a16z: The best technology doesn’t necessarily win in the enterprise market.
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a16z: The best technology doesn’t necessarily win in the enterprise market.
Enterprises don’t buy the “best” technology—blockchain adoption hinges on suitability.
Navigating Web3 tides with focused insightsBy Pyrs Carvolth and Christian Crowley
Translated by Chopper, Foresight News
In today’s blockchain application cycle, founders are learning an unsettling yet profound lesson: enterprises don’t buy the “best” technology—they buy the upgrade path that causes the least disruption.
For decades, new enterprise-grade technologies have promised order-of-magnitude improvements over legacy infrastructure: faster settlement, lower costs, cleaner architectures. Yet real-world adoption rarely matches these technical advantages.
That means: if your product is “objectively better” yet fails to win, the gap isn’t in performance—it’s in product-market fit.
This article is written for a specific group of crypto founders: those who launched from public-chain use cases and are now struggling to pivot into enterprise business. For many, this represents a massive blind spot. Drawing on our own experience, case studies of founders who successfully sold products to enterprises, and direct feedback from enterprise buyers, we share several key insights to help you pitch more effectively—and close deals.
What Does “Best” Actually Mean?
Inside large enterprises, “the best technology” is the one that seamlessly integrates with existing systems, approval workflows, risk models, and incentive structures.
SWIFT is slow and expensive—yet it endures. Why? Because it delivers shared governance and regulatory confidence. COBOL remains in use—not because it’s modern, but because rewriting stable systems introduces existential risk. Batch file transfers persist because they generate clear checkpoints and audit trails.
An uncomfortable conclusion follows: enterprise blockchain adoption stalls not due to lack of education or vision—but due to misaligned product design. Founders who insist on selling the most technically perfect architecture will repeatedly hit walls. Founders who treat enterprise constraints as design inputs—not compromises—are far more likely to succeed.
So don’t dilute blockchain’s value. Instead, repackage the technology so enterprises can adopt it comfortably. That requires the following mindsets.
Enterprises Fear Loss Far More Than They Love Gain
Founders often make a critical mistake when pitching to enterprises: assuming decision-makers are primarily motivated by upside—better tech, faster systems, lower costs, cleaner architectures, etc.
The reality is that enterprise buyers’ core motivation is minimizing downside risk.
Why? In large institutions, the cost of failure is asymmetric—exactly the opposite of startups. Founders without prior experience at major corporations frequently overlook this. Missing an opportunity rarely draws punishment; but making a visible mistake—especially one tied to unfamiliar new technology—can derail careers, trigger audits, or even attract regulatory scrutiny.
Decision-makers almost never receive direct personal benefit from recommending a given technology. Even when strategic alignment exists and corporate-level investment is approved, benefits are diffuse and indirect. Losses, however, are immediate—and often personal.
The result? Enterprise decisions are rarely driven by “what could be achieved,” and far more often by “what is unlikely to fail.” That’s why many “superior” technologies struggle to scale. The barrier to adoption is seldom technical superiority—it’s whether adopting the technology makes the decision-maker’s job safer or riskier.
So you must rethink: Who is your real customer? One of the most common mistakes founders make in enterprise sales is assuming that “the person who understands the technology best” is the buyer. In reality, enterprise adoption is rarely driven by technical conviction—it’s driven by organizational dynamics.
In large institutions, decisions hinge less on upside and more on risk management, coordination costs, and accountability. At enterprise scale, most organizations outsource part of their decision process to consulting firms—not because they lack intelligence or expertise, but because critical decisions must be continuously validated and defensible. Bringing in a reputable third party provides external validation, distributes responsibility, and offers credible justification if the decision is later questioned. Most Fortune 500 companies operate this way—and allocate massive annual budgets to consulting services accordingly.
Put simply: the larger the institution, the more its decisions must withstand internal post-hoc scrutiny. As the saying goes: “No one was ever fired for hiring McKinsey.”
How Enterprises Actually Make Decisions
Enterprise decision-making resembles how many people use ChatGPT today: we don’t ask it to decide for us—we use it to test ideas, weigh trade-offs, reduce uncertainty, while retaining ultimate responsibility ourselves.
Enterprises behave similarly—except their decision-support layer consists of people, not large language models.
Any new decision must pass through legal, compliance, risk, procurement, security, and executive oversight gates. Each layer asks different questions, such as:
- What could go wrong?
- Who is accountable 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 any meaningful innovation initiative, the “customer” is almost never a single buyer. Rather, the “buyer” is a coalition of stakeholders—many of whom care far more about avoiding errors than driving innovation.
Many technically superior products lose precisely here: not because they’re unusable, but because no one inside the organization can safely deploy them.
Take online sports betting platforms as an example. As prediction markets gain traction, crypto “pick-and-shovel” providers (e.g., deposit-onboarding service providers) may see online sportsbooks as natural enterprise customers. But doing so requires understanding a crucial distinction: the regulatory framework for online sports betting differs significantly from that of prediction markets—including separate state-by-state licensing requirements. Knowing that states vary widely in their stance toward crypto, onboarding providers realize their true customers aren’t the product, engineering, or business teams eager to integrate crypto liquidity—but rather the legal, compliance, and finance teams, whose primary concern is safeguarding existing gaming licenses and core fiat operations.
The simplest solution is to identify decision-makers early and explicitly. Don’t hesitate to ask your internal champions—those who love your product—how they plan to advocate for it internally. Behind the scenes stand legal, compliance, risk, finance, and security teams—each holding quiet veto power and distinct concerns. Winning teams repackage their product as a low-risk decision, giving stakeholders ready-made answers and a clear benefit/risk framework. Just asking reveals who needs what—and helps you chart a path to “yes” that feels both prudent and reassuring.
Consulting Firms
Often, new technologies reach enterprise buyers only after passing through an intermediary layer. Consulting firms, systems integrators, auditors, and other third parties play a pivotal role in translating and legitimizing emerging technologies. Whether you like it or not, they’ve become gatekeepers. Using mature, familiar frameworks and collaboration models, they recast novel solutions in recognizable terms—transforming uncertainty into actionable recommendations.
Founders often feel frustrated or skeptical about this, viewing consultants as slowing progress, adding unnecessary steps, or inserting themselves as additional stakeholders influencing final decisions. And yes—they do exactly that! But founders must stay grounded: in the U.S. alone, the management consulting services market is projected to exceed $130 billion by 2026, driven largely by large enterprises seeking support on strategy, risk, and transformation. While blockchain-related work represents only a small slice, don’t assume slapping “blockchain” on your project lets you bypass this system entirely.
Whether you like it or not, this model has shaped enterprise decisions for decades—and won’t vanish just because you’re selling blockchain. Our repeated conversations with Fortune 500 companies, major banks, and asset managers confirm: ignoring this layer risks a strategic misstep.
Deloitte’s partnership with Digital Asset is a textbook example: by collaborating with a firm like Deloitte, Digital Asset’s blockchain infrastructure was reframed in enterprise-friendly language—centered on governance, risk, and compliance. For institutional buyers, participation by trusted entities like Deloitte validates the technology and clarifies the implementation roadmap, making it more credible and defensible.
Don’t Use the Same Pitch
Because enterprise decision-makers are acutely sensitive to their own needs—especially downside risk—you must tailor every presentation: avoid using the same enterprise pitch, the same slide deck, or the same framework for every prospect.
Details matter. Two large banks may appear similar on the surface, but their systems, constraints, and internal priorities can differ dramatically. What resonates with one may fall completely flat with another.
A generic pitch signals to prospects: “You didn’t invest time to understand how *this* institution defines the problem.” If your pitch isn’t customized, institutions will struggle to believe your solution truly fits.
An even more serious error is the “rip-and-replace” narrative. In crypto, founders often paint a vision of a clean-slate future: replacing legacy systems entirely with newer, better decentralized technology. But enterprises rarely do this. Legacy infrastructure is deeply embedded across workflows, compliance processes, vendor contracts, reporting systems, and countless touchpoints and stakeholders. Rip-and-replace doesn’t just disrupt daily operations—it introduces pervasive risk.
The broader the impact of change, the fewer people within the organization dare to approve it: the larger the decision, the larger the coalition required to endorse it.
The successful cases we’ve seen all involve founders adapting to the enterprise customer’s current reality—not demanding the customer adapt to their ideal world. Entry points must integrate smoothly into existing systems and workflows, minimize disruption, and establish reliable footholds.
A recent example is Uniswap’s collaboration with BlackRock on tokenized funds. Uniswap did not position DeFi as a replacement for traditional asset management. Instead, it provided permissionless secondary-market liquidity for products issued under BlackRock’s existing regulatory and fund structures. This integration required no operational overhaul—only an extension onto-chain.
Once your solution clears procurement and goes live, pursuing bolder goals is perfectly feasible—and far more credible.
Enterprises Hedge Their Bets—You Must Become the “Right Hedge”
This risk aversion manifests in predictable behavior: institutions hedge aggressively—and at scale.
Large enterprises don’t bet everything on emerging infrastructure. Instead, they run parallel experiments: allocating small budgets across multiple vendors, testing various solutions in innovation labs, or running pilots without touching core systems. To institutions, this preserves optionality while capping exposure.
But for founders, there’s a subtle trap here: being selected ≠ being adopted. Many crypto companies are merely one of several options used for experimentation—fine for pilots, but with no intention to scale.
The real goal isn’t winning a pilot—it’s becoming the highest-probability hedge. That demands more than technical superiority: it demands professionalism.
Why Professionalism Beats Purity
In this market, clarity, predictability, and trustworthiness routinely trump pure innovation: technical excellence alone rarely wins. That’s why professionalism is critical—it reduces uncertainty.
By “professionalism,” we mean designing and presenting your product with full awareness of institutional realities—legal constraints, governance processes, and existing systems—and deliberately operating within those boundaries. Following established conventions signals to buyers: “This product is governable, auditable, and controllable.” Regardless of whether this aligns with blockchain or crypto ethos, this is how enterprises evaluate technology adoption.
This isn’t resistance to change—it’s a rational response to institutional incentives.
Obsessing over ideological purity—be it “decentralization,” “minimal trust,” or other crypto principles—rarely persuades institutions bound by legal, regulatory, and reputational constraints. Demanding that enterprises adopt your “full vision” all at once is unrealistic and premature.
Of course, breakthrough technology *and* ideological purity can coexist. LayerZero’s recent launch of its new public chain, Zero, aims to solve enterprise adoption challenges around scalability and interoperability—while preserving core principles of decentralization and permissionless innovation.
But Zero’s true differentiation lies not just in its architecture, but in its institutional design philosophy. Rather than building a one-size-fits-all network and expecting enterprises to adapt, Zero collaborates with core partners to jointly design specialized “Zones” tailored to specific use cases—payments, settlement, capital markets, etc.
Zero’s architecture, its team’s genuine willingness to co-develop with these verticals, and LayerZero’s brand collectively mitigate key concerns for large traditional financial institutions. These factors together helped secure partnerships with Citadel, DTCC, and ICE.
Founders often interpret enterprise hesitation as conservatism, bureaucracy, or short-sightedness. Sometimes that’s true—but more often, there’s another layer: most institutions aren’t irrational. Their core objective is continuity of operations. Their design goal is capital preservation, reputation protection, and resilience under scrutiny.
Technologies that win in this environment aren’t necessarily the most elegant or ideologically pure—they’re the ones that diligently adapt to enterprise reality.
These realities help clarify the long-term potential of blockchain infrastructure in the enterprise space.
Enterprise transformation is rarely instantaneous. Consider the “digital transformation” wave of the 2010s: despite relevant technologies having existed for years, most large enterprises are still modernizing core systems—and often spend heavily on consultants to do so. Large-scale digital transformation is a gradual process, achieved through controlled integrations and expansion from proven use cases—not overnight replacement. That’s the reality of enterprise change.
Successful founders aren’t those who demand full-vision adoption upfront—they’re those who master step-by-step execution.
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