Artificial Intelligence (AI) is arguably one of the most pivotal technological developments of the 21st century. However, we have only barely scratched the surface when it comes to truly tapping into the vast potential and applications of such a technology. The pace, as well as the manner in which AI, robotics, automation, etc. have evolved in the last couple of years have changed our lives immeasurably and irrevocably. Be it a large, global conglomerate or the average consumer, AI impacts nearly everyone who interacts with technology today. And judging by the rate of developments in the tech sphere, it’s safe to assume that this influence is only going to increase substantially in the very near future.
Artificial Intelligence for real customer engagement
Individuals who interact with technology in their daily lives do so to meet a need of some sort. This could be the need for information or the need to avail certain services that are more conveniently accessible on their mobile devices, as opposed to the traditional way of interacting with businesses through offline channels. There is an increasing demand for personalized experiences, which necessitates the application of a technology such as AI. Some of the most successful digital brands have created an enviable position for themselves in the market, simply by providing consumers with a personalized experience on digital platforms. Using technology which maps the customer journey and predicts a user’s possible reactions for more favorable outcomes, these new-age digital businesses are dethroning big and established brands by just being proactive.
Artificial Intelligence is capable of processing a substantial amount of data in a much shorter amount time as compared to humans, and performing routine or recurring tasks by identifying and following patterns across various processes. This makes it a technology that can be deployed both on an enterprise level, as well as on customer facing platforms to make certain processes more efficient. For instance, consider the example of digital lending applications, wherein AI-led risk assessment algorithms reduce the entire application and underwriting process to a few minutes. As a result, the consumers’ loan requests are approved within hours, instead of weeks.
AI-led platforms or devices are equipped with massive computational power that enable them extract and interpret relevant customer data from large, unclassified clusters of information through detailed analytical models. However, the ability to integrate AI algorithms with web or mobile applications is what makes it a key value addition to any modern business. Mobile apps have completely changed the rules of B2C (business to consumer) interactions. The intuitive capabilities of apps powered by artificial intelligence, with a good interface and experience, can draw more users and enable companies to carry out smarter conversations with them to turn them into customers. Intelligent apps which understand the “why” and “what” of a customer’s behavior or demands can help businesses identify what the user wants, and doesn’t, without having him/her say so.
Machine learning and data analytics provide a foundation for such intelligent apps to use the data that an automated application collects and turn into contextual insights to help businesses deliver a smoother experience or new feature that users seek. There is a significant amount of flexibility that AI offers app developers to enable them to create a seamless interface with third-party REST application programming interfaces (APIs), which allow them to use, and re-use, machine learning algorithms and learning services.
Unlocking the potential of low-code apps
The low code approach to app development can be quite effective for businesses that want to build and release their mobile or web applications quickly. For businesses, there are all sorts of benefits to building low code platforms. For one, the streamlined approach to app development is characterized by greater speed in designing and developing since it involves low or no code and often depends on integration with APIs.
Moreover, another key reason why organizations, specifically small and medium-sized businesses must take the low/no code approach is that it involves much lower expenditure as compared to traditional app development. Creating a tailor-made app for a large business may take several developers, a few months, and a lot of money. On the other hand, with a low/no code approach, that time can be brought down to a few days and much lower spends. In addition, apps with low/no code are also far less susceptible to bugs, which for developers is good news, since it considerably reduces the time it takes in testing as they use APIs that have already been tested by others before. Another important feature of low/no code apps is that they allow app makers to customize and optimize them quickly when they want to incorporate user feedback or introduce new personalized features.
Businesses are increasingly realizing the massive potential of both digitization as well as AI when it comes to attracting new customers and achieving growth. With a growing demand from consumers for digitally accessible, flexible, and personalized services, AI-powered applications can address the specific needs of users through advanced functionalities. Low or no code platforms are the future of app development, simply because they are quicker to develop and deploy, as well as much more cost-efficient. Furthermore, low code apps are also rapidly bringing about a significant shift in the overall app development ecosystem. They are replacing the cumbersome and redundant processes of the conventional development life cycle to make it a more creative and innovative space for developers and app makers alike.
(The author is the Founder & CEO at ONGO Framework – a B2B IT and digital solutions provider that helps SMEs and start-ups with enterprise mobility and digital transformation.)