“Gen AI and Low-Code is the high octane combo that can accelerate digital transformation” – Kissflow

Dinesh Varadharajan, Chief Product Officer (CPO) at Kissflow, belives that the fusion and combination of Gen AI and Low-Code can accelerate digital transformation across the Middle East – and can really unlock the economic impact of AI by 2030.

US$320 billion – this staggering figure is what experts project the economic impact that AI will unlock for the Middle East by 2030. With such invigorating promise, it’s unsurprising that enterprises have been quick to jump on the AI bandwagon.

Admittedly in 2023 many were rushing to establish its relevance to their business, but as the market has rapidly matured, in 2024, we can expect rubber to hit the road, and aspirations to become reality.

Many enterprises will find that this journey is far from seamless, however. Lack of skills, complexity, integration issues, scalability and maintenance are challenges they are likely to encounter.

And while these are daunting, they are far from insurmountable – provided organisations recognise the potential for the simpler and more streamlined approach, one that is made possible by the power of Low-code.

Low-code platforms accelerate the application development process through highly customisable, ready-made, and reusable components that can be dragged and dropped by non-skilled users to build applications.

This is extraordinarily impactful for a business looking to jump on the AI train. Low code democratises development processes and allows domain experts to bring their visions to life without them getting lost in translation during IT-led phases such as requirements gathering and design. And with AI in the mix, business users get the ideal co-pilot to augment their skills.

Agility as standard

Non-technical users get to reimagine and digitise business processes. In most cases, they will be tweaking something within existing infrastructure, which means no overhauls or large expenditures.

The AI tutor will guide the low-coder through a visual drag-and-drop or natural-language editor (often as a chatbot) to create AI models that add real value to the business.

Gen AI-infused low-code Application development platforms (LCAPs) provide a range of multimedia assets and text resources to accelerate development and time to value. And of course, virtual assistants also help reduce errors and improve overall quality, all while shortening the user’s LCAP learning curve. Let’s look at this in more detail by taking three broad areas of improvement delivered by low-code development.

  1. Best practice, every time

AI can ensure that low-code developers build their applications in step with current best practices. Because they are guided, there is little room for forgetting the golden rules established by the company. The AI assistant can suggest new data fields depending on the type of application being built, adding them automatically.

Accuracy is all but guaranteed because AI can generate or complete code automatically, based on requirements and context provided by the end user. This is especially helpful for repetitive coding tasks like setting up database schemas or creating user interfaces. And when it comes to testing the solution, AI can step in again, identifying and generating test use cases and scripts, and ensuring no steps are skipped.

  1. Automation, where appropriate

Accuracy is one thing, but in today’s development environment, with tomorrow’s technology, where everything is needed yesterday, AI makes it possible to speed up many processes. By automating repetitive tasks, like adding data entry fields or creating workflow templates, organisations are digitising complex manual business processes that absorb the time of skilled professionals. AI and low code streamline the entire process, while preserving accuracy.

Not only that, but AI can optimise the applications themselves to improve their efficiency and scalability by analysing application frameworks, workflows, and usage patterns.

  1. Working naturally

Natural language processing (NLP) for low-code and no-code application development tools makes it possible for users to create applications by giving direct text-based commands in their own words rather than having to learn a programming language.

No code is required. Citizen developers just type their requirements like they are chatting with a colleague and the AI bolts the necessary components together and connects them with code. While NLP is nascent and is still error-prone, recent advancements are very promising and we will likely see natural language rise in prominence as an input method.

AI and low code are the future

Professional programmers tend to think in terms of code when they design, to make the process expedient. This has an impact on requirements fit. AI-embedded LDPs mitigate that problem by allowing citizen developers to think in terms of business pain points, which are then deftly overcome by AI in custom applications.

With low code, employees have more time to focus on the logic behind their applications and on business metrics such as efficiency and productivity.

Keeping up with user requirements is also more straightforward because deploying updates and creating new iterations of applications has become easier. Employee and customer experiences are now looked after by those who know employees and customers best.

For that reason alone, we can say with confidence that the rise of AI-driven low-code apps is not a flash-in-the-pan trend. It is the future; here to stay.

By integrating AI into low-code app development and internal business operations, organisations can be better equipped to improve their operational efficiency, meet constantly changing user needs, and stay competitive.

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