Low-Code & No-Code AI: Democratizing Automation in Enterprises

Building software using complex coding patterns are now becoming the things of the past and all thanks to drag and drop features of low or no-code platforms. The need for skilled developers to assist us with complex coding and get applications did hinder our productivity a lot. It came with processes like understanding the requirement, working on the design, execution, testing and then deployment. So, there were several aspects that came with the traditional development approach. It not only proved to be expensive but also time-consuming.

But, the entrance of low-code and no-code platforms did flip the script.

Businesses are benefiting significantly by automating their tasks through low-code and no-code AI platforms. It helps them develop a custom software for their business and that without any specific need of coding skills.

Being able to leverage this can certainly help businesses of all sectors to gain an edge in their industry. So, here we are going to discuss about every aspect related to low-code and no-code AI including:

• The need of low-code and no-code AI
• The stats or numbers that proves this shift towards automation.
• How enterprises can benefit from this implementation
• What are low-code and no-code platforms?
• How these platforms can affect software development service providers
• Real world examples

So, read on and get a complete hang of it to gain an edge.

Why It’s Time To Look Beyond Traditional Software Development?

The traditional software development approach has certainly helped many businesses stand out but now it’s literally making things stagnant with the availability of even better approaches. Now going for traditional way can lead to challenges like:

• More Expenses: Certainly one of the big challenges that one may face is in the form of high-costs that comes through hiring of the developer and maintenance team.
• Time Taking: Another major issue that comes along the line of traditional approach is that it comes with a lot of steps. So, it might not help you respond quickly to market changes and eventually there can be several missed opportunities.
• Future Updates: Lastly, if the application has been deployed, it will require consistent maintenance and updates to keep it away from possible bugs and threats. This can eventually cost you more and also downgrade your service experience.

These challenges highlight why it’s time for businesses to move beyond traditional approaches. Read on to know how.

The Need of Low-Code & No-Code AI

The use of low-code and no-code platforms has helped businesses to get software development done using:

• Visual drag-and-drop interfaces.
• Pre-built modules.
• And even AI-based tools.

One will be able to complete the complex enterprise software solutions without having to be skilled in coding. So, it makes the development process quite hassle-free and assists businesses enhance their operations through automations.

The best part is that the numbers are the same and below we highlight it precisely, check it out.

Stats Proving the Shift

• Gartner finds that, by 2026, 75% of new applications will be built with low-code tools, with AI-powered automation generating $5 trillion in productivity gains globally.
• The low-code automation market is estimated to reach $21.2 billion by 2022 (up from $4 billion in 2019).
• By 2025, more than 70% of new enterprise applications are expected to employ low-code or no-code tech; a clear sign of speedy general assimilation.

Why Enterprises Embrace No-Code & Low-Code Solutions?

Low-code and no-code platforms are being adopted for three main reasons:

• Speed and Agility: One of the primary reasons to consider going for low code and no-code platforms is that it allows teams to turn ideas into products in a matter of a few weeks. As it comes with a simple drag and drop facility, the developers can respond to market changes, innovate faster, and sustain a competitive advantage.
• Developer Shortage: With an ongoing global shortage of skilled developers, many organizations are experiencing bottlenecks and delays in their projects. Low-code and no-code solutions empower citizen developers, business users with no coding experience, to build and deploy applications without help from traditional development teams.
• Cost Effectiveness: By being less reliant on traditional developer teams and enabling rapid app creation, organizations experience substantial cost savings through low-code and no-code options. Less time and effort are required to maintain, deploy, and upgrade applications. Additionally, subscription-based pricing models create budget predictability.

What Are Low-Code and No-Code Platforms?

When it comes to low-code platforms, it helps the users to work on the applications just with the use of minimal coding. With the help of the respective platforms, you will benefit from visual development tools, pre-built components and easy integrations. All these aspects will simplify the coding process and assist you get your software without a lot of complexity. Some of the popular low-code platforms are:

• Mendix
• Appian
• Microsoft Power Apps
• Zoho Creator
• OutSystems
• Appsmith

No-code platforms are software development tools built for those who know nothing about programming. Instead, they use a visual workflow, form builders, or automated connectors to create enterprise solutions, automatically execute business processes, and develop AI applications all without any code. Below are some of the popular no-code AI platforms, check it out:

• Data Robot
• Lobe
• Nanonets
• Amazon SageMaker
• Obviously AI

Now when you are clear about what no-code platform stands for, lets understand how one can develop AI applications using the same.

How to Develop an AI Application Without Coding?

Building an AI application without code on no-code platforms it basically means:

1. Picking a no-code platform (for example: Microsoft Power Platform, Google Vertex AI, or Mendix).
2. Using drag-and-drop tools to design the workflow without code.
3. Incorporating pre-built AI models, data connectors, and APIs into your workflow.
4. Testing and iterating through the process usually with automatic deployment and testing.

These platforms abstract all the underlying complexities of logic, allowing the user to purely focus on logic, decisions, and integration. Let’s now get a hold of its impact on software development service providers to get complete clarity.

Impact on Software Development Solution Providers

Software development companies are responding to low-code and no-code AI platforms. These concerns allow these firms to come up with AI and ML development services that are faster, scalable and more accessible for companies of all sizes.

1. Development Services for AI and ML

Development companies can leverage no-code platforms to speed up creating AI and ML applications while changing the nature of coding. This also allows providers to deliver a solution faster while maintaining quality that enables enterprises to automate, without waiting or dealing with long development timelines.

2. Build Quickly, Customize, and Iterate

Instead of relying on professional developers to build applications, providers will enable clients to customize their workflows and AI models through training on the no-code platforms. This will allow companies to build or adjust their solutions quickly, and enable continuous iteration, and agile response to the business environment, without relying on professional developers.

3. Process Reengineering and Training Citizen Developers

With code developers marginalizing their function, provider solution architects are redesigning business processes and engineering systems for the possibilities of no-code environments. They will also be training business users in organizations to be citizen developers to facilitate the build process until the business is completely self-sufficient in code-free automation and AI application build.

Enterprise Solutions With Real-World Examples

Leading organizations demonstrate concrete uses of low-code or no-code AI platforms and realize considerable value from automating and connecting foundational business activity.

* Automating supply chain workflows

For example, Siemens is using those platforms to automate supply chain functions to eliminate manual errors, improve reliability, and respond more quickly to activities and events. They additionally connect suppliers, inventories, and logistics to automate workflows at the front-end and back-end.

* Customer engagement applications

As another example, Schneider Electric is utilizing no-code platforms to create applications to drive customer engagement, leveraging data to personalize interactions, onboard customers, and serve requests to increase customer satisfaction and retention.

* AI-Powered Predictive Analytics Dashboards and Legacy Import

Lastly, DBS Bank has taken those platforms to integrate and create AI-powered Dashboards for predicting trends in business and customer behavior. Low-code and no-code platforms also support integration of legacy systems with cloud and IoT ecosystems to manage business continuity and scalability across enterprise tech stacks.

AI and ML Development Services Trends

The advancement of AI and ML services has been greatly influenced by no-code platforms, reshaping prototyping, deployment, security, and consulting methods for enterprise automation.

1. Fast Prototyping and Model Deployment

No-code solutions accelerate designing and implementing AI/ML models for teams, enabling both data scientists and business operators to test ideas and deploy solutions rapidly, allowing for easy evolution and improving project timelines.

2. Automated Workflow Design With Built-in Security

Today’s AI services provide automated workflow design within the process, with enterprise-level security built-in. This functionality reduces risk and provides compliance with regulatory treatment of sensitive and customer-facing data while being operationally efficient.

3. Consulting and Integration on Intelligent Automation

All the services highlighted are focused on integrating AI with the enterprise’s current applications and data lakes and leveraging consulting services. As organizations consider AI implementations, the consulting helps with the decision to segregate the best automation strategies and define the decisions associated with intelligent automation, which would help organizations increase their investment in AI and automation.

Chart: Adoption of Low-Code/No-Code AI (2019–2025)

Below is a chart visualising projected adoption rates for low-code/no-code platforms, based on cited research and analyst reports.

Image Source

Key Benefits for Enterprises

Low-code and no-code solutions offer a remarkable opportunity for businesses to accelerate innovation, reduce costs, and scale successfully in an ever-evolving digital economy.

• Time-to-market accelerators: Business can accelerate innovation cycles by going from ideation to deployed applications in days instead of months. The ability to respond quickly to market needs enhances competitive position as well as customer satisfaction.
• Cost reductions: Reducing reliance on high-cost developers is a substantial cost savings. The efficiencies created by faster development cycles combined with simpler maintenance also help organizations increase their budgets and maximize returns on investments in automation.
• Increased alignment of business and IT: Elimination of silos between business units and IT results in collaborative work and shared ownership. Communication improvements mean improved solutions that meet both compliance and real world needs.
• Limitations & Challenges: Even though they hold the prospect of transformative impacts, enterprises must be strategic in addressing the limitations of low-code and no-code platforms.
• Limitation of Customization: While the aim is to move away from using traditional developers, highly customized and complicated applications need traditional development skills to extend and fine-tune capabilities beyond platform capabilities.
• Security and Compliance Risks: Visual tools and platforms can also create governance risks if traders or developers do not complete reviews on the IT side; therefore, it is good to have a rigorous framework to ensure the enterprise meets security, privacy, and regulatory compliance levels.
• Complexity and Scalability: Some of the very complex enterprise systems might exceed the performance and architecture demands of platforms, and recognize that organizations may leverage both low-code/no-code and traditional development work low-code/no-code.

Future Trends in Enterprise Automation

In the future, multiple new trends will be driving the continuing evolution and adoption of low-code and no-code AI platforms within enterprises.

• AutoML Capabilities: Upcoming platforms will include automated machine learning capabilities, allowing even the most non-technical user to quickly deploy advanced AI models with little expertise.
• Edge AI: Future automation technologies will enable the deployment of AI and automated workflows directly on edge devices, such as IoT sensors, meaning that AI can be executed for real-world applications, close to the data available.
• Enterprise-level Security and Governance: The current trend toward enterprise-level security capabilities, compliance automation, and governance capabilities will be enhanced to accommodate the growing enterprise and regulatory requirements, while maintaining agile capability.

Final Thoughts

So, this shows how low-code and no-code AI platforms play a key role in transforming the next-gen enterprises with complete automation solutions. Businesses will be able to work on having AI applications that not only automates fundamental business practices but also assist them remain competitive in the respective market. One can always consider taking assistance from skilled custom software developers who can assist them in terms of design and security.

If you are looking for assistance for low-code and no-code AI platforms for democratizing automation, then you can always knock on the doors of LL Technolab for all the answers.