The tech industry has grown leaps and bounds in the past decade. From just operating mobile phones to dealing in increasingly sophisticated digital technologies: cloud computing, artificial intelligence, and data analytics, IT enterprises have come a long way. But what technologies are CIOs at large most excited about right now? And how do their preferences differ along with sectors and regions? Let us find out.
Artificial intelligence (AI) is defined as the theory and development of computer systems able to perform tasks normally requiring human intelligence. This includes visual perception, speech recognition, decision-making, and translation between languages. Gartner Analysts1 says in a prediction for 2022 that to make AI delivery easier, AI engineering automates data, model, and application upgrades. When combined with robust AI governance, AI engineering will operationalize AI delivery for a long-term value proposition.
Machine learning (ML) is a subset of AI where machines are given data to analyze and use algorithms to track patterns or trends. It can then take what it has learned and apply it to make predictions about new data sets. ML models “learn” over time with more exposure to the information being provided by humans. Despite the value that comes with ML, there has been a lag in the adoption of the same. A report on a Comet Survey2 shows that only a few companies have invested in ML experiments, and 68% of the 508 ML practitioners have abandoned 40-80% of their experiments in the past year. However, 63% said their organizations have plans to increase ML budgets for 2022.
Internet of Things (IoT) -- but what exactly is this "Internet of Things"? IoT refers to the billions of physical devices that are now connected to the Internet, communicating with one another. IoT devices can be found in everything from thermostats and alarm clocks to traffic lights and even satellites. The Annual Global IoT Survey by Research and Markets3 shows that respondents see the need to diversify the IoT storage strategies to manage the massive amounts of data.
IoT devices can collect and exchange data between each other, making it possible for CIOs to monitor and control these devices remotely across existing networks. By providing a constant stream of valuable data, IoT technology has helped industries such as manufacturing better manage their assets, gain visibility into their processes, increase productivity, and make faster decisions.
Robotic Process Automation, or RPA, is a software product that mimics the actions of a human user by replicating user inputs to interact with a computer application. RPA allows businesses to automate tasks and processes without investing in expensive IT infrastructure. The technology can be trained to handle end-to-end processes through the use of simple rules that can be applied across any operating system or software application--even those without an open API.
RPA can be used to automate tasks ranging from data entry and retrieval from multiple systems to the creation of custom reports and payment processing. The technology can also be used for more repetitive processes such as filling out forms and transferring data between multiple systems. RPA eliminates manual labor, increasing productivity while reducing costs and improving accuracy.
Let us start with the basics. Blockchain is a decentralized, encrypted database. It is used for many applications, but in its most basic form, it is a distributed ledger where transactions are recorded and confirmed anonymously. Think of it as an encrypted, peer-to-peer network that allows users to report verified information without needing an intermediary. Blockchain Services Global Market Report 20224 shows that the global blockchain services market will likely grow from $2.94 billion in 2021 to a whopping $4.65 billion in 2022. This is a 58% compound annual growth rate (CAGR).
It is secure and tamper-proof: Any transaction on the blockchain is immutable and cannot be changed or deleted once added to the chain. This factor makes it impossible for hackers to alter any data on the blockchain. The records stored on a blockchain network can also be monitored by everyone who has access to the system, which means no central authority or administrator is controlling them—anyone can validate new transactions, which makes tampering nearly impossible.
It offers transparency: Data stored in a block cannot be altered retroactively without altering all subsequent blocks in the chain, which requires collusion of all participants on the network—resulting in the transparency of all actions taken within the network since its inception. Every change made to data on a block is available for viewing by anyone with access to it—this same level of transparency can help prevent fraud and improve the accountability of organizations using this technology.
You can use data analytics technology to improve business performance, make better decisions, and improve customer experience, business productivity, or efficiency. Analytics technologies can increase revenue or decrease costs.
Data analytics technologies and techniques are widely used in commercial industries to enable organizations to make more-informed business decisions and by scientists and researchers to verify or disprove scientific models, theories, and hypotheses. Data is extracted and categorized to identify and analyze behavioral data and patterns, and techniques vary according to organizational requirements. Data analysis has multiple facets and approaches, encompassing diverse techniques under various names while being used in different business domains.
Computing technology is ever-changing, and in the past 20 years, the face of technology has dramatically changed. Technology has been growing rapidly in every sphere, and every organization has to properly plan and manage its performance over time. New technologies are born as well as many customers stop using older ones. The choice of the leading technologies which have the potential to appear in the techno stack for each company should be made carefully.
The right enterprise asset management strategy is one of the most important decisions that a CIO can make. Whether it is procuring new technology, expanding into global markets, or perhaps consolidating disparate technologies, the resulting change in overall IT operations can impact a business. The shift is towards increasingly new technologies and frameworks to develop applications, serve customers, and operate day-to-day businesses.