2018 will be a fascinating year as several emerging technologies go mainstream in the enterprise. Business with the knowledge and leadership to move quickly and embrace these technologies are well placed to both create new products and optimize operations.
Towards the end of 2017, Bitcoin became big news as its value skyrocketed. I’ve have no doubt that Bitcoin will be on our minds throughout 2018 too, but we’ll also hear a lot more about the technology that powers Bitcoin, the blockchain.
A blockchain is a digital ledger that stores an ever-growing list of records. In the case of Bitcoin, those records are transactions, but blockchains can store other types of information, such as medical records, contracts, and document provenance. The most important features of blockchains are that they’re distributed, decentralized, and immutable. Organizations using a blockchain don’t have to trust each other or a central authority.
Throughout 2017, enterprise organizations launched blockchain pilot studies. Maersk and Microsoft teamed up to test the feasibility of using a blockchain for shipping insurance. Walmart, IBM, and others explored how blockchains could be used to trace the origins of food products.
In 2018, we can expect to see wider adoption and exploration of the potential of blockchains.
Analytics have been used throughout the enterprise for many years, but often on an ad-hoc per-project basis. In 2018, we will enter the era of what has been called the quantified enterprise. Companies will harness the full spectrum of the data they generate — their “data exhaust” — to streamline and optimize processes and convert the insights gained from analytics into actions that generate value for the business.
Machine Learning / Artificial Intelligence
Machine learning has been hyped for several years, but it’s only in the last couple of years that we have seen machine learning software and hardware begin to yield fruit in the enterprise. In 2018, as higher-level tools for working with machine learning technologies become more widely available, companies will apply it to a wide gamut of problem domains.
What is machine learning good for? Any application that involves learning associations, prediction, classification, and information extraction. Machine vision and speech recognition are headline examples, but, to take just one domain, we’ll see machine learning increasingly applied to pricing, customer segmentation, product recommendations, and process automation.
2018 will be the year 5G starts rolling out in earnest. CableLabs, the cable and broadband industry research group, is laying the groundwork will make 5G a reality for many consumers in the next couple of years. Cable providers have announced the launch of wireless home broadband services based on 5G technologies in 2018. With increased bandwidth and significantly reduced latencies, 5G will change the way we think about mobile business connectivity, opening up new possibilities for apps and services.
Centralized cloud computing firmly staked its place as the dominant infrastructure hosting modality of the early 21st Century, but centralization has limitations. For true real-time computing, processing will be moved closer to the sources of the data, to the edge. Advancements in processing and power requirements make it increasingly feasible to push to the edge data processing that would once have required a data center.
Bringing It All Together
Individually, the emerging technologies we have discussed are exciting, but it is their combination that will make 2018 a year to remember. Decentralized ledgers, big data and analytics harnessing machine learning, enhanced low-power connectivity, and edge computing: these add up to huge advances in the Internet of Things, which will be a key driver of innovation over the next several years.