Continuous Intelligence is the Future of the Internet
It’s true that various blockchains will power the 3rd iteration of the web, but continuous intelligence will be the glue that holds it all together.
Introducing Continuous Intelligence (CI)
Like most emerging technologies, the definition of continuous intelligence is not so clean-cut. The management consulting firm, Gartner, defines it as the following:
A design pattern in which real-time analytics are integrated within a business operation, processing current and historical data to prescribe actions in response to events. It provides decision automation or decision support. Continuous intelligence leverages multiple technologies such as augmented analytics, event stream processing, optimization, business rule management and ML.
Breaking down the definition, continuous intelligence (CI) is a way to leverage augmented analytics, event processing, and machine learning at an enterprise level to track business processes, operations, and historical data as events occur within a computer information system. Noting that, CI is essentially the crossroads of multiple technologies being brought together to deploy real-time analytics that decisions are made off of.
What Makes CI Special?
CI is part of a rapid change in the field of data analytics to move away from static data, that is data that legacy systems at most enterprises once depended upon to provide insights that were no longer relevant at that moment in time. CI providing real-time data that is processed by a machine learning model is a massive game changer for data systems going forward. Initially when legacy systems were setup, data was used to provide validation and insight, but now through digital transformation that allows multiple streams of data from multiple systems and databases to communicate, data is in and of itself a form of intelligence.
CI doesn’t just stop at the enterprise level either, it can deliver client facing solutions to the customers of major companies. For example, in the world of ecommerce, real-time data delivery is a competitive advantage that all consumers would opt into. If a customer orders something, they could get information real-time on the product they’ve ordered: If there are supplies of it outstanding, if the product is still in the manufacturing process, and where it is in its stage of delivery. A CI solution in this area would deliver incredible real-time analysis to the firm responsible for the execution of the order as well, running and fine-tuning a machine learning model to understand where in the process there are significant issues and what can be done about them.
How does CI Play into Web3 and the Future of the Internet?
Web3 is right around the horizon. Futurists, engineers, and thinkers envision a decentralized web that is running on multiple blockchains used for identity management, ownership through tokenomics, and especially trustless transactions without intermediaries. Web3, however, won’t be without its issues. There are some very real scenarios in which elements of Web3 will benefit from some form of a decentralized CI.
Decentralized CI running through blockchain processes would also yield decentralized Artificial Intelligence, or decentralized AI, that is sifting through millions of transactions and events happening on-chain. This could provide valuable insight to users, developers, and anyone else interfacing with the network. This would, in turn usher in an era where we realize a Web4 that would be a frictionless form of Web3 where users don’t need to pay attention to the goings on of the blockchain itself and can interface with the network seamlessly while a decentralized CI/AI work in the background to provide the necessary fixes and data to developers to make the whole network run smoothly.
When will CI be a Mainstream Data Analytics and Event Management Tool?
Currently the market for CI is still relatively untapped. In 2019, Gartner produced insights that predicted that by 2022 more than 50% of all major business processes would incorporate CI for real-time data to improve decision-making.
It is possible that due to the COVID-19 Pandemic accelerating digital transformation and solutions, more than 50% of firms are locked into contracts with CI tools and firms. A few of the major players in this space include Sumo Logic, Splunk, Datadog, Dynatrace, ServiceNow, Palantir Technologies, Loggly, Elastic NV, and Snowflake. As can be seen this is an extremely competitive space with many firms fighting for lucrative contracts and trying to be the premier data and event management firm.
The key question to selecting the right CI platform comes down to how effective the machine learning model is. Not all firms are going to have an impressive ML model backing them. CI is only as effective as the ML model it is running on top of. Knowing that, this space quickly becomes filled with lots of potential for inconvenient, borderline obsolete, CI software. Understanding the technology the CI is operating on will always give an enterprise, a blockchain developer, or data engineer a leg up on their decision-making, that is until the CI can make the decisions for them down the road.
