Three Sources of AI Capability. Only One Creates Advantage.
When it comes to AI, companies have no shortage of asks. They have big visions. Big ideas. Transformation. But they have no idea how to go from where they are to where they want to be. The topics covered in previous articles in this series (automation or strategy, three types of feasibility) should provide enough clarity for firms to get a good idea of what’s required to execute on an idea. The next step is to determine how that execution is going to happen, namely where is the capability going to come from?
There are three main sources of technology that we consider: 1) industry agnostic software, 2) internal development, 3) external, third-party integration providers. There are some nuances to each of these, but these three categories provide a good starting point. Almost every organization should have a mix of these sources. Each plays a different role within a company’s technology ecosystem and should be used selectively depending on the type of functionality the company is pursuing.
A large majority of companies in real estate have defaulted to external vendors or generic tools without considering whether those products will actually solve their problems. I not only think this is a huge mistake for competitive reasons, but I think we’ve seen little evidence that this approach is providing meaningful value to real estate companies.
Industry Agnostic Applications
The first category is what we call “industry agnostic” functions. These are functions such as accounting, HR, and others that are necessary for the operation of the business, but are not core to the strategy of the business and offer no competitive advantage one way or the other. It’s not likely that a customer/client will choose your real estate company over another because of the backend accounting or HR software you have. Most of these functions apply to every business regardless of the industry and there are standardized solutions from large vendors that should suit your purposes just fine. So it doesn’t make much sense for a firm to pursue the development of these kinds of tools internally. Just buy a good one, integrate it, and don’t waste any more time than necessary getting it up and running.
Internal Development
This area, in my opinion, is what every firm should be focused on. Capabilities that are core to how a company competes, how it provides value, and how it differentiates itself from competitors should always be developed internally (see next section as to WHY these should be developed internally). These include decision-making systems, investment models, portfolio analytics, and other tools that capture the firm’s proprietary knowledge and strategy. Internal tools embed the nuances of how a company evaluates opportunities, manages risk, allocates capital, and optimizes the products/services it provides to clients. Since competitive advantage depends on doing something better or differently than competitors, relying on external tools limits that differentiation. Even highly sophisticated vendor solutions are often sold broadly across the industry, which reduces their ability to create any kind of sustained advantage.
External, Third-Party Integration Providers
This group plays an intermediate role in the ecosystem and includes categories such as data providers, cloud infrastructure, visualization tools, etc. that serve to enhance the functionality of internally developed systems. For example, purchasing geospatial data from a specialized vendor may be far more efficient than building that dataset internally. Likewise, a visualization tool could allow a firm to integrate data from many different sources into something that is more efficient. There are many ways the core functionalities will need to be “glued together,” and external tools are a great way to fill those gaps. However, the analysis and decision logic built on top of that data should remain internal to preserve differentiation. In this sense, external tools function as building blocks within a larger internally developed proprietary systems.
The Strategic Importance of Internal Capabilities
There are three primary reasons internal technology capabilities should form the foundation of an organization’s AI strategy: company strategy, competitive advantage, and integration infrastructure. First, no external provider understands a firm’s business model, decision-making processes, and strategic priorities as well as internal teams. Tools built externally are highly unlikely to capture all the little nuances and details that drive performance in real estate investing and operations. We often hear firms say something like, “It’s ok, but it doesn’t give us flexibility.” No external vendor is going to be able to understand and replicate the intuitive way your firm does business. This is not a criticism of external vendors, it’s just not reasonable to expect someone outside your firm to understand the firm as well as the people inside. And this gap will be reflected in the performance of externally developed tools.
Second, competitive advantage depends on proprietary capabilities. Using the same tools and capabilities as everyone else limits differentiation and reduces the potential for superior performance. For example, let’s say you’re a multifamily investor and I’m a software company that has built the most amazing acquisitions software that has ever existed. Everyone, hands down, says this is the best acquisitions software in the universe. So you decide to subscribe to this acquisitions software. Now, as a software company, what am I going to do as soon as I walk out of your office? Yep, I’m going to go to every other multifamily investment firm (who are all your competitors, by the way) and try to sell them the exact same software. And then the next competitor, and the next, etc. By the time I’m done, every multifamily investor will have this software and there will be little competitive advantage left. So you’ll end up paying more for this software without substantial benefits.
Third, developing internal capabilities create the infrastructure needed to integrate additional technologies effectively. Real estate firms, for some reason, are notorious for wanting to jump to “outcomes” and “models.” They say, “We don’t have three years for foundations, how do we get to value tomorrow?” Funny thing is that six years later they’re still saying the same thing and haven’t improved much. Skipping the data and infrastructure foundations (data collection, storage, processing, etc.) and expecting to be able to develop “models” is like building the 20th floor of a building before building the previous 19 floors and the foundation. Suggest to a developer that they develop the 20th floor first, in place in the sky, before the previous 19 and they’ll look at you like you’re a complete idiot. They’re right, but it goes both ways when a company tries to skip the technical foundations. This can be attributed to the lack of knowledge about technology and AI fundamentals within the real estate industry.
Why are these foundations important? Without a strong technical infrastructure, AI and machine learning capabilities are going to be extremely limited because of data constraints. There just isn’t enough clean, available data to develop and implement AI at scale throughout the organization. Additionally, without internal systems in place, integrating external tools becomes difficult and costly. Each new dataset or third-party application requires custom integration into clunky legacy systems, increasing complexity, time, and cost, thereby reducing the value of that application. Conversely, firms with strong internal infrastructure can rapidly integrate new technologies, making external providers more useful and cost-effective. In this way, internal development does not replace external solutions; it actually enables them and increases their value to the firm.
Think of the difference between internal infrastructure and external tools like apps on the iPhone. The iOS on iPhone provides the infrastructure that makes it easy to build and integrate (install) apps on your phone. How long would it take app developers to develop apps (and how much more would they cost) if each one of them had to also build the operating system for those apps to run on? We probably wouldn’t have many apps. The foundation provides the ease-of-use for many individual apps.
An “Internal” Caveat
There is one caveat that we’ve found to the “develop it internally” rule and that’s the barrier to entry/replication. I have to give credit to Ed Hinchey from Fisher Brothers for this one. He brought this up in the course of Columbia’s “AI in Real Estate” course and it led to a very interesting discussion. The debate was around whether a company should build something internally, even if it is core to their operations, if it can then easily be replicated by another firm or external vendor and distributed widely.
The first time a capability is developed usually takes much longer than it does for someone else to replicate it once the challenges and solutions have been discovered. So if a capability is thought to be easy to replicate once it’s developed, even if it is strategically important to the firm, it might be better to try to find it externally or support the development of it externally.
However, capabilities with high barriers to entry - those requiring significant expertise, data, or infrastructure - are more likely to generate that sustainable competitive advantage when developed internally. Differentiation arises from creating systems that competitors cannot easily copy. Therefore, companies should prioritize internal development for high-value capabilities that are difficult to replicate.
AI Strategies Should Be Broad and Flexible
Real estate companies should not rely exclusively (or primarily) on startups or external vendors to build digital capabilities. While third-party providers play an important role, the overall technology strategy should be driven and developed internally. Internal systems should provide the architecture and the foundation, while external tools provide specialized components as “plug-ins.” This approach allows firms to “pull” high-value technologies into their ecosystem rather than passively adopting vendor-driven solutions.
A disciplined sourcing strategy also helps avoid adopting tools that appear promising but fail to integrate effectively or deliver meaningful value. By prioritizing internal capabilities and selectively incorporating external tools, companies can build a coherent technology stack aligned with their objectives. Over time, this balanced approach enables firms to develop proprietary internal intelligence, maintain flexibility in continuously improving their AI capabilities, and leverage the broader technology ecosystem more effectively.
Keep in mind that everything discussed above are guidelines, but technology decisions rarely fall into clear-cut categories. Most decisions will require understanding the gray areas where multiple approaches are viable. Companies must therefore develop the expertise to analyze every project and every part of a project on a case-by-case basis and maintain flexibility in their decisions. The appropriate choice often depends on available resources, existing infrastructure, and strategic priorities. Rather than applying rigid rules, firms should consider sourcing decisions within the broader context of their technology roadmap.
Ultimately, evaluating sources of technology should not simply be a purchasing decision. Every decision should be made within the larger ecosystem as a strategic choice that shapes how organizations build capabilities, differentiate themselves, and capture value from artificial intelligence.