first software built by entrepreneurs who deeply understand your industry, are deeply technical, and have entirely rearchitected your platforms to one enable you to scale and two be incredibly flexible in terms of how you can add AI on now and in the future. I see a ton of opportunity here and potentially a dramatic reordering of the winners and losers of incumbent companies based on who become the early adopters of some of these new platforms. And we're already seeing it. There's some banks and there's some insurance companies that are starting to get the reputation of being forward thinking, easier to work with, wanting to lean in. And those companies in some areas like mortgage servicing have been able to turn areas of their business from 5% margin businesses to 50% margin businesses. And you imagine doing that across your company as quickly as possible. It's going to make a much bigger difference against your competitor that maybe takes 2 or 3 years to catch up.

Angela Strange: One of the reasons as an investor that I get so excited about infrastructure is that it's beautiful infrastructure that enables beautiful consumer experiences and beautiful business experiences. For instance, why does your bank market products to you that you already have? It's because your customer data sits in all of these different sectors. Why can't customer service agent A answer questions about customer service B if you call in about your banking operations? Now, imagine the future of a unified data layer and incredibly smart people supplemented by agents that can understand your needs, help you with any product you already have, anticipate your needs in the future. That would be a beautiful experience for both customers and businesses.

Angela Strange: In 2026, we're going to see a dramatic acceleration for any company that has built a new AI first platform that sells into this large industry. But the opportunity is massive. So if you are a founder who deeply understands or is deeply curious about any archaic aspect of banking or insurance, the opportunity is now. You can build your software faster and customers are ready to buy.

Sarah Wang: I'm Sarah Wang, general partner on A16Z Growth, and my big idea for 2026 is that systems of record start to lose their edge. A passive system of record layer stops making sense when agents can independently execute on unsigned intent. I expect to see a new dynamic agent layer that actually makes sense for employees to replace legacy systems of record. This is a very exciting development on the long road of inserting intelligence into companies.

Sarah Wang: I don't say that systems of record are losing privacy lightly at all. I used to work at a firm that almost exclusively invested in ERPs and other systems of record because of the stickiness of the data gravity. There was a wave of SAS 2.0 that was wellunded and tried and failed to take on the system of record mostly through a better UI. This is the first time that we've seen a genuine threat to that and that's because the distance between intent and execution is collapsing and that's creating not a 20 to 50% better experience for the user but how you get to that magical TEDex.

Sarah Wang: Let's take the concrete example of ITSM IT service management. This has traditionally been the domain of powerhouse company Service Now. I chatted with a head of IT recently who told me for the first time in his two decade long career he believed that IT support was fundamentally going to change. It will look completely different in 5 years. So why is that? If you think about the way that the old systems work, how long it takes to do something like request access to new software in the firm and you contrast that with the ITSM agents that are arriving. They plug into your stack and this type of request becomes nearly instantaneous.

Sarah Wang: Through advancements in LLM, you can now extract intent. You can classify the request type. You can map it to a known workflow, identify user entities, and the request from the user becomes fulfilled in a way that is efficient and accurate. So, we think there's a couple of valuable layers in this new paradigm. Of course, there's the foundation model layer. We believe that stays valuable. Um, but it's really the emerging agent layer that sits as close as possible to the user and is collecting data on that user, understanding user preferences that we think acrru value in the future.

Sarah Wang: Based on everything that we're seeing in the wild, we believe this is a huge opportunity for new players to come in and win. Why is that? We're in a phase right now where the product is getting better on a weekly, if not daily, basis, and you need teams that move fast. If you're going to collapse intent and execution, what bridges that is actually having an accurate or reliable solution for your customer. Otherwise, they're not going to use it. They're not going to trust the agent that you're building. That's why we're starting to see even agents built on top of classic iconic platforms like Data Dog lose to some of the new AI SRE companies like a Resolve or a Traversal. We're extremely excited about this opportunity and 2026 is going to be the year that the dynamic agent layer overtakes the system of record.