Enterprise Blockchain Shows Signs of Revival After Industry Lull

Enterprise blockchain has been through cycles of hype and disillusionment, but recent changes in public-chain infrastructure are reshaping what “possible” looks like. In an opinion piece, Paul Brody, founder and CEO of Nightfall Networks, argues that the earlier wave of enterprise blockchain projects arrived before the industry had the privacy, scalability, and—critically—the financial plumbing needed to make large-scale business models work.

Brody draws a parallel to Pets.com: the company raised significant capital and bet that online ordering would scale smoothly—until the real world of shipping costs and logistics made the unit economics collapse. The broader point, he says, is that the idea was not inherently wrong; it simply reached the market before the surrounding systems (and costs) caught up.

Key takeaways

• Brody argues enterprise blockchain failed less because of blockchain itself and more because projects launched before privacy, performance, and liquidity were ready for real business constraints.
• Earlier permissioned blockchain efforts often required “non-blockchain-like” workarounds to achieve privacy, which he characterizes as costly and slow.
• He points to improved public-chain capacity, evolving privacy tooling, and stablecoin-driven onchain liquidity as key building blocks for enterprise use cases.
• Brody frames the opportunity as moving beyond tracking information to enabling payment and settlement in a single ecosystem.
• He cites potential operational gains from digital supply-chain approaches, including inventory and administrative cost reductions described by McKinsey and by his own industry experience.

Why the early enterprise blockchain era struggled

Brody starts with two ways he says inter-company systems tend to break down today. First, organizations end up with collaboration information that is constantly out of sync—functioning like disconnected islands of internal systems that exchange data through emails, spreadsheets, and asynchronous messages. In the second failure mode, teams resort to tightly integrated, real-time proprietary connections between partners, which can work well but often comes with expensive coordination and long-term lock-in.

Blockchain, he suggests, appeared to offer a middle path: shared business logic and information across a broader ecosystem without forcing every partner into a custom integration. But around 2017, the “obvious” pitch—shared visibility with less lock-in—attracted heavy investment. Brody lists well-known enterprise blockchain initiatives that he says largely “crashed and burned” within a few years, including TradeLens, We.Trade, Contour, B3i, ASX Chess, and Everledger.

His central explanation is that many of these systems depended on achieving privacy in environments where privacy was not native by default. According to Brody, companies responded by building private or permissioned chains and then layering extensive workarounds to protect sensitive information. In his view, the result was uniformly slow performance and high cost, with limited traction among enterprise users.

Privacy as the deciding constraint for enterprise adoption

The author argues that companies do not want unrestricted transparency about competitive details. Instead, enterprise needs typically call for selective disclosure—keeping particular workflows, counterparties, and data fields from being visible to everyone in a network.

In the period when permissioned blockchain projects dominated, Brody says the industry tried to patch privacy limitations using complex mechanisms that were not truly native to blockchain design. He claims this approach produced dismal user experiences, leading some “survivors” to back away from blockchain entirely and return to software-as-a-service models.

That framing shifts the question from “Is blockchain useful?” to “Can blockchain support the privacy enterprises require without sacrificing speed and cost?” Brody’s answer is that the ecosystem has changed since those early attempts.

What changed: scalability, privacy tools, and liquidity

Brody points first to scalability. He cites Ethereum’s performance in 2020, when it processed about 1 million transactions per day and saw transaction costs spike to $30–$50 during periods of high demand, referencing Cointelegraph reporting about gas-fee surges. He also notes that today most transactions cost under a penny and that Ethereum capacity is “ramping” toward billions of transactions per day, referencing Ethereum.org build guidance. His conclusion: the underlying infrastructure now supports high throughput in ways that were less realistic during the earlier enterprise push.

Privacy is where he says the progress is most meaningful. While privacy is still not the default for all onchain activity, Brody highlights an expanding toolkit—ranging from privacy pools and zero-knowledge roll-ups to full privacy chains—and adds that Ethereum is developing additional capabilities to introduce privacy at multiple layers of the network. The practical takeaway for enterprise planning, as he presents it, is that businesses can now pursue scaled operations while retaining a higher degree of data confidentiality.

Finally, Brody emphasizes liquidity. He argues that regulators’ evolving stance toward stablecoins has helped fuel onchain activity, and he cites Cointelegraph reporting that stablecoin transaction volume reached almost $1.8 trillion in June. He frames this liquidity as the missing ingredient that turns “operational” blockchain use into a financial system enterprises can actually transact through.

In his view, once blockchains can handle both the movement of value and the logic around payments and settlements, enterprises get something they have rarely had: a single environment to buy, sell, move assets, and get paid.

From visibility to working capital and faster contracting

Brody extends the argument beyond throughput and privacy into business economics and process redesign. He describes how digital supply-chain tools can reduce inventory through better planning, citing McKinsey’s view that reductions of 35% to 75% could be possible. He also offers a more conservative estimate from his own field experience: replacing spreadsheets and electronic data interchange (EDI) cascades could reduce inventory by roughly 20% at the same service level—translating, he says, into potentially billions in working capital savings for many industries.

He argues smart contracts can also compress time and administrative workload for contract rules that typically take days to manage manually. As an example, he points to Microsoft’s move of its Xbox royalty workflows onto smart contracts, claiming the time to access monthly royalty statements fell from 45 days to four minutes while handling more than 2 million transactions per day.

Once key supply-chain documents—purchase orders and invoices—exist onchain with verifiable provenance, Brody suggests that financing becomes more efficient. His argument is that demonstrated buyer quality can lower the cost of credit, and improved visibility into inventory and delivery status can accelerate receivables factoring.

Put together, Brody’s thesis is that the value proposition for enterprise blockchain should not be limited to auditability or shared records. Instead, he argues that the next attempt should target integrated execution: operational tracking linked to settlement, payment, and working-capital flows.

Investors and enterprise strategists watching this space should pay close attention to whether privacy tooling and onchain liquidity are being packaged into practical systems that reduce integration costs rather than recreating the slow, workaround-heavy models of the past—and whether measurable improvements in inventory efficiency, contract processing, and financing actually hold up in live deployments.