The Future of Software Development in 2022 and Beyond

Software development is an ever-evolving industry. To succeed in it, you must keep an open eye for emerging opportunities and leverage them for your business success. Read further to learn what’s trending in software development industry right now.

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Summary: “Software development is an ever-evolving industry. To succeed in it, you must keep an open eye for emerging opportunities and leverage them for your business success. Read further to learn what’s trending in software development industry right now.

In the past two years, organizations have had to accelerate their digital transformation priorities, developing new business models and offerings to compete in an increasingly competitive marketplace. The shift in demand toward a personalized, dynamic online experience has created the demand for new digital products – all of this translated into software development, leading to the inception of new software development trends.

 

 

Ongoing Software Development Trends for 2022 and Beyond

The future of software development looks bright for 2022, with the demand never higher for innovative products and solutions to meet the changing demands of the marketplace. In order to develop flexible, scalable solutions, pay attention to the following software development trends:

1. Low-Code / No-Code Platforms

Low-code development platforms (LCDP) and no-code development platforms (NCDP) offer pre-built blocks that can be dragged and dropped (visual environment) to assist in rapid development of mobile and web apps both by professional developers (for speed) and by those outside the IT department. While there are concerns over future flexibility, scalability, and security of software built using these low and no-code platforms, the platforms have lowered the bar to entry on software development, going mainstream in the last couple of years.

Popular platforms for low-code/no-code development include Outsystems, Mendix, and Appian.

2. Machine Learning Operations

There has been a huge increase in demand for artificial intelligence (AI) and data science leveraging machine learning (ML) both inside and outside IT. This has an impact both on what is being developed and operated as well as how. Machine learning can be used in many stages of development, helping inform priorities and decisions, set accurate budgets, rapidly prototype, review and test, and even assist in programming.