To say AI has great potential feels like the biggest understatement of the year. Since the launch of ChatGPT in particular, terms that were reserved for technical specialists such as generative AI and LLMs have become mainstream.
However, that explosion of conversation and a scramble to incorporate AI tools into business workflows or find a valid way to describe an organization's solution as ‘AI-powered’ in marketing copy has led many to the question of the moment. Are the applications of AI, and in particular generative AI, being over-hyped?
Journalists, analysts, and buyers alike are becoming fatigued by the constant nod to the emerging technology and are asking questions about whether AI can actually solve complex business challenges outside of the sandbox, today.
The rise and limitations of SaaS
To answer this, it’s useful to look at the recent evolution of digital transformation in businesses. The development of cloud computing has led to increased integration of software to drive transformation, leading to a surge of applications and services and the rise of SaaS.
Predictions say that cloud-native applications will soon match the numbers of apps developed over the last four decades. Businesses are choosing to go cloud-native because of the ability it provides to cater to specific digital transformation needs, while SaaS has in turn replaced legacy solutions because it can handle the increased demand for cloud-native apps.
However, the issue with SaaS is that the one-size-fits-all nature of these solutions are not always the best fit for individual sectors and business needs, undermining that very objective of using digital transformation to address needs that are specific to a business in order to gain and maintain and a competitive edge. What’s more, multiple competitors using the same ‘out-of-the-box’ SaaS solutions soon begin to appear homogenous to customers.
Finding a way to mine the core simplification and speed benefits of SaaS while customizing applications to individual business needs has become the core challenge of digital transformation today.
No-code and GenAI: a perfect pairing
This is where no-code technology has entered the conversation. No-code platforms allow users who don’t have formal training in software development to develop applications using visual drag-and-drop tools. Far from needing to understand a programming language, the only skills that are really necessary when using no-code platforms to develop business applications are problem-solving and, crucially, a good understanding of the business and its processes. Combining these two things ensures applications are optimized to the organization's individual needs.
No-code fuses the speed and accessibility of SaaS and the customization qualities of traditional software development by offering businesses a way to democratize the process of developing applications. It helps enterprises meet their application backlogs by helping to address use cases from customer-facing applications to workflows, where every employee can quickly and easily contribute to solving unique business challenges.
GenAI also comes into play here as a powerful catalyst for no-code development; this is a great example of where AI can already be making a huge difference in any enterprise today in a very simple way. It allows enterprises to streamline application development and hugely speed up the process by automating tasks. For example, it can be used to convert user requests straight into application templates or frameworks, eliminating a whole step from the development process.
It can be used to automate and speed up workflows and processes across a business, from project management to customer privacy and regulatory compliance, to employee lifecycle management. One government institution used this technology to roll out an application to thousands of users to automate complicated project management processes - 95% of the app was built without the institution needing to write a single line of code.
Myth-busting GenAI and no-code
GenAI and no-code technologies are being used together as part of a natural progression of digital transformation. Far from replacing jobs, they are fueling the speed of innovation by creating citizen developers out of employees, helping them build applications which work specifically towards the distinct goals of the business , automating mundane tasks, and freeing up developers and other departments to focus on those activities that are really going to move the needle.
The no-code market is forecast to generate $187 billion in revenue by 2030, growing from $10.3 billion in 2019, matching the growing demand for more and more specific software applications and showing the appetite for a tool that offers freedom and flexibility to design applications that not only work for their business but become the driving force behind its competitive edge.
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