2023 has been the breakthrough year of generative artificial intelligence. From predictive models that assist with accurate forecasting and foster better decision-making to leveraging generative AI tools to empower developers in building enterprise-grade applications faster, artificial intelligence, specifically GenAI, opens up several new avenues of opportunities and benefits. It has become rather understood that enterprises must embrace this technology to streamline business processes or risk falling behind their competitors.
Over the past years, low-code development platforms like OutSystems have been gaining traction mostly because of how it accelerates software development and helps fill development gaps. And now, low code AI is set to further advance the playing field with its AI-coding assistants, process automation, and advanced auto-completion. In fact, the new low code generative AI era will lower the rapid application development barrier, with enterprises already incorporating low code practices and operations to their enterprise operations.
Here we discuss the prospects of AI low code development, the popular low code AI tools to invest in, and what to expect from this unification of two impressive technologies.
Breaking down low code AI: What it means?
Let’s start by first defining low-code development. While most are aware, low-code software development involves leveraging visual development environments and drag-and-drop interfaces to build enterprise-level applications fast, right, and for the future without spending hours in extensive coding. Such apps can be employed to build customer-facing apps, core apps, or internal business apps, serving four major use cases – customer experience transformation, workplace innovation, process automation, and legacy app modernization.
Now let’s explore the role of AI in software development. Fundamentally, artificial intelligence mimics human intelligence using algorithms and data. It might automate manual tasks or even replicate cognitive functions. Essentially, AI software development takes care of a great deal of repetitive tasks when building a software application. This includes manual testing, creating/updating UI elements, code duplication, developing layouts for multiple screen resolutions, configuring build scripts, and more. Advanced AI-assisted software development even takes care of data analysis, provides recommendations, fosters intelligent decision-making, and advanced problem-solving.
Low code AI brings together machine learning models, natural language processing, image recognition, and other AI capabilities into rapid application development. The combination of low-code and AI enables faster development and deployment of AI-powered applications, making it more accessible to a broader range of developers and organizations.
How can low code and AI coexist?
The capabilities of both GenAI and low-code development platforms are perceived to be synonyms as both technologies help in accelerated code generation. However, one distinct difference between the two is – generative AI is targeted towards professional developers while low-code technology is targeted towards citizen developers.
While generative AI is a great way to bridge the gap between cognitive human intents and computer algorithms that solves challenges, software development has a much broader scope spanning across architectures, data modeling, product engineering, maintenance, support, and more; all of which go beyond the capacity of generative AI. Therefore, the only possibility for AI is to enable and empower low code development environments. And on that note, low code AI will co-exist together, enabling faster innovation, enhancing efficiency and unlocking rampant automation for every industry, much to the likes of OutSystems AI.
Key benefits of low code AI software development
The infusion of low code AI for software development opens up doors to incredible opportunities and technical advantages, all directed towards improving customer experience, product quality, and improving the software development process. Here is a technical breakdown of low code AI software development:
- Accelerated time-to-market: With AI-driven automation and accelerated rapid application development with low-code, technical teams don’t need to focus on repetitive tasks. Low-code development platforms like OutSystems enable developers with varying expertise to leverage its visual development environment and pre-built components, without spending hours in hard coding, hence simplifying and expediting the development process. Integrated with AI, developers can leverage machine learning models and NLP algorithms for faster prototyping, testing, and deployment. Overall, low code AI software development shortens SDLC and accelerates time-to-market of software products.
- Endless task automation: Low code AI automates repetitive tasks like code generation by analyzing patterns in code, suggesting improving and even providing code snippets. In rapid application development, AI can be used for intelligent test automation to deliver superior software quality. AI algorithms integrated to low code development platforms automate bug and vulnerabilities detection in the code by analyzing patterns and historical data. Natural language processing capabilities in low code AI assists with workflow automation and automating various steps in the CI/CD pipelines.
- Enhancing customer experience: With personalization a critical differentiator of customer experiences, AI ensures that enterprises deliver it across channels and devices. AI algorithms analyze user behavior and preferences, resulting in tailored experiences that boost engagement and retention.
- Predictive modeling: The heart of AI’s technical power is predictive modeling. Using advanced algorithms and machine learning, AI can make data-driven predictions of next steps in logic flows, identify potential application issues, and anticipate user behavior and market trends.
- Improved decision making: AI algorithms can analyze large volumes of data in real-time, providing valuable insights and actionable intelligence to developers and stakeholders. By integrating AI capabilities into low-code platforms, developers gain access to powerful analytics tools that enable data-driven decision making throughout the software development process, from design and testing to deployment and maintenance.
- Scalability and flexibility: Low-code platforms with built-in AI capabilities offer scalability and flexibility, allowing applications to adapt and evolve based on changing business requirements and user needs. AI-powered features can automatically adjust to new data patterns and user behaviors, ensuring that applications remain relevant and competitive in dynamic market environments.
- Reduced technical complexity: Low-code platforms abstract away much of the technical complexity associated with software development, making it easier for non-technical users to participate in the development process. AI further simplifies development by automating complex tasks and providing intuitive interfaces for configuring and deploying AI-driven features, democratizing access to advanced technology for a broader audience of developers.
- Increased productivity: Low-code platforms abstract away much of the manual coding traditionally required for application development. AI augments this by automating tasks such as data analysis, natural language processing, and image recognition, freeing up developers to focus on higher-value tasks. This results in increased productivity and efficiency throughout the development lifecycle.
OutSystems AI: Unlocking the power of AI-driven rapid application development
According to Forrester’s Total Economic Impact Study commissioned by OutSystems, organizations experienced a 50% faster time-to-market for applications developed using low-code platforms, with AI-driven automation further accelerating development processes by up to 30%.
Here’s how an AI-driven high-performance low-code platform results in 100X productivity increase and 30% increase in team skills:
| AI enables developers to streamline repetitive tasks: | When combined with the benefits of high-performance low-code: |
| Coding | Governance required to safely reap AI’s benefits |
| Debugging | Power to deliver whatever the business asks for |
| Testing | Agility to adapt apps to evolving business needs |
| Deploying | Security to build mission-critical customer apps |
| Scalability to grow with your success |
In efforts to unlock the full potential of AI-led software development, OutSystems has infused AI to its rapid application development platform, unveiling OutSystem AI – the AI-powered high-performance low-code platform.
The idea behind this platform is to make the lives of developers and IT teams easier by handling the repetitive and mundane tasks of building apps fast and for the future. Whether it’s having AI mentors guide them through development, adding AI to their apps, or both, your developers and IT teams encounter less friction and get more done faster.
Here is how OutSystems AI empowers AI-driven software development:
#1: AI Mentor System
The superpower of OutSystems AI is its Mentor System aimed at enhancing the expertise and lives of developers with powerful AI guides called mentors. Just like the living world, mentors are experts that assist developers throughout SDLC; guiding, automating, and validating the work of developers. AI Mentor System empowers developers to be more productive and develop high-quality mission-critical applications fast, right and for the future.
- AI Code Mentor: An AI-based coding expert that assists developers throughout complex builds, saving time and enhancing productivity.
- AI Architecture Mentor: Embedded AI-based enterprise architect that ensures your code meets architectural standards
- AI Security Mentor: An AI-based security lead that constantly reviews your code to check for inconsistencies, vulnerabilities, and future issues.
- AI Performance Mentor: Functions like a performance expert that ensures your app is stable, secure, and at peak performance levels.
- AI Maintainability Mentor: Your very own analyst that runs through your app looking for ways to reduce technical debt and ensure you follow all the best practices.
#2: AI Agent Builder
OutSystems AI Agent Builder makes it easy for you to build your AI agent without too much coding. This way, you get to channelize the power of generative AI to your apps and workflows. It employs the large language models (LLM) and retrieval-augmented generation (RAG) models to provide speedy and highly relevant responses. LLMs in AI Agent Builder reads and understands user queries to generate human-like text. RAG looks for relevant details in the user query and searches for answers from a large dataset to result in even better responses. Together, RAG and LLMs result in contextual inputs, delivered by your very own AI agent.
To test its own technology, OutSystems rolled out its own AI agent built using Azure OpenAI models, and RAG to access internal data sources like related documentation. It is known to ease the lives of customer support reps who instead of answering all user queries, can now focus on critical ones while the AI agent provides accurate and relevant answers. Also, it has improved response time and improved support reps’ productivity.
#3: ChatGPT connector
OutSystems AI empowers you to seamlessly integrate ChatGPT to your existing applications in mere minutes, improving user experiences. Named ChatGPT Connector, you can find it in the OutSystems Forge repository.
Consider this example in the insurance industry. When selecting insurance policies, customers often struggle to compare from amongst the overwhelming number of options. With ChatGPT connector embedded into your apps, users can instantly compare different insurance policies, evaluate their differences, and generate the summaries of different coverages. Based on all this analysis, the policyholder can choose the right one.
Other use cases include:
- Document summarization: Department verticals, especially legal and finance struggle with analyzing and summarizing lengthy contracts and documents. With the ChatGPT connector, you can easily build apps embedded with ChatGPT, and it can provide recommendations, summaries and insights.
- Customer support: The ChatGPT connector when embedded in your virtual assistants can improve your response time and answers. Utilizing NLP algorithms, these virtual assistants can provide personalized responses, answer questions, and perform tasks, improving customer experiences and rep productivity.
- Personalized recommendations: The OutSystems ChatGPT connector when embedded to your web store, social store, app, or portal can provide personalized recommendations, reading a user’s historical data, preferences, behavior, most browsed items, and more.
Accelerating rapid application development with OutSystems AI
There are several industry-driven use cases where OutSystems AI simplifies user experiences and productivity. With existing OutSystems apps, you can easily incorporate AI functions to your apps leveraging its pre-built components seamlessly integrated with AI models.
The bottom line is AI revolutionizes your software development in a way that empowers you to stay competitive. In today’s evolving landscape, incorporating AI is not an option, it’s a must. With the AI revolution catching heat, our team of OutSystems developers have been assisting several enterprises across BFSI, healthcare, eLearning, and logistics and transportation in implementing AI to its core functions. As an OutSystems Partner and System Integrator, we are committed to ensuring that your IT and development teams embrace AI and low-code together to build transformative solutions.
