In the current blockchain application cycle, founders are learning an unsettling but profound lesson: enterprises don’t buy the “best” technology; they buy the upgrade path with the least disruption. For decades, new enterprise-level technologies have promised orders-of-magnitude improvements over traditional infrastructure: faster settlement, lower costs, and cleaner architecture. But the actual implementation rarely fully matches the technological advantages. This means that if your product is “obviously better” but can’t win, the gap isn’t in performance but in product-market fit.

This article is written for a group of crypto founders who started in the public chain space and are now painfully transitioning to enterprise-level business. For many, this is a huge blind spot. Below, we’ll share some key insights based on our own experience, cases of founders successfully selling products to enterprises, and real feedback from enterprise buyers to help you better market to enterprises and win deals.

What does “best” really mean? Within large enterprises, the “best technology” is technology that is perfectly compatible with existing systems, approval processes, risk models, and incentive structures. SWIFT is slow and expensive, yet it still stands strong. Why? Because it provides shared governance and regulatory security. COBOL is still used because rewriting stable systems carries existential risks. Batch file transfers still exist because they create clear checkpoints and audit trails.

A potentially uncomfortable conclusion is that the obstacle to enterprise blockchain adoption isn’t a lack of education or vision but a misalignment of product design. Founders who insist on pushing the most perfect technological form will constantly run into walls. Founders who treat enterprise constraints as design inputs rather than compromises are most likely to succeed. So, there’s no need to downplay the value of blockchain; the key is to help the technology team package a version that enterprises can accept.

Enterprises fear losses far more than they love gains. When founders market to enterprises, they often make the mistake of thinking that decision-makers are primarily driven by gains: better technology, faster systems, lower costs, cleaner architecture, and so on. The reality is that the core motivation of enterprise buyers is to minimize downside risk. In large organizations, the cost of failure is asymmetrical. This is the complete opposite of small startups, a point that founders who haven’t worked in large corporations easily overlook. Missing opportunities rarely results in punishment, but obvious mistakes (especially those related to unfamiliar new technologies) can severely impact career prospects, trigger audits, and even invite regulatory scrutiny.

Decision-makers rarely directly benefit from the technologies they recommend. Even if there’s strategic alignment and investment at the company level, the gains are dispersed and indirect. But the losses are immediate and often personal. As a result, enterprise decisions are rarely driven by “what could be achieved” but more by “what is unlikely to fail.” This is why many “better” technologies struggle to gain traction. The barrier to implementation is usually not technological leadership but whether using the technology will make the decision-maker’s job safer or more dangerous.

So, you must rethink who your customer is. One of the most common mistakes founders make when doing enterprise sales is assuming that the “most technically savvy person” is the buyer. The reality is that enterprise implementation is rarely driven by technological conviction but more by organizational dynamics. In large organizations, decisions are less about gains and more about risk management, coordination costs, and accountability. At the enterprise level, most organizations outsource part of the decision-making process to consulting firms, not because they lack intelligence or expertise but because key decisions must be continuously validated and defensible. Bringing in a well-known third party provides external endorsement, distributes responsibility, and provides credible evidence if the decision is later questioned. Most Fortune 500 companies operate this way, hence the huge consulting fees in their annual budgets. In other words, the larger the organization, the more the decision must withstand internal scrutiny after the fact. As the saying goes, “No one ever got fired for hiring McKinsey.”

How exactly do enterprises make decisions? Enterprise decision-making is much like how many people use ChatGPT now: we don’t let it make decisions for us; we use it to test ideas, weigh pros and cons, and reduce uncertainty while remaining responsible ourselves. Enterprises behave in much the same way, except their decision support layer is people, not large models. New decisions must pass through layers of legal, compliance, risk, procurement, security, and executive oversight. Each layer is concerned with different issues, such as: What could go wrong? Who is responsible if something goes wrong? How does this fit with existing systems? How do I explain this decision to executives, regulators, or the board? Therefore, for truly meaningful innovation projects, the “customer” is almost never a single buyer. The so-called “buyer” is actually a coalition of stakeholders, many of whom are more concerned with avoiding mistakes than with innovating.

Many technologically superior products often lose out here: not because they can’t be used but because there isn’t a suitable person in the organization who can use them safely. Take online gambling platforms as an example. As prediction markets become popular, crypto “water sellers” (such as deposit channel service providers) may see online sports betting platforms as natural enterprise customers. But to do so, you must first understand that the regulatory framework for online sports betting is different from that for prediction markets, including separate licenses for each state. Knowing that state regulations have different attitudes toward crypto, deposit service providers will understand that their customers are not the product, engineering, or business teams that want to integrate crypto liquidity but the legal, compliance, and finance teams, who are concerned about the risks to existing gambling licenses and core fiat currency business. The simplest solution is to clearly identify the decision-makers as early as possible. Don’t be afraid to ask your product supporters (people who like your product) how they can help you market it internally. Behind the scenes, there are often legal, compliance, risk, finance, security… They all have undisclosed veto power and have very different concerns. Winning teams will package the product as a risk-controlled decision, giving stakeholders ready-made answers and a clear benefit/risk framework. Just ask, and you’ll know who to package for and then find a seemingly safe yet reassuring path to “agreement.”

Consulting firms often act as intermediaries before new technologies reach enterprise buyers. Consulting firms, system integrators, auditors, and other third parties often play a key role in the transformation and legitimization of new technologies. Whether you like it or not, they have become the gatekeepers of new technologies. They use mature, familiar frameworks and collaboration models to transform new solutions into familiar concepts and turn uncertainty into actionable recommendations. Founders often feel frustrated or skeptical about this, feeling that consulting firms slow down progress, add unnecessary processes, and become additional stakeholders influencing the final decision. They do! But founders must be realistic: in the United States alone, the management consulting services market is projected to exceed $130.00B in 2026, most of which comes from large enterprises seeking help with strategy, risk, and transformation. Although blockchain-related business accounts for only a small portion, don’t assume that a project with “blockchain” in its name can escape this decision-making system. Whether you like it or not, this model has influenced enterprise decision-making for decades. Even if you’re selling a blockchain solution, this logic won’t disappear. Our experience communicating with Fortune 500 companies, large banks, and asset management firms has repeatedly proven that ignoring this layer can lead to strategic errors. The collaboration between Deloitte and Digital Asset is a typical example: through collaboration with large consulting firms like Deloitte, Digital Asset’s blockchain infrastructure is repackaged into a language that enterprises are more familiar with, such as governance, risk, and compliance. For institutional buyers, the involvement of trusted parties like Deloitte not only validates the technology but also makes the implementation path clearer and more defensible.

Don’t use the same pitch. Because enterprise decision-makers are extremely sensitive to their own needs (especially downside risks), you must customize your presentations: don’t use the same enterprise sales pitch, the same PPT, or the same framework for every potential customer. Details matter. Two large banks may look similar on the surface, but their systems, constraints, and internal priorities can be vastly different. What impresses one may be completely ineffective for another. A generic pitch is equivalent to telling the other party that you haven’t taken the time to understand the institution’s specific definition of the project. If your pitch isn’t tailored, institutions will find it difficult to believe that your solution can be a perfect fit.

An even more serious mistake is the “tear it all down and start over” argument. In the crypto space, founders often tend to paint a completely new future: completely replacing old systems and ushering in a new era with newer, better decentralized technologies. But enterprises rarely do this; traditional infrastructure is deeply embedded in workflows, compliance processes, existing vendor contracts, reporting systems, and countless touchpoints and stakeholders. Tearing it all down and starting over not only disrupts daily operations but also introduces various risks. The wider the impact of the change, the less likely anyone in the organization will dare to make a decision: the bigger the decision, the bigger the decision coalition. The successful cases we’ve seen are all founders who adapt to the enterprise customer’s current situation rather than asking the customer to adapt to their ideals. When designing entry points, be able to integrate into existing systems and workflows, minimize disruption, and establish reliable entry points. A recent example is Uniswap’s collaboration with BlackRock on tokenized funds. Uniswap didn’t position DeFi as a replacement for traditional asset management but provided permissionless secondary market liquidity for products issued under BlackRock’s existing regulatory and fund structure. This integration doesn’t require BlackRock to abandon its operating model; it simply extends it to the chain. Once you’ve gone through the procurement process and the solution is officially launched, there’s plenty of time to pursue more ambitious goals.

Enterprises will hedge their bets; you need to be the “right hedge.” This risk aversion manifests itself as a predictable behavior: institutions will hedge their bets, often on a large scale. Large enterprises don’t bet everything on emerging infrastructure; they conduct multiple experiments simultaneously. They allocate small budgets to multiple vendors, test multiple solutions in innovation departments, or conduct pilots without touching core systems. In the eyes of institutions, this preserves optionality while limiting risk exposure. But for founders, there’s a subtle trap here: being selected ≠ being adopted. Many crypto companies are just one of the options that enterprises use to test the waters; pilots are fine, but there’s no need to scale them up. The real goal isn’t to win a pilot but to become the hedge with the highest probability of winning. This requires not only technological advantages but also professionalism.

Why does professionalism trump purity? In these types of markets, clarity, predictability, and credibility usually crush pure innovation: it’s difficult to win on technology alone. That’s why professionalism is so important; it reduces uncertainty. By professionalism, we mean designing and presenting products with full consideration of institutional realities (such as legal constraints, governance processes, and existing systems) and committing to operating within these realistic frameworks. Following conventions is equivalent to telling the other party that the product is governable, auditable, and controllable. Whether or not this aligns with the blockchain or crypto ethos, this is how enterprises view technology implementation. This may seem like enterprises are resisting change, but it’s not. It’s a rational response to enterprise incentive mechanisms. Dwelling on the ideological purity behind the technology, whether it’s “decentralization,” “minimum trust,” or other crypto ethos, makes it difficult to persuade institutions bound by law, regulation, and reputation. Products that require enterprises to accept the “complete vision” in one go are too demanding and overreaching.

Of course, there are also examples of breakthrough technology + ideological purity winning together. LayerZero recently launched a new public chain, Zero, in an attempt to solve the scaling and interoperability challenges in enterprise implementation while retaining the core principles of decentralization and permissionless innovation. But Zero’s real difference isn’t just the architecture but the institutional design thinking. Instead of creating a one-size-fits-all network and expecting enterprises to adapt, it co-designed dedicated “Zones” with core partners for specific scenarios such as payments, settlement, and capital markets. Zero’s architecture, the team’s willingness to truly collaborate around these application scenarios, and LayerZero’s brand all minimize some of the concerns of large traditional financial institutions. These factors combined have led institutions such as Citadel, DTCC, and ICE to announce their partnerships.

Founders easily interpret enterprise resistance as conservatism, bureaucracy, and a lack of vision. Sometimes this is the case, but there’s usually another reason: most institutions aren’t irrational; they all aim to maintain operations. Their design goals are to preserve capital, protect reputation, and withstand scrutiny. The technologies that win in this environment aren’t necessarily the most elegant or ideologically pure but the technologies that strive to adapt to the enterprise’s current situation. These realities help us see the long-term potential of blockchain infrastructure in the enterprise space. Enterprise transformation rarely happens overnight. Look at the “digital transformation” of the 2010s: although the relevant technologies have been around for years, most large enterprises are still modernizing their core systems, often at great expense by hiring consulting firms. Large-scale digital transformation is a gradual process that requires controlled integration and expansion based on mature use cases, rather than a complete replacement overnight. This is the reality of enterprise transformation. Successful founders aren’t those who demand a complete vision from the start but those who know how to implement it step by step. [Foresight News]