Blockchain is redefining the systems of record. Together they will change the boundaries of organizations to unlock trapped value.

Artificial Intelligence (AI) is a constellation of technologies—from machine learning to natural language processing—that allows machines to sense, comprehend, act and learn. It will transform the relationship between people and technology. 

Blockchain is a new type of database system that maintains and records data in a way that allows multiple stakeholders to confidently and securely share access to the same data and information. It will transform the way business gets done, eliminating the current message and reconciliation model to agree a state of play, and assuring that “I see what you see” (assuming we have authorization).

Neither of these definitions of technology do justice to what is really starting: business transformation at a whole new level. Together, AI + blockchain will remap organizational and process boundaries, moving them from siloed verticals with complex processes to allowing them to operate efficiently across horizontals while unlocking trapped business value. Consider this: How many of life’s important needs are satisfied by just one service provider or authority? How many companies are involved in picking and moving to a new home? Having and caring for a child?

Three reasons are driving this remapping:

Data quality

To be clear, blockchain doesn’t cure bad data. But blockchain is changing the nature of boundaries between organizations and is changing the concept of trust in data. The invention of databases from since the 1950s has locked us into a business model where Party A can’t trust Party B’s data because it could have changed. A database administrator can change data, Party B’s business process might execute differently from Party A’s expectations, or a hacker could have broken in and modified either data sources. These realities have led us to build our own data systems that we could fully control. And we have had to operate them in a “messaging”-based business model where Party A sends its view of the world to Party B and vice versa. Only when they both can reconcile those views can any business transaction be completed.

Through blockchain and other types of distributed ledger technologies, it is now possible to share access to a common shared data set with counterparties and they can each trust the data. That ability to trust comes from one of several key concepts of blockchain. Chief among them is when data is introduced into a blockchain, its original state and every subsequent related movement or change of that data is tamper evident. In other words, any participant with the appropriate access to a data element can prove to themselves mathematically that no one has tampered with the data. Data quality is inherently high.

This state of the data in turn supports AI. AI, which is really only hampered by its ability to harness the best available data, will be even more potent with data fueled by blockchain. But there’s more. As AI works through its complex decision trees, this “learning process” can be captured on a blockchain, in a tamper-evident fashion, and shared so its decisions may be evaluated and trusted.


AI-based applications must process huge amounts of data. Thanks to blockchain’s cryptographic algorithms, nefarious actors would have a difficult time hacking the systems and stealing sensitive data and information. This is perhaps the most critical element of this combination.

Consider this: Imagine the data that was being used to drive decisions on neonatal surgery, nuclear power management or air traffic control patterns. Having the highest level of certainty that the data had not been altered or tampered with is critical for AI to achieve its potential in these circumstances. With blockchain, if anyone tries to change, tamper with or duplicate a record, all stakeholders will know.

Traversing ecosystems

AI systems are dramatically changing the nature of services and experiences for humans. In this first phase of scaled use of AI, the focus has been on what value and services individual organizations could deliver to people. This “internal application focus” is driven by the natural commercial focus on how a business drives profit and growth—start with what we can do, what we can control. It is the rare instance where a human’s needs are comprehensively met by a single organization and by extension their AI implementation.

Take the example of a family relocating to a new place to live, a most basic aspect of the human experience. A myriad of organizations is involved in helping with that single objective including banks, insurance companies, realtors, inspectors, movers, retail firms (to buy stuff for the new house), new school systems, utility companies, postal systems, DMV, and tax authorities. Almost none of these organizations share access to the same data, leaving the family to handle its data case by case across all of these players. As each of these types of organizations starts to implement AI systems, they will be limited to the use of their own data or data they can get permission to access.

Now imagine a world where, through a blockchain-based system, the family’s data and data pertaining to the end-to-end process could be shared and controlled where each party could access just what they were allowed to access and messaging and reconciliation were eliminated. As these models are implemented, the possibilities for AI systems will grow significantly.

Here, the AI would be a consumer advocate type of service. In other words, the individual would “own” their data since they are the only part of the equation that has full access and would be the conduit to driving that data into an AI system that then makes recommendations and optimizes the data. In our example, AI systems will be able to evaluate and optimize the factors of the moving experience across the end-to-end process making linkages and connections that would typically be near impossible with the current fragmented data sets. What if an AI system could access historical utility / energy consumption of a house, weather data, insurance claim history, the family’s behavior patterns, and (more examples) to be able to calculate an accurate home maintenance cost and then design a specific custom services and insurance plan to suit it.

The wider access to data across an ecosystem and the advances in automated business logic through smart contracts are enablers of new and greater access for AI machines to traverse business ecosystems as well to deliver more comprehensive solutions to customers.

Strength in combination

New technology innovation is accelerating rapidly, and each technology is offering new and exciting ways to improve the way we work and live. But these technologies should be considered in isolation. It’s the combination of these technologies, however, that will allow for the most advantageous transformation.

David Treat

Lead – Technology Incubation Group

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