The global market for custom application development services is forecast to grow to more than US$61 billion in 2023 according to Deloitte, compared to $47 billion in 2018.
This voracious appetite for bespoke application development is seeded in the need for companies to systematise their processes, and retain a robust workflow through a changing workforce. To keep step with this, the employment of software developers is projected to grow 21% between 2018 and 2028, outpacing the majority of other occupations. But this demand far outstrips supply, with software engineers and developers already labelled the world’s most in-demand profession.
Artificial intelligence (AI) software developers are on the rawest edge of this talent drought, while also being uniquely placed to address the issue – with AI itself. Small wonder the application of AI in software has soared. AI now has its fingers in pies across the development board – from initial project requirements to coding creation, review, testing, deployment and project management. Predictive coding similar to Google’s autocomplete can reduce keystrokes by around 50% and concurrently improve accuracy, while machine learning (ML) and natural language processing (NLP) technologies help detect and address issues earlier in the dev process, debugging before errors embed.
While AI assistance has had a few false starts in the past, all signs point to this next few years being its debutante ball. Gartner Research Vice President Mark Driver has predicted that “by 2022, at least 40% of new application development projects will have virtual AI co-developers on their team.”
Appending artificial intelligence onto traditional software development is accelerating efficiencies dramatically, and AI’s influence in this sphere will continue to grow. However, there is a second software development model ripe for AI augmentation. The emerging no code movement also offers an intriguing opportunity for the envelopment of artificial intelligence, one which re-envisions custom application development from the ground up.
In no code application development platforms like Intelastel, a user-friendly visual interface cloaks the raw code, creating a non-intimidating platform accessible to non-professional ‘citizen’ developers. This allows them to develop and customise applications without knowledge of a coding language. In this model, it is pre-written code that shoulders the heavy lifting, while AI assists in understanding the context of data and advising on system and application configuration.
Where the two development models truly diverge is within pledged partnership length. Custom software development has previously been treated as entirely distinct to the day-to-day usage of the software it creates. However, Intelastel’s application development platform encapsulates both a builder (Configurator) and centralised business platform (Client view). Because of this blended nature, Intelastel’s AI capabilities will extend further, past build stage and into the application’s day-to-day usage, where it can make smart suggestions on system layout based on the live data flow. This alloyed model changes the nature of creator/created software development into a symbiotic, evolving exchange, in which the build can be continually fine-tuned by the use cases. In this picture, work processes become workflows, with the requisite fluidity to flexibly accommodate business adaptations in flight, instead of software stagnating between upgrades.
AI is set to become a central component in software development. That now seems inevitable, whether that’s in applications that assist professional developers on bespoke projects, or serving as copilot alongside business users as they configure no code applications with platforms such as Intelastel.
But what’s truly exciting is the potential for AI to develop development itself. In laying the foundations of AI-augmented software development, we are laying the groundwork for projects with unlimited scope as AI evolves in capacity and sophistication.
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