By Ankit Ratan
A majority of modern business organisations, irrespective of their size, often need to design, develop and deploy complex technology projects. As they plan and execute such projects, they have to consider the strategic options of whether they should hire more people with required technological skills, or outsource the development, or perhaps buy an off-the-shelf tech product that can be quickly customised and deployed.
Few technology projects are as complex and challenging as the ones involving Machine Learning and Artificial Intelligence. Most organisations looking to embrace AI and ML solutions believe they cannot do so without having a strong tech team and data scientists on board. This was largely true until now. Today, we have No-code AI solutions that increasingly resemble standard off-the-shelf tech products and can be easily picked and deployed. They are also steadily gaining popularity as a faster and efficient way to implement AI-enabled applications without the accompanying hassles.
What is a No-code AI platform?
A No-code AI platform essentially requires no coding at the time of deployment. The no-code ML tools available today are enabling businesses to develop and deploy AI applications without any prior coding.
In fact, as AI and ML-based process automation has gained popularity among mainstream businesses, the demand for enabling platforms that are plug and play and which require no-coding expertise has skyrocketed.
This trend is particularly true in the BFSI industry, which has been forced to expedite its digitalisation strategies in the wake of the pandemic. Many banks and other financial services companies have found themselves struggling when deploying deep-tech solutions, often because there is a veritable scarcity of developers with the required expertise. Those who are available typically come at huge costs.
Like banks, other large businesses in non-tech industries who are considering deploying custom ML applications for their processes also do not always have inhouse ML experts, and are equally wary of sharing their data with third parties owing to data privacy concerns. For such use cases, no-code AI platforms are ideal as they can be deployed in-premise in order to quickly and easily automate processes.
Benefits of No-code platform
Software development has changed rapidly over the past few years and no code development platforms have seen a steady adoption, owing to their simple nature. These platforms are available as ‘guided’ platforms with drag-and-drop functionality, offering a simple yet completely automated ML application development. As such, these platforms allow even business or domain users with no tech expertise to quickly implement ML-based automation and improve their operations. The developers are in turn freed up to focus on solving more critical business issues.
No-code platforms offer other business advantages also, including operational efficiency, increased productivity and cost-savings, which help businesses allocate resources for developing additional applications that are customised to their requirements.
Usually the success of an ML project highly depends on its ability to collect, manage, and maintain a dataset and the more data it has, more are its chances of being successful. The success of a project using no-code AI will highly depend on the use case and level of maturity when it comes to data management. A successful ML application depends on the amount of data collected, feature engineering, architecture and testing.
Future of No-code AI platforms
In the current scenario, when organisations are forced to embrace cutting-edge technologies and automation just in order to compete successfully within their industries, no-code platforms have a clear business advantage. Many organisations are thus turning to no-code AI platforms to fast-track their automation journey and the trend is only going to gather momentum in the days and years to come.
(The author is Co-Founder, Signzy)
