Authored by: Pyrs Carvolth, Christian Crowley, a16z
Compiled by: Chopper, Foresight News
In the current blockchain application cycle, founders are learning an unsettling yet profound lesson: enterprises do not buy the 'best' technology; they buy the least disruptive upgrade path.
For decades, new enterprise-grade technologies have promised orders-of-magnitude improvements over legacy infrastructure: faster settlement, lower costs, cleaner architecture. But the implementation reality rarely matches the technical advantages.
This means: if your product is 'clearly better' but doesn't win, the gap isn't in performance, but in product-market fit.
This article is written for a group of crypto founders: those who started in the public chain space and are now painfully pivoting to enterprise business. For many, this is a huge blind spot. Below, we share key insights based on our own experience, case studies of founders who successfully sold to enterprises, and real feedback from enterprise buyers to help you better pitch to enterprises and secure deals.
What Does 'Best" Really Mean
Within large enterprises, the 'best technology' is the one that perfectly aligns with existing systems, approval processes, risk models, and incentive structures.
SWIFT is slow and expensive, yet it still stands. Why? Because it provides shared governance and regulatory security. COBOL is still used because rewriting a stable system introduces existential risk. Batch file transfers persist because they create clear checkpoints and audit trails.
An uncomfortable conclusion might be: the slow adoption of blockchain by enterprises is not due to a lack of education or vision, but product misalignment. Founders who insist on selling the most perfect technological form will keep hitting walls. Founders who treat enterprise constraints as design inputs rather than compromises are the ones most likely to succeed.
So, don't downplay the value of blockchain; the key is to help technical teams package a version that enterprises can accept, which requires the following approaches.
Enterprises Fear Loss Far More Than They Love Gain
A common mistake founders make when pitching to enterprises is assuming decision-makers are primarily driven by gains: better technology, faster systems, lower costs, cleaner architecture, etc.
The reality is that the core motivation for enterprise buyers is to minimize downside risk.
Why? In large institutions, the cost of failure is asymmetric. This is the complete opposite of small startups, a point easily overlooked by founders who haven't worked in big corporations. Missing an opportunity is rarely punished, but a visible mistake (especially one related to unfamiliar new technology) can severely impact career prospects, trigger audits, or even invite regulatory scrutiny.
Decision-makers rarely benefit directly from the technology they recommend. Even if strategically aligned and funded at the company level, the gains are dispersed and indirect. But losses are immediate and often personal.
The result is that enterprise decisions are rarely driven by 'what might be achieved' but more by 'what is unlikely to fail.' This is why many 'better' technologies struggle to gain traction. The barrier to entry is usually not technical superiority, but rather: does using this technology make the decision-maker's job safer or riskier?
Therefore, you must rethink: who is your real customer? One of the most common mistakes founders make in enterprise sales is thinking the 'most technically savvy person' is the buyer. The reality is, enterprise adoption is rarely driven by technical belief, but more by organizational dynamics.
In large institutions, decisions are less about gains and more about risk management, coordination costs, and accountability. At an enterprise scale, 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 validation, distributes responsibility, and offers credible justification if the decision is later questioned. This is true for most Fortune 500 companies, hence the huge annual consulting budgets.
In other words: the larger the institution, the more decisions must withstand internal scrutiny after the fact. As the saying goes, 'Nobody ever got fired for hiring McKinsey.'
How Enterprises Actually Make Decisions
Enterprise decision-making is a lot like how many people use ChatGPT today: we don't use it to make the decision for us, but to test ideas, weigh pros and cons, reduce uncertainty, while always remaining accountable.
Enterprises behave largely the same, except their decision support layer is people, not a large language model.
New decisions must pass through layers of legal, compliance, risk, procurement, security, executive oversight, etc. Each layer cares about different questions, such as:
- What could go wrong?
- Who is responsible if something goes wrong?
- How does this integrate 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 care more about not making mistakes than innovating.
Many technically superior products often lose here: not because they are unusable, but because there is no suitable person within the organization who can use them safely.
Take the example of an online gambling platform. As prediction markets gain popularity, crypto 'picks and shovels' providers (like on-ramp service providers) might see online sports betting platforms as natural enterprise clients. But to do this, you must first understand: the regulatory framework for online sports betting is different from prediction markets, including separate licenses per state. Knowing that states have different attitudes towards crypto, the on-ramp provider would realize: its customer is not the product, engineering, or business team wanting to access crypto liquidity, but the legal, compliance, and finance teams, who care about the risk to existing gambling licenses and core fiat business.
The simplest solution is to identify the decision-makers early and explicitly. Don't be afraid to ask your product champion (the person who likes your product) how to help them sell internally. Behind the scenes, there are often legal, compliance, risk, finance, security... they all have hidden veto power and vastly different concerns. Winning teams package their product as a risk-managed decision, giving stakeholders ready-made answers and a clear benefit/risk framework. Just by asking, you can find out who to package for, and then find a seemingly safe and reassuring path to 'yes'.
Consulting Firms
Often, new technology reaches enterprise buyers through an intermediary layer first. Third parties like consulting firms, system integrators, and auditors often play a key role in translating and legitimizing new technology. Like it or not, they become the gatekeepers of new technology. They use mature, familiar frameworks and engagement models to translate new solutions into familiar concepts, turning uncertainty into actionable advice.
Founders are often frustrated or skeptical of this, feeling consultants slow progress, add unnecessary processes, and become additional interested parties influencing the final decision. They do! But founders must be realistic: in the US alone, the management consulting services market is projected to exceed $130 billion by 2026, mostly from large enterprises seeking help with strategy, risk, and transformation. While blockchain-related business is only a small part, don't assume a project with 'blockchain' can bypass this decision-making system.
Like it or not, this model has influenced enterprise decisions for decades. Even if you're selling a blockchain solution, this logic won't disappear. Our experience talking with Fortune 500 companies, large banks, and asset managers repeatedly proves: ignoring this layer can be a strategic mistake.
The partnership between Deloitte and Digital Asset is a classic example: by partnering with a major consulting firm like Deloitte, Digital Asset's blockchain infrastructure was repackaged into language more familiar to enterprises, like governance, risk, and compliance. For institutional buyers, the participation of a trusted party like Deloitte both validates the technology and 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 risk), you must customize your pitch: don't use the same enterprise sales pitch, the same deck, 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 worlds apart. What works for one may be completely ineffective for the other.
A generic pitch tells the other party: you haven't taken the time to understand how this institution specifically defines the project. If your pitch isn't tailored, it's hard for the institution to believe your solution can be a perfect fit.
An even more serious mistake: the 'rip and replace' narrative. In crypto, founders often tend to paint a picture of a completely new future: completely replacing old systems, ushering in a new era with newer, better decentralized technology. But enterprises rarely do this. Legacy infrastructure is deeply embedded in workflows, compliance processes, existing vendor contracts, reporting systems, and countless touchpoints and stakeholders. Rip and replace doesn't just disrupt daily operations; it introduces all sorts of risks.
The broader the scope of change, the less likely anyone inside the organization will dare to approve it: the bigger the decision, the larger the decision-making coalition.
The success stories we've seen are where founders first adapt to the enterprise client's current state, rather than asking the client to adapt to their ideal. When designing the entry point, it should integrate into existing systems and workflows, minimize disruption, and establish a reliable foothold.
A recent example is the collaboration between Uniswap and BlackRock on tokenized funds. Uniswap did not position DeFi as a replacement for traditional asset management, but rather provided permissionless secondary market liquidity for products issued under BlackRock's existing regulatory and fund structure. This integration did not require BlackRock to abandon its operating model; it simply extended it on-chain.
Once you're through the procurement process and the solution is live, there's plenty of time to pursue more ambitious goals later.
Enterprises Hedge Their Bets, You Need to Be the 'Right Hedge'
This risk aversion manifests as a predictable behavior: institutions hedge their bets, and often on a large scale.
Large enterprises don't bet the farm on emerging infrastructure. Instead, they run multiple experiments simultaneously. Allocate small budgets to multiple vendors, test various solutions in innovation departments, or run pilots without touching core systems. From the institution's perspective, 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 for enterprises to test the waters; a pilot is fine, but there's no need to scale.
The real goal is not to win a pilot, but to be the hedge with the highest probability of winning. This requires more than just technical superiority; it requires professionalism.
Why Professionalism Trumps Purity
In these markets, clarity, predictability, and credibility usually trump pure innovation: technology alone rarely wins. This is why professionalism is crucial; it reduces uncertainty.
By professionalism, we mean: designing and presenting the product with full consideration of institutional realities (e.g., legal constraints, governance processes, and existing systems) and committing to operate within these reality frameworks. Following conventions tells the other party: this product is governable, auditable, and controllable. Whether this aligns with the spirit of blockchain or crypto, this is how enterprises view technology implementation.
This may seem like enterprises resisting change, but it's not. It's a rational response to enterprise incentives.
Getting hung up on the ideological purity of the technology, be it 'decentralization,' 'minimal trust,' or other crypto ethos, is difficult to sell to institutions bound by legal, regulatory, and reputational constraints. Products that demand the 'full vision' accepted all at once ask too much, too soon.
Of course, there are examples of breakthrough technology + ideological purity winning. LayerZero recently launched a new chain, Zero, attempting to solve scalability and interoperability challenges for enterprise adoption while preserving the core principles of decentralization and permissionless innovation.
But Zero's real differentiator is not just architecture, but institutional design thinking. Instead of building a one-size-fits-all network and expecting enterprises to adapt, it co-designs dedicated 'Zones' for specific scenarios like payments, settlement, and capital markets with core partners.
Zero's architecture, the team's willingness to truly collaborate around these application scenarios, and the LayerZero brand all help minimize some concerns of large traditional financial institutions. These factors combined led to Citadel, DTCC, ICE, and other institutions announcing partnerships.
Founders can easily interpret enterprise resistance as conservatism, bureaucracy, or lack of vision. Sometimes it is, but there's usually another reason: most institutions are not irrational; they are designed for operational continuity. They are designed to preserve capital, protect reputation, and withstand scrutiny.
The technology that wins in this environment is not necessarily the most elegant or ideologically purest, but the one that strives to adapt to the enterprise's current state.
These realities help us see the long-term potential of blockchain infrastructure in the enterprise space.
Enterprise transformation is rarely overnight. Look at the 'digital transformation' of the 2010s: although the technology existed for years, most large enterprises are still modernizing their core systems, often at great cost and with the help of consulting firms. Large-scale digital transformation is a gradual process, achieved through controlled integrations and scaling based on mature use cases, not a wholesale replacement overnight. This is the reality of enterprise transformation.
Successful founders are not those who demand the full vision upfront, but those who understand phased implementation.
