IT automation advances society by churning data into information. This transformation of data into information is the first stage in the knowledge management cognitive pyramid (DIKW). The ultimate aim of the IT industry is to ascend into Wisdom stage of DIKW pyramid where all machines would have cognitive capabilities. If we study the history of the IT industry, we would find that the current trend follows the same pattern. The first generation of IT started with mainframe-based Electronic Data Processing (EDP) systems. It was all about processing data into information. This was an era of highly-centralized, highly-controlled IT infrastructure. But when the personal computer (PC) became a household phenomenon, it led to the rise of client-server systems and started the Second generation of the IT revolution. This generation was marked by decentralization and fostered a culture of IT innovation. This was the time when the internet became reality and client-server systems were replaced by web-based systems. Modern web (known as Web 2.0) came up with a set of capabilities known as the social web. These include online streaming, social media/networking, tagging, podcasting, blogging etc. Another parallel development that greatly enhanced the attractiveness of the social web is the smartphone. Arguably, the smartphone is the most versatile machine ever built by man - it's a phone, camera, PDA, portable music player and what not. This mixture of PC, smartphone, tablet, social network, and social media, mobile app pushed us into the Third generation of the IT revolution. Characteristics of this period are a huge amount of structured-unstructured data (Big Data), cloud infrastructure and smart analytics. While each of these technologies can exist separately, their synergy makes it a major disruptive force. For example, Snapchat is a social networking messaging service that runs on the mobile phone. It relies on Amazon's cloud infrastructure and generates a huge amount of data from its users. By analyzing its customer's post and messages, it can intelligently predict the buying and spending pattern, likes and dislikes, food habit etc. These kinds of smart analytics make it all powerful.
The rise of big data, analytics, and cloud computing are slowly replacing lots of traditional IT skills. Code automation, component-based development, enterprise-ready and off-the-shelves products are reducing software development effort. Continuous development and continuous integration (CI/CD), micro-services etc have become the norm. Therefore, the industry has shifted its focus toward analytics so that we make more sense of available data. This renewed focus on analytics is turning information into knowledge (intelligence). Interestingly, if we map each generation with DIKW pyramid, we would find each shift in IT revolution corresponds to one stage in DIKW pyramid. The following figure explains it all.
DIKW Stages vs Generations of IT Revolution
First Generation (Mainframe Era - Process Data) 1955 - 1977
Second Generation (PC/Client-Server Era - Process Information) 1978 - 2004
Third Generation (SMAC Era - Build Knowledge) 2005 - 2026
Fourth Generation (AI Era - Cognitive Abilities) 2027 - ??
If we learn anything from the past trend, we can conclude that the current era would last for another decade and then the next era would begin. But are we ready for such a change? Current shift toward Fourth generation might be detrimental for 60-65% of mid and senior level IT employees. A huge number of them would be unemployed if they fail to retrain themselves in these areas.
Furthermore, it can be concluded from the pattern that next era (Artificial Intelligence) would come into prominence in the next 10 years. The current technology landscape is evolving in that direction at a breakneck pace. In recent years, there has been the huge surge in the study of Artificial Intelligence (AI), machine learning, robotics, Natural Languages Processing (NLP), Internet of Things (IoT) and Quantum Computing. These technologies can empower businesses to improve performance by reducing errors and improving agility and quality, and in some cases achieving outcomes that go beyond human capabilities. New solutions such as Driverless car, retail automation, smart home, green energy will become an eventuality.