By integrating AI with low-code platforms, organizations can significantly improve the effectiveness of their software, apps, and programs while cutting down on the time and resources involved in the development process.
Combining the immense potential of artificial intelligence (AI) and low-code platforms can truly become a game changer for the global economy. Both these new-age technologies are transforming businesses like never before. By combining their prowess, firms cutting across industrial sectors can reach new heights of profitability and customer satisfaction. Microsoft has demonstrated how combining AI and low code can transform software development, process automation, and workflow management.
The technology giant has recently strengthened its low-code suite with AI, leading to the significant addition of Copilot to its development platform. While the complementary potential of AI and low code is manifesting in numerous ways, we deep dive into both these technologies, their complementary potential, use cases across the industry verticals, and challenges lying ahead that must be addressed to encourage wider adoption of AI-enabled low code development.
AI and Low code: What are these technologies?
AI is an umbrella term used for computer software that mimics humans’ cognitive functions to accomplish various tasks, including analyzing data, solving problems, and making decisions. The technology simulates the analytical capabilities of humans to interpret situations, make adjustments, and offer independent judgements. The primary skills included in AI are image recognition, data analysis, natural language processing, and problem-solving.
On the other hand, low-code development is specifically invented to reduce the time and effort involved in developing apps, software, systems, and programs. These platforms accelerate development by offering visual interfaces and a whole host of pre-built components. In low code development, developers work on a graphical user interface (GUI) that allows them to drag and drop elements , and connect them with APIs or any other third-party apps to create mobile/web apps, software applications, or system programs.
GUI’s user-friendly nature and drag-drop convenience make the development process very easy and effortless. No wonder, even individuals from non-technical backgrounds can build apps with ease with the help of low-code platforms.
AI and Low Code: How do these complement Each Other?
a) Agility and Effectiveness: While using low code can significantly speed up the pace of development, integration of AI can considerably enhance the effectiveness of the overall development process. AI can also automate repetitive activities. Its ability to offer code snippets can further reduce development time and effort.
b) Improved decision-making: From generating insights to offering real-time updates, AI can significantly improve the quality of decision-making in the low code development process.AI can also provide personalized recommendations and examine the crucial parameters of the entire development process; it can help develop efficient, stable, and productive apps and programs for their intended purposes.
c) Enriching User Experience: The integration of AI can significantly enhance the user experience, with features like virtual assistants, chatbots, and personalized recommendations becoming part of apps developed by low-code platforms. This value addition ensures continuous patronage from the target market and helps make the business sustainable over a longer period.
d) Data-Driven Applications: AI can parse the data to uncover patterns and future trends. While all these capabilities are desirable, apps with superior capabilities are hard to develop using conventional coding. However, a low-code philosophy with AI’s added prowess can help firms develop data-driven apps offering exceptional features and performance.
e) Wider Accessibility: Low code has democratized app development by making the development process simple and effortless. Anyone, regardless of the level of technical skills, can develop apps and programs thanks to user-friendly interface and drag-drop features. AI can further ease the development process by supplementing low code with capabilities such as natural language processing (NLP), robotics, and computer vision among others.
AI-enabled Low-code Platforms: Use Cases
a) Financial Sector: The use of AI-powered low-code platforms in the financial sector can prove enormously beneficial in detecting fraudulent transactions and pinpointing suspicious transfers of funds. The best part of these platforms is their ability to learn continually and evolve with time to further strengthen the safety of the system.
b) Healthcare Sector: The use of AI in low-code apps in the healthcare sector can centralise patient records, automate appointment scheduling, and aid diagnostics to enhance the effectiveness of the treatment procedure. The sector can also benefit from simulating capabilities offered by AI-based low-code apps in drug discovery, patient trials, and clinical research among others.
c) Retail Segment: Powered by AI, the low-code apps developed specifically for the retail segment can take engagement with prospective buyers to a different level altogether. These apps can offer personalized communications, quick service support, and faster purchase processing to create a win-win situation for all stakeholders involved in the industry’s value chain.
d) Manufacturing Sector: AI-equipped low-code applications can help manufacturing companies create, communicate, and deliver superior value to the target market. These apps can help in both inbound and outbound logistics.They can transform the business potential by tracking equipment health, anticipating maintenance needs, and supporting production operations.
d) Customer Support: The areas aplenty when it comes to applying AI-based low-code platforms in customer care divisions. The apps can automate a variety of customer care functions, including processing return requests, addressing billing concerns, and reducing response time to achieve elevated levels of customer satisfaction.
Challenges and Concerns
a) Data Quality: For delivering superior performance, AI-based low-code platforms rely significantly on the data quality . In fact, these applications and platforms are as good as the quality of data that is fed into them. This mandates all stakeholders to attach the highest prominence to the accuracy, quality, and integrity of the data used as input to run these apps, software, and programs.
b) Training and Skills: Organisations must invest in training employees to make the most of the AI-powered low-code platforms. Remember, training and skilling is a continuous process, and firms must run these programs continually to help employees keep up the pace with ongoing developments in the domain.
c) Ethical Concerns: The concerns related to the ethical use of the data in AI have become very prominent, and therefore, developers involved in low-code development must use the data without infringing on basic tenets of privacy, safety, and fairness.
d) Scalability: To make the AI-integrated low-code platforms the mainstay of the technology sector, the developers must work specifically on making these solutions scalable without mandating comprehensive changes in the existing infrastructure, systems, and processes among others.
AI and low code are among the most sought-after innovations, If used in conjunction, this duo can completely transform the software and automation industries. These technologies can equip businesses with abilities to develop cutting-edge apps quickly for achieving superior results on profitability and customer satisfaction. AI-powered low-code apps can also help elevate customer engagement and help organisations make informed data-driven decisions to strengthen customer loyalty.
The confluence of these innovations can also herald a new wave of innovation across the industry verticals spanning product categories and service domains. In sum, integrating AI and low-code can help firms tap a wealth of opportunities arising from the fast-changing business environment and become more competitive, productive, and customer-oriented in the process.