Pacing ahead to conquer the next-gen technology & drive business growth
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We have known software development to be a traditional process with detailed and complex cycles for a great deal of time. Technical projects which involve new-age technologies like artificial intelligence and machine learning are even more complex and require a dedicated team of skilled people for completion and execution. In the past few years, the rise of custom-built Low-Code/No-Code AI and ML solutions is changing development using drag and drop environments ensuring faster deployment cycles.
Why is Low-code/No-code on the rise?
With the pandemic still around, the demand for rapid digital transformation has triggered the growth of applications developed by organizations. There are not enough professional developers to meet the growing demand of skilled AI/ML experts, which has significantly contributed to the embracing of Low-code/No-code for software developments using custom AI/ML solutions.
Business Wire predicts a 44.4% growth of the
Low-code/No-code market by 2022 to $27.23 billion.
Another prominent reason for the rise of the Low-code/No-code model is innovation driving faster deliverability. With AI and ML taking on strategic importance in business, using Low-Code/No-Code development platforms with custom-built AI and ML technologies will help fasten development and reduce costs.
But before understanding how Low-code/No-code is transforming the AI/ML landscape, let us know more about Low-code/No-code and its growing popularity.
Difference between Low-Code and No-Code Development Platforms:
Low-code/No-code business platforms are primarily designed to solve all ongoing development challenges that organizations face. Rapid development and deployment allow IT teams to meet business requirements and keep up with the different stakeholders' demands. The Low-code development platforms involve less coding, a visual IDE environment, and a lifecycle management system. The approach offers to work and transform teams to excel in an agile way. Whereas, No-code uses a visual method to build applications without coding using drag and drop processes.
Key reasons for the growing popularity of
Low-code/No-Code fills the gap by empowering more business people to become developers and build and develop solutions with ease.
Low-code/No-Code platforms robust agility translates to easily adaptable techniques with code snippets and plugins available to deploy on the go.
With Low-code/No-Code development, visually stunning-fully functional applications can be created and modified by business users, reducing professional developers' burden.
Using the Low-code/No-Code approach, citizen developers can build applications much faster without coding.
The Low-code/No-Code platforms offer everything from design, development, integration, testing, and deployment together; business teams and developers have more time to create and innovate.
Gartner predicts, "By 2023, over 50% of medium to large enterprises will have adopted Low-code/No-code application platform as one of their strategic application platforms."
Now let us understand how the combination of Low-code/No-code and AI/ML shapes the future of software development.
How are Low-code/No-code platforms Democratizing AI/ML?
By 2023, Gartner expects democratize design trends to accelerate - expanding on the Low-Code/No-Code phenomena with the automation of additional application development functions to empower the citizen-developer. But for citizen developers, Low-Code/No-Code, in addition to being a more straightforward approach to software development, also represents a complete shift in mindset. With limited coding to think about, designing workflows leveraging the real power of AI/ML not only increases the speed of adoption but also reduces the barrier to entry to experiment with AI/ML.
The BFSI sector is rapidly adopting Low-code/No-code based applications due to the low cost of application creation, options of drag-and-drop, reusable components, which overall fasten the decision-making process related to development. For the BFSI sector, specifically, Low-code/No-Code based applications help financial business users to create data-driven applications without having any prior professional development knowledge.
AI/ML is used within the BFSI industry to streamline and optimize processes ranging from credit scoring, fraud detection, managing trading algorithms, etc. However, implementing these processes can take months to develop and go-live. With the combination of Low-Code/No-Code based AI/ML solutions, process development becomes more efficient, making organizations better decision-makers, saving them on time and cost.
Some BFSI applications that can be built using Low-code/No-codebased AI/ML solutions are:
Credit Rating Management
Trading and Credit Risk Management
AI-based Fraud Detection
Disputes and Complaints Management
TPA Claims Processing
Mortgage App Management
Agent / Customer Onboarding
Low-code/No-code is the future of software development. In times to come, more application development involving AI/ML technologies will be done by citizen developers using Low-code/No-Codeplatforms. For organizations looking to achieve the speed, agility, and enhanced digital capabilities necessary for optimizing customer experiences, Low-code/No-code is essential to deliver a full suite of best-in-class solutions and services.
At NSEIT we are committed towards helping businesses grow using our digital-native solutions. We can help you determine your Low Code - No Code strategy and help you plan a roadmap offering with significant benefits. You can also check out our other blogs on low code no code for more details or visit our Digital Transformation services section for more details, or drop us a mail at firstname.lastname@example.org
Assistant Manager, Presales and Solutioning
Shikhar is a part of the Presales and Alliance team at NSEIT - working with senior leadership on identifying and growing the strategic alliances in digital transformation practices disrupting the Banking, Financial Services, and Insurance space. He’s an MBA from the Great Lakes Institute of Management, Chennai, and takes a keen interest in new-age digital and analytics developments
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