Unlock the potential of GenAI and low-code development! Let’s explore 4 key steps to integrate GenAI for faster development and a competitive edge.
Generative artificial intelligence (GenAI) has captured hearts and minds to a surprising extent given its relatively recent migration to the public consciousness. In the GCC, the GenAI market is predicted to be worth US$640 million this year but grow at a CAGR of almost 21% to reach US$2 billion by 2030.
This is a stark quantification of the technology’s phenomenal charm offensive. Private citizens, technologists, business leaders — it does not matter who you are or what you do. Everyone can see the potential in machine intelligence that can have flawless human-like conversations and then create formal documents from scratch. Or poetry. Or music.
Imagine the potential in business. Just think of the myriad ways GenAI can augment human agents by not only automating mundane tasks but helping significantly with creative ones. Given software’s ability to process information, if we were able to imbue it with the ability to innovate, we would have a powerful ally indeed. Right now, the Arab Gulf has skills gaps that pervade every STEM discipline.
GenAI can plug these gaps. Most organisations do not have enough skilled coders to execute their digital strategies. GenAI has the potential to transform development when it joins forces with another hot trend (although admittedly, one that makes less headlines): low-code development. From ideation to implementation and beyond to testing and deployment, GenAI could help regional enterprises master the development lifecycle once and for all.
Technologists and industry analysts are both predicting that GenAI and low-code will come together to help organisations meet the surging demand for digital experiences. GenAI has all the expertise and all of the ease of use required to empower citizen developers and accelerate times to market. One of low-code’s greatest strengths is eliminating the translation errors between business stakeholders and requirements analysts.
Those with domain knowledge, can forge ahead and add value quickly. And GenAI guides them through best practices and applies governance standards. A functional, secure, compliant application can sometimes be built in a matter of hours by briefing a GenAI-powered virtual assistant using natural language.
But powerful as these two technologies are, deployment of GenAI and low code, without due consideration of best practices, would be a mistake. The right steps will lead to the right outcomes. There are four of these steps.
1. The right people
Some regional businesses will have an in-house team of developers, and some will not. But the power of low code, especially when supported by GenAI, is that it can benefit both types of organisations. Even professional coders can code faster and more accurately with low-code and GenAI.
From a strategy perspective, however, companies must take stock of their workforce and think about who might gain most from these technologies and who has the potential to add the most value. Do not overlook non-developer technical staff such as admins and analysts. Design a phased-release program that equips each category and trains them appropriately with due regard for their role. Scale, industry, and the size of the existing developer pool are not factors that determine an organisation’s ability to adopt low-code development platforms and GenAI. Almost anyone can benefit as long as they are empowered in the right way.
2. The right use cases
GenAI fits into the technology mix whether you decide to build an application from scratch or customise an off-the-shelf solution. Before integration projects kick off, however, it is advisable to make sure solutions architects have focused appropriately on use cases. They should design the solution around business capabilities and people empowerment. GenAI can help with code generation, flow generation, and recommendations on script versus flow. It is worthwhile starting with these use cases while bearing in mind that more will emerge over time. GenAI will likely be used in the future in more sophisticated use cases, including process generation and process automation design.
Also Read: Your AI Journey – Have You Packed Everything You Need?
3. The right brief
GenAI can do many things, but it cannot read minds. Its results are only as good as its initial instructions. The quality of human input is crucial, so organisations must train users of all stripes to give clear prompts. Be precise in laying out the end goals of the app and the details of how it will be used and what users hope to gain from it. These prompts will be in the form of task requirements, API specifications, and even potential constraints. It is important to get the brief right and to learn from missteps.
4. The right feedback
Bedding down a new technology is a trial-and-error process. Stakeholders must design this process to accommodate feedback. Progress measurement and reporting should allow implementation leaders to always see how far they have come and how far they need to go. You should see better-quality code.
You should see shorter development cycles. You should see happier developers who are focusing more on innovation than deadlines. If you do not see all these things, then return to the drawing board and make sure genAI is being applied by the right people to the right use cases and that the right briefs are being issued.
Our future, assured
GenAI is a gamechanger. We knew this from the very moment we had our first encounters with it. When every enterprise can be an app factory, competitiveness is ramped up and economic growth follows. Customers will, of course, be delighted. And employees will be empowered and inspired to go further and innovate more often.
What we are building here is something a lot more special than the extraordinarily powerful technologies of genAI and low code themselves. We are building an inclusive, democratised development cycle with more efficient, more secure, more exciting outputs. In a digital economy, this is the foundation of sustainable competitiveness.
