To capture attention related to the AI opportunity many low-code platforms will pivot towards branding themselves as AI-powered application development tools. With this integration, we expect the next phase of AI-powered software development to spotlight developers as they assign routine and repetitive tasks to AI-powered mentors, reducing the burden of mundane work. As developers spend time on expert-level coding requirements, their AI companion can tackle code duplication, manual testing, creating and updating UI elements and layouts for multiple screens, and configuring build scripts.
Low-code tools will also move in the direction of empowering organisations to build AI applications from the ground up in the coming years. For instance, high-performance low-code platforms should pull in large language model connectors to allow developers and organisations to embed the capabilities of ChatGPT into applications they build, provide personalised recommendations for users, and power virtual assistants, for example.
Data management also will become an area in which organisations must prioritise and invest. The goal of implementing AI and building intelligent applications will require mass quantities of data to deliver insights and enable decision-making. Businesses must examine their current data to ensure that it is ready for AI, and cultivate a comprehensive understanding of effective data management practices, such as data collection, cleansing, labeling, security, and governance.
We continue to see a similar trend on the talent front. AI is already disrupting how time is spent at work, while 40% of working hours across industries are expected to be impacted by large language models. This changing work structure will alleviate some of the strain caused by the scarcity of skilled professionals across diverse sectors in APAC. Within software development, AI has the capabilities to automate code generation, testing, and deployment processes. Rather than spending time on mundane, repetitive tasks, developers can channel their energy and talents toward solving complex problems with innovative applications. Additionally, with the ability to use natural language inputs to describe their desired applications, a wider talent pool can contribute to app development.
AI will also impact the wider job landscape. The technology is predicted to replace 85 million jobs, but create 97 million new positions by 2025. Specifically, analysts expect a 40% jump in the number of AI and machine learning specialists by 2027. New jobs will include prompt engineering, tapping into AI experts to design, develop, and refine generative AI text prompts for various applications, especially with the rise of natural language processing tools.
In summary, AI's enduring influence in enterprise tech will drive transformative changes in software development throughout 2024. As low-code platforms pivot towards AI integration, organisations can create more sophisticated applications and harness the skills of existing developers more efficiently.
Source: INWIS