Article | July 14, 2021
The world has started stepping into the “new normal” era. With the boost in vaccine inventions and countries rapidly vaccinating their citizens, we will be back to living a ‘new normal’ life. We keep mentioning normal as the ‘new normal’ because things will never be the same as before the pandemic.
A majority of changes have happened for the best. Nevertheless, challenges emerged in the pandemic, and these were answered by innovations. Let us precisely talk about the innovations in software development trends.
Digitalization played a vital role in transforming society and overcoming the hurdles created by the pandemic. Hybrid working style, chatbots, IoT, AI, and development in applications to improve performance and customer experience are the key software development trends that are on the rise.
Growth Predictions Post Pandemic
● 63.3% of companies consider accelerated digital transformation.
● IaaS market solutions will be worth $64 billion.
● Online sales will account for 22% of global retail (currently it is 14%)
● The utilization of low code products will reach 50%.
● The outsourcing services industry is estimated to reach more than $66 billion.
Software development trends have led to a boom in the software industry. As a result, all the sectors have turned towards software for solutions. Observing this change of scenario, here are some of the predictions on software development trends that will rule the industry by 2022.
Software Development Trends
The combination of AI and Big Data with IoT has led to significant changes in the IoT industry. IoT has profoundly incorporated its way into daily human life. It eases everyday chores by connecting all the devices with sensors and syncs them automatically. The machines understand our timely needs and act subsequently.
IoT has come a long way from just connecting the phone and the laptop. Instead, the day starts with Alexa, Siri, or Google. From telling them to turn on your coffee maker to adjusting your AC temperature, every little thing is manageable by the internet of things!
As a result, more and more devices are built with sensors to simplify everyday processes. Thus, IoT is one of the software development trends to be utilized in various sectors by 2022.
IoT has groundbreaking potential and has been adapted in smart cities. The smart cities project is a possibility only because of IoT.
Progressive Web Apps (PWA)
Progressive Web Apps are a trend in software development that is gaining popularity in these challenging times. PWA are apps that combine the functions of native apps and website accessibility. They provide the same user experience as native apps without having the hassle of upgrading and installing for web or mobile devices.
Easy maintenance, one codebase, easily searchable, lightweight, and operating offline are some of the advantages of progressive web apps. PWA is here to stay and is the latest in software development.
It is progressive, responsive, connectivity-independent, secure, easily installable, and linkable. As a result, many companies are switching their websites and apps to PWA for hassle-free code development and a great user experience.
Be it software developers, web developers, or users, low-code development is a hit amongst all. This new technology in software development saves time, is fast and intuitive. The long hours spent in coding every line are held by low code development. Herein the code is sketched like a flowchart and fed into the machine. As a result, a lot of manual effort is saved.
Low-code development is one of the latest technologies in software and the future of the software industry. Traditional developers thought that this process did not have much potential, but the pandemic changed this thought. Low-code development will allow people with little digital skills to digitalize their ideas.
Building apps quickly is the need of the hour, and low code development helps achieve that. This trend will also help in bridging the gap between the supply and demand of software engineers.
AR (Augmented Reality)
Augmented reality has appallingly changed the marketplace. Customers can virtually try new makeup or beauty products without even touching the product. The beauty industry has seen incredible conversion while using AR for its marketing. Similarly gone are the days of 2D mapping. AR has managed to bring 3D mapping into our lives. Be it gaming or navigation; augmented reality has strongly made things attractive.
AR is a hit in advertisements. Companies are luring customers by adding filters or creating environments in apps. This has shown great conversion numbers to the businesses. This is because AR is software that is more than visually appealing. It improves functionality, enhances effectiveness, and creates brand value. As a result, we are going to see more from this technology in 2022.
Using Big Data is building credibility. Security has a whole new meaning post-Covid-19. The public has become aware of the information that it will allow access to. This has led to a boost in the use of Big Data.
By 2022 Big Data can be used as DaaS (Data as a Service). This will allow companies to access the required data, and thus redundancy is avoided.
The use of Big Data has proven to provide data-driven solutions. It is giving the customers exactly what they are looking for. And this can be achieved only when you have proper segregation and security of a large amount of data.
Netflix has proven its popularity by utilizing Big Data and giving the viewers the exact content they are looking for.
Thus, Big Data is a software trend that will be a compulsion for companies to adapt in the future.
AI (Artificial Intelligence)
This list would be incomplete without mentioning the hottest software trend in the market these days. In the last five years, AI is one industry that has gained tremendous momentum. This is because machines are trained to think and perform tasks that were possible only for humans.
The combination of machine learning, deep learning, neural networks, and machine control has already enhanced customer experience in various sectors. The improved user experience, better efficiency, less prone to errors, reduced costs, and increase in ROI have made AI a dominant trend in the technology world.
By 2022 there will hardly be a sector that has not implemented AI. From the demand and supply chain industry to predicting stock markets, we will see a lot of AI everywhere.
Conclusion: Be Ready for 2022!
These are some of the predictions of software development trends 2022. There will be enormous changes in the lifestyle, working style, and adaptive measures taken by humans. And in this changing era, technology trends will guarantee maximum productivity along with comfort.
As the pandemic unfolds and most of the population gets vaccinated, there will be turning points in the latest software trends and the IT industry. There will be minor glitches and fluctuations, but these newest software development trends will help overcome them all. They assure an increase in revenues and adding value to the brand of the company.
Software development is not just a trend in software engineering but a process of continuous innovation. Of course, the predictions of technological processes are pretty unpredictable as inventions surge. But one predictable thing is that game-changing technology trends will keep emerging, and there are no stopping innovations in these fields.
Frequently Asked Questions
What are the top 3 emerging technologies in software?
AI (Artificial Intelligence) dominates the emerging technology industry, followed by IoT (Internet of Things) and then AR (Augmented Reality), VR (Virtual Reality), and MR (Mixed Reality). These play a predominant role in changing the face of technology.
What is trending in software development nowadays?
The current trends in software development are AI chatbots, powerful programming languages, and active incorporation of IaaS, PaaS, SaaS, DaaS to provide flexibility and improve productivity. These effective solutions are implemented to build apps, websites, manage hybrid working culture, and ease communication processes between teams.
Why should you track trends in software development?
It is the need of the hour to digitalize the business. If you keep up with the rapidly changing software trends, you can be distinguished from your competitors, and it will help you stay ahead of the race. Your products/services will be productive, efficient, and trusted by the customers.
If you do not digitalize your businesses and incorporate the required technology, your business will cease to exist.
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"text": "AI (Artificial Intelligence) dominates the emerging technology industry, followed by IoT (Internet of Things) and then AR (Augmented Reality), VR (Virtual Reality), and MR (Mixed Reality). These play a predominant role in changing the face of technology."
"name": "What is trending in software development nowadays?",
"text": "The current trends in software development are AI chatbots, powerful programming languages, and active incorporation of IaaS, PaaS, SaaS, DaaS to provide flexibility and improve productivity. These effective solutions are implemented to build apps, websites, manage hybrid working culture, and ease communication processes between teams."
"name": "Why should you track trends in software development?",
"text": "It is the need of the hour to digitalize the business. If you keep up with the rapidly changing software trends, you can be distinguished from your competitors, and it will help you stay ahead of the race. Your products/services will be productive, efficient, and trusted by the customers.
If you do not digitalize your businesses and incorporate the required technology, your business will cease to exist."
Article | July 14, 2021
Depicted as a natural predisposition to form groups of work, teamwork has been popularized through history as a central feature of organizational change programs that advocates empowerment and disruptiveness. The suasive force of discourse regarding the ineluctable essence of teamwork as a tradition and custom founded on some inclination for humans to work cooperatively, create a set of “rituals”, conventions and practices which invite to innovation, flexibility and creativity.
Teamwork as “human nature” was a common thread all through history and management literature. The team-based nature of early human activities can be traced to hunter-gathering in societies where orality was the prime source of communication. The locus communis was the collective memory (facts, rules, code of conduct, religious beliefs and practical knowledge). The pneumonic function of the verse will fulfil a didactic function as a way of memorizing any content in order to systematize a conceptual theoretical primitive language. In preliteracy times, doctrines and their conservation were highly dependent of the spoken word and memory (Havelock, 1957, 1992). Thus, in an oral culture experience is “intellectualized” mnemonically (Ong, 1982). In a sociobiological perspective, aspects of teamwork behaviour allude to a biologically determined “natural history of species”.
According to Katzenbach and Smith (1993) “teams- real teams and not just groups that management call “teams” should be the basic form of performance for most organizations, regardless the size”. This statement clearly sets the basis for the team as a natural building block of any organizational design. Buford (1972) in a comprehensive study of Ancient Greek and Roman craftmanship interpreted teamwork in a very familiar approach we understand it today: collaborative work, multiskilling, mutually interdependent tasks. There were technical divisions of labour based on skills, the relationship between mentor and apprentice and so on. The greatest craftsmen were expected to be versatile in different skills, but the coordination of work efforts was left to the so-called professional cadre of engineers, architects and masters.
With the advent of Capitalism, the massive growth of the economic activity claimed for reorganization. A new form of discourse emerged, our prehuman origins and modes of communication becoming codified and formalized as the scientific disciplines of evolutionary biology, economics and linguistics respectively (Foucault, 1972). Within the economic discourse, there was a creation of a distinct managerial object, which opened new domains of knowledge and professional practice.
The mythical traditions of teamwork replicated in today’s contexts and the “tribal” notion of team popularized by Codin (2008) paves the way to concrete changes in the form we perceived our working environment. The analogy of team as “family” so common in the corporate world which in its essence represents our first experiences as a community is not a happy term anymore, since in a manner it could go against the interests of today’s organizations. Therefore, in building a healthy sustainable workplace culture teams cannot be perceived as family. Teams have a commitment to a common goal, clear expectations and performance.
The MetaQuant: From siloed work to interdisciplinary collaboration
With the paradigm shift to automation, organizations are taking actions that promote scale in AI through the creation of a virtuous circle.
The central overarching question is: Are traditional ML teams good enough to develop models able to achieve long lasting competitive advantage?
“In a world spinning around AI, competition among institutions seems to be fierce while mayor obstacles appear on the way: recruiting top talents is not only time-consuming but also high-priced, or just trying to find a balanced approach to talent, meaning "reshaping" the old-school computer scientists into quants, is critical in terms of AI implementations. The big winners: those firms that integrate AI with human talent” (Litterio, 2020: 167).
Successful machine learning (ML) projects require professionals beyond engineering expertise. AI has the biggest impact when it is developed by dynamic creative cross-functional teams. The move from functional to interdisciplinary teams initially brings together the diverse skills and perspectives to build effective tools.
In order to bring theory into practice, and in the need of a novel conceptual framework design, I have coined the term MetaQuant.
The MetaQuant is a new breed of market players, who “translates human language into signals” and "reads" the data from a holistic perspective identifying patterns within the linguistic and symbolic constructs. The MetaQuant is the linguist, the semiologist, the sociologist, the cognitive psychologist and the philosopher or rather a combination of these intertwined profiles which will fuel the potential for information advantage providing a unique core differentiator transforming data into knowledge. In this sense, the MetaQuant has emerged as a crucial component of any AI model paving the way for a novel insight where hybridization is critical. The formula for a successful organization in a discovery-driven environment is the MetaQuant + The ML team. And eventually the Quantum Computing Expert. Finding the needle in the haystack can be a competitive difference maker.
Creative thinking, actionable insights, collaboration, proficiency, flexibility, shared vision and training are the ingredients for an elite team.
It is vital for organizations to establish workflows that empower everyone to play a role in order to move projects from test to deployed AI/ML. Yet, knowing how to do ML is not the same as being proficient with it and knowing how to implement a ML model end-to-end is not the same as using ML creatively to build solutions to real-world problems, to explore and assess potential applications specific in competitive contexts.
Ideally, when selecting members for your elite team, it is advisable to make a first distinction between those who wish to do research in ML from the ones who wish to apply ML to your business problems. Both are of major importance alike. The instreaming of new talent brings in novel ideas which can positively impact the work culture.
Demonstrating flexibility is a significant asset. Since ML projects may encounter all kinds of roadblocks, being able to easily change tactics to overcome obstacles without getting frustrated or losing sight of the end goal is key to deliver projects.
Mentoring and inspirational leaders is greatly valued when designing a ML team. An exceptional team leader is the one who shares a unique perspective and knowledge. Experience in the field is a substantial source of wisdom within the organization. Having a passion for diversity of input and fostering a healthy culture of support distinguishes average from excellent ML teamwork.
Educating everyone is the dictum to become an AI-first institution.
To ensure the adoption of AI, organizations need to educate everyone, from top leaders down. To this end most are launching in-house programs which typically incorporate workshops, on-the-job training to build in capabilities. Some others, and which reflects a common trend today, opt for partnerships with renowned academies or prefer the outsourced modality “training as a service” program or a bootcamp.
For an A-team, it is critical to make a mark in the ecosystem through journal publications, book chapters, white papers or lecturing in conferences. Disseminating their work and findings through meetups, workshops, and seminars is a must for building a thriving culture that promotes exchange and cross-fertilization of new ideas and technologies in a substantial way. Systematicity and coding belong to the ritualistic change of conscience.
Article | July 14, 2021
Just because something is labeled a “thing,” in this case DevOps, doesn’t mean that an organization is doing anything modern in its application development practice.Many people will think that technology decision points drive the “modernization” of applications. To be sure, technology plays a key role, but I prefer to think of application modernization as a three-legged stool.
Article | July 14, 2021
What would you call a machine that looks like a human? Obviously a Robot! Robots are machines or mechanical human beings that are designed to assist humans with laborious and complex tasks. However, such robots are no more just mechanical design rather they have become smarter with time and advancement of technologies. AI developments have induced evolution and better capacity in robots. Even robotics and AI together can revolutionize almost any industry for the greater good. As the industry is realizing the combined potential of both the technologies, will we see the combination anytime soon?