An uncomfortable but clarifying lesson founders are learning in the current cycle of blockchain adoption is that enterprises do not buy the “best” technology. They buy the least disruptive path to progress.
For decades, new enterprise technologies — especially in banking and financial services in the past 10 years — have promised order-of-magnitude improvements over legacy infrastructure: faster settlement, lower costs, cleaner architectures. Yet adoption rarely follows technical merit.
Here’s what this means: If your “better” product isn’t winning, the gap isn’t performance. It’s fit.
This piece is for founders in crypto who cut their teeth building for public blockchain use cases and are now going through the painful process of steering toward enterprise sales — a massive blind spot for many.
Below, we share a few key learnings based on our own experience seeing founders successfully sell to enterprises, and the feedback we hear from those buyers, to help companies better pitch and win with enterprises.
What “best” means
Inside large enterprises, the “best” technology is the one that works with existing systems, approval processes, risk models, and incentive structures.
SWIFT persists despite being slow and expensive. Why? Because it offers shared governance and regulatory comfort. COBOL persists because rewriting stable systems introduces existential risks. Batch file transfers persist because they create clear checkpoints and audit trails.
The (maybe) uncomfortable takeaway is that enterprise blockchain adoption is not blocked by a lack of education or vision. It’s blocked by misaligned product design. Founders who insist on selling the technology at its maximum form will keep running into walls. Founders who treat enterprise constraints as design inputs — not compromises — are the most likely to win.
The opportunity, then, is not to dilute the promise of blockchains but to help technologists package and sell a version that enterprises can actually say yes to by applying the following mindsets.
Enterprises fear downside more than they value upside
A common mistake founders make when pitching enterprises is assuming that decision makers are primarily motivated by upside or the promise of better technology: faster systems, lower costs, cleaner architecture, and so on.
In reality, enterprise buyers are far more motivated to minimize downside risk.
Why? Inside large institutions, the cost of failure is asymmetric. This is the opposite of the mindset in smaller startups, so founders who haven’t worked in large enterprises may miss this. The missed opportunities are rarely punished, while visible mistakes are — especially one tied to new or unfamiliar technology. Those mistakes can meaningfully harm careers, trigger audits, or even invite regulatory scrutiny.
Decision-makers almost never participate directly in the upside of the technology they recommend. Even in cases where there is strategic alignment or corporate-level investment, the upside is diffuse and indirect. The downside, however, is immediate and often personal.
As a result, enterprise decision-making is less shaped by what could work and more by what’s unlikely to fail. This is why many “better” technologies struggle to gain traction. The bar for adoption usually isn’t technical superiority; it’s whether adopting the technology makes the decision maker’s job safer or riskier.
Therefore, you have to reimagine who you think your customer is. One of the most persistent mistakes founders make when selling into enterprises is assuming that the buyer is the person who understands the technology best. In reality, enterprise adoption is less driven by technical conviction and more by organizational dynamics.
Inside large institutions, decisions are shaped less by upside and more by risk management, coordination costs, and accountability. At enterprise scale, most organizations have externalized part of their decision-making process to consulting firms — not because they lack intelligence or expertise, but because key decisions must be consistently validated and defensible. Bringing in a recognized third party provides external validation, distributes accountability, and serves as a credible reference point if the decision is later challenged. This is true across most Fortune 500 companies, which, as a result, carry enormous consulting line items in their annual budgets.
In other words, the larger the institution, the more important it becomes that decisions can survive internal scrutiny after they are made. As the saying goes, “No one gets fired for hiring McKinsey.”
How enterprises actually make decisions
Enterprise decision-making resembles how many individuals use ChatGPT today: We don’t rely on it to make decisions for us. We use it to pressure-test ideas, synthesize tradeoffs, and reduce uncertainty — all while retaining accountability for ourselves.
Enterprises largely behave in the same way, except their decision-support layer is human, not an LLM.
New initiatives must pass through some combination of legal, compliance, risk, procurement, security, and executive oversight. And each layer asks different questions, questions like:
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What could go wrong?
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Who is accountable if it does?
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How does this fit with what already exists?
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How can I explain this decision to the executive team, regulators, or the board?
The result is that for meaningful initiatives — not those siloed within a company’s innovation arm — the customer is rarely a single buyer. The “buyer” is really a coalition of stakeholders, many of whom care more about avoiding mistakes than buying innovation.
This is often where many technically superior products lose — not because they don’t work, but because the right people in the organization can’t safely own the decision to adopt them.
Consider online betting platforms. As prediction markets dominate the zeitgeist, crypto picks and shovels — like on-ramp providers — might look to online sportsbooks as an obvious enterprise target. But to do so, it would be imperative to understand that online sportsbooks operate under a different regulatory framework, including state-by-state licensing, than do prediction markets. Knowing that each state regulator treats crypto differently, an on-ramp provider would understand that its customers aren’t the product, engineering, or business development teams looking to tap into crypto liquidity. Rather, the customers are the legal, compliance, and finance teams that think about the risks to their existing sportsbetting licenses and their core fiat business.
The easiest solution here is to map the decision-makers early and explicitly. Don’t be afraid to ask your product champion (who loves what you have built) how to help them sell internally. Somewhere behind the curtain sit legal, compliance, risk, finance, and security… all with quiet veto power and very different fears. The teams that win learn to package their product as a risk-contained decision, with pre-baked answers and clear upside/downside frameworks for stakeholders. By simply asking, you can learn who you need to package this for, and then carve a path to “yes” that feels boringly safe.
The consultant (and translation) layer
In many cases, before new technology ever reaches an enterprise buyer, it’s filtered through an intermediary. Third parties like consulting firms, systems integrators, and auditors often play a critical role in the translation and legitimation of new technologies. For better or worse, they become the gatekeepers for a new technology. They use established and familiar frameworks and engagement models to turn new solutions into familiar concepts and uncertainty into defensible recommendations.
Founders often view this dynamic with frustration or skepticism, seeing consultants as slowing progress, adding unnecessary process, or acting as auxiliary stakeholders that influence final decisions. And they do! But founders must be realists: In the U.S. alone, the management consulting services market is projected to be worth more than $130 billion in 2026, with the majority of that spend coming from large enterprises seeking help on strategy, risk, and transformation. While blockchain-related work represents only a small fraction of that total, it would be a mistake to assume that just because an initiative involves blockchain, it sits outside these same decision-making channels.
Whether you like this dynamic or not, it has shaped enterprise decision-making for decades. And just because you’re selling blockchain-based initiatives, the dynamic hasn’t gone away. Our experience speaking with Fortune 500 companies, GSIBs, and large asset managers reinforces this reality: Ignoring this layer can be a strategic mistake.
Deloitte’s alliance with Digital Asset illustrates this dynamic: By partnering with a major consulting firm like Deloitte, Digital Asset’s blockchain infrastructure was reframed through a lens far more familiar to enterprise — in this case, governance, risk, and compliance. For institutional buyers, the involvement of a trusted party like Deloitte validated the technology, making the path to adoption far clearer and more defensible.
Don’t run the same pitch everywhere
Because those involved in enterprise decision making are so attuned to their needs — and especially to their downside risk — it’s important to tailor your presentation: Don’t reuse the same enterprise pitch across every lead. The same deck. The same framing and messaging. The same “why now.” The same architecture slide.
But nuance matters. Two large banks may appear similar on paper, but their systems, constraints, and internal priorities often differ meaningfully. What resonates with one may fall flat with another.
A generic pitch signals you haven’t taken the time to understand how this specific institution defines the program. If your pitch isn’t tailored, then, from the institution’s point of view, it’s hard to believe your solution can fit cleanly inside.
Compounding this mistake is the “rip and replace” narrative. In crypto, founders often default to pitching a clean-slate future: One where legacy systems are outright replaced with newer, better decentralized technology that can usher in a new era. Enterprises rarely operate this way. Legacy infrastructure is embedded in workflows across the organization, compliance processes, existing vendor contracts, reporting systems, and many other touchpoints and stakeholders. Replacing legacy infrastructure from scratch not only disrupts the enterprise’s day-to-day operations but also introduces a range of risks and failure points.
The more sweeping the change, the harder it is for someone inside the organization to own the decision: the bigger the decision, the larger the decision-making coalition.
We’ve seen success when founders meet the enterprise where it is, not where they want the enterprise to be. Design entry points that integrate into existing systems and workflows, minimize disruption, and establish a credible wedge.
A recent example of this is Uniswap’s collaboration with BlackRock around its tokenized fund. Rather than framing DeFi as a replacement for traditional asset management, Uniswap enabled permissionless secondary market liquidity for a product issued within BlackRock’s existing regulatory and fund structures. The integration did not require BlackRock to abandon its operating model. It just extended it onchain.
You can focus on expanding to something more ambitious once you’re through the procurement process and your solution is deployed into production.
Enterprises hedge — make sure you’re the right one
This risk aversion often manifests predictably: Institutions hedge. Often, a lot.
Rather than making a single, decisive bet on emerging infrastructure, large enterprises frequently run parallel experiments. They allocate modest budgets across multiple vendors, test competing approaches in innovation departments, or run pilots without committing core systems. From the institution’s view, this preserves optionality while limiting exposure.
For founders, however, this creates a subtle trap. Being selected does not mean being adopted. Many crypto companies become one of several low-conviction hedges. Interesting to trial, not critical enough to scale.
The real objective is not to win a pilot. It is to become the winning hedge. This requires more than just technical merit. It requires professionalism.
Why professionalism beats purity: No hoodies
In these markets, clarity, predictability, and credibility routinely outperform raw innovation: Rarely will you win on technology alone. Because of that, professionalism matters. It reduces uncertainty. By “professionalism”, we mean designing and presenting products that acknowledge institutional realities (think legal constraints, governance processes, and existing systems) and committing to work within them. A convention signals that a product can be governed, audited, and controlled. Regardless of whether this speaks to the ethos of blockchain or crypto, it’s largely how enterprises approach technology adoption.
This approach can seem like an enterprise’s resistance to change. It’s not. It’s a rational response to enterprise incentives.
Focusing on the ideological purity behind the technology — whether around “decentralization,” “trust minimization,” or any other part of the crypto ethos — rarely persuades institutions that operate under legal, regulatory, and reputational constraints. Products that insist enterprises adopt the “full vision” upfront ask too much, too soon.
There are, of course, examples of groundbreaking technology and ideological purity being a winning combination. LayerZero recently introduced Zero, a new L1 blockchain to overcome scalability and interoperability hurdles to enterprise adoption. But it does so while also preserving the industry’s core tenets of decentralization and permissionless innovation.
What differentiates Zero, however, is not just its architecture, but its approach to institutional design. Rather than building a one-size-fits-all network and hoping that enterprises adapt, LayerZero is working with anchor partners to co-design purpose-built “Zones” optimized for specific use cases such as payments, settlement, or capital markets. Zero’s architecture, the team’s willingness to truly co-build around these use cases, and LayerZero’s brand minimize some of the downside concerns for large traditional financial players. These combined factors made them more appealing to institutions like Citadel, the DTCC, and ICE, which all announced as partners.
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The temptation for founders is to interpret enterprise resistance as conservatism, bureaucracy, or lack of vision. While this may be the case sometimes, there’s usually another component at play. Most institutions are not irrational. They are optimized for continuity. They are designed to preserve capital, protect reputations, and survive scrutiny.
The technologies that win in this environment are not always the most elegant or ideologically pure (see Canton, for example). They are the ones who strive to meet the enterprise where they are.
These realities help clarify the long-term potential of blockchain infrastructure in the enterprise.
Enterprise transformation rarely happens in a single leap. Look at the “Digital Transformation” push in the 2010s: Years after the enabling technologies existed, most large organizations were still modernizing core systems, often through large-scale, expensive consulting engagements. Adoption at scale unfolds gradually, in steps, through controlled integration and expansion from proven use cases, not overnight replacement. This is the reality of the enterprise.
The founders who succeed are not the ones who demand the full vision upfront. They are the ones who sequence it.
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