In addition to financial transactions, distributed ledger technology (DLT) is starting to exert its influence on business processes, legal engagements, the supply chain, and a host of other activities.
And yet, it’s been more than a decade since the first blockchain was introduced, and to a large extent it still exists only on the fringe of most enterprise data architectures.
Of course, it is not unheard of for new technologies to experience lengthy roll-outs on the way to mainstream success. The earliest cloud services date back to the mid-1990s, but the technology didn’t catch on in a big way until 2010 or so.
But blockchain has the potential to be a game-changer for so many critical enterprise activities that it shouldn’t hurt to see what the headwinds are at the moment and examine how they can be diminished.
According to a collaborative article posted on LinkedIn recently, the major hurdles at the moment are:
- Technical Complexity – as an amalgam of cryptography, consensus algorithms and other highly specialized tools, DLT is a challenge to implement and maintain. And the technology is evolving at a rapid pace;
- Regulatory Uncertainty – since it operates on a global scale but in a decentralized manner, blockchain cuts across numerous jurisdictions, most of which have different ideas as to how it should be governed and taxed;
- Organizational Resistance – many legacy processes must change in significant ways to accommodate blockchain, challenging the traditional roles of individuals and even entire teams or departments;
- Business Value – Blockchain’s efficacy is not perfect across all deployments, so it can be difficult to demonstrate its ability to improve on existing solutions or outperform alternative ones.
Another significant factor in blockchain deployments is creating the interoperability it needs to function with newly emerging intelligent platforms.
In many ways, these two technologies complement one another, with blockchain providing the trust and transparency of the data used to train AI models, while AI can automate many of the data transactions across a chain. But creating this environment is neither easy nor immune to setbacks.
Smart Blockchain at Scale
A recent post by Block Telegraph highlights some of the key pain points in this effort, starting with the scalability problem.
Not only does the enterprise need to substantially increase compute and storage resources, but demand for data processing and complex computational capabilities puts a strain on the decentralized nature of blockchain environments, which slows down performance and drives up costs.
Data privacy also becomes in issue when AI is introduced to blockchain. If not handled properly, the data that an AI models pulls for training or executing contracts could be exposed to all members of the chain, which is a problem when dealing with health records, legal documents and other types of privileged information.
A number of tools and techniques can be used to resolve these issues, but they bring added cost and complexity to the environment.
Key vertical industries also have their own unique implementation issues.
One of the most difficult to overcome is integration with numerous, specialized legacy platforms, says Kirsten Peremore of HIPAA-compliant platform developer Paubox.
Healthcare organizations in particular are usually steeped in complex IT infrastructures that handle everything from electronic health records and medical billing processes to diagnostics and prescription drug maintenance.
All of these systems tend to interact with one another in a delicate balance that could be upended by the gradual introduction of blockchain.
At the same time, a single, forklift upgrade is likely to be highly disruptive, which is one thing healthcare organizations cannot tolerate.
In all likelihood, the medical field will employ different blockchains for different purposes, depending on the level of privacy, transparency and other factors required by any given transaction.
But this will take time to sort out. As well, the most sensitive healthcare information will reside on private or consortium-backed blockchains, which have smaller footprints than public ones and are therefore at greater risk of compromise.
Blockchain also represents a new software development challenge for the enterprise, and already there is a plethora of development platforms to choose from – each one with its advantages and disadvantages for key applications.
Tarun Nagar, CEO of app developer Dev Technosys, notes that while popular platforms like ethereum (ETC) have powerful tools and bring credibility to the resulting applications, others, like Corda, provide features like permission-defined dispersed decision-making, which bring privacy benefits to financial transactions and smart contracts.
In general, choosing a blockchain platform requires the same basic analysis as traditional development environments. Is it compatible with existing systems? Does it have high ease-of-use and accessibility characteristics? Is it secure? And perhaps most importantly, does it fit within your budget?
All technologies require a learning curve before they can be trusted with critical functions in the enterprise. And with blockchain being such a complex and far-reaching development, it’s understandable that organizations want to take their time getting familiar with it before pushing it further into production environments.
But competitive pressures are also not to be ignored. Blockchain will push its way into the mainstream before long, but hopefully not until it’s been vetted to a degree that minimizes its chances of doing significant harm.