Businesses of all sizes – from early-stage startups to global enterprises – are catching onto the power of AI to streamline operations, save resources, and boost innovation. However, turning AI projects into successes that generate real ROI is no simple task.
Organizations seeking to build their own, tailored AI solutions are often not able to invest in building out a data team, plus months of iterative development, data preparation, and algorithm experimentation – to say the least.
Meanwhile, technology advances so rapidly, that by the time IT teams research, build, and deploy one type of AI application, a new, more innovative solution has already emerged.
For those businesses that don’t have the time nor resources to dedicate to hiring an entire AI team and a months-long development cycle, low-code/no-code (LCNC) platforms enable them to reap the rewards of AI without the investment typically needed.
LCNC platforms enable users to build AI apps with little to no coding and technical know-how, thanks to their pre-built components and intuitive interfaces. They’re proving to be so impactful across industries that the LCNC market value is expected to growfrom $10.46 billion in 2024 to $82.37 billion in 2034, at a CAGR of 22.92%.
Let’s dive into why modern businesses should adopt LCNC for AI projects – and how they can do so.
The Power of Low-Code/No-Code for AI App Development
LCNC offers a whole host of benefits for AI app development.Here’s how it can help businesses supercharge AI projects to support growth and innovation.
Bridging the digital divide
LCNC applications enable users to build apps through intuitive drag-and-drop interfaces or a wizard with questions and drop-down menus, requiring little to no coding. They often include pre-built AI capabilities, such as image recognition, sentiment analysis, or predictive analytics, which can be integrated with a few clicks.
They make it easy to import, clean, and preprocess data, and simplify the integration of AI services (such as OpenAI, AWS, or Google AI) through API connectors. They often even leverage AI themselves, such as chatbots and recommendation systems that guide users to implement AI features.
All of this lowers the barriers to entry for AI app development and deployment. LCNC is paving the way to a new wave of ‘citizen developers’ – non-technical people who can now build business apps and web-based solutions without technical know-how.
In fact, Gartner predicts that by 2026, 80% of the user base of LCNC tools will be developers outside formal IT departments. With more people able to build AI solutions – from domain experts to business professionals – enterprises will see more innovative ideas and an expansion of potential AI applications.
Adaptability and flexibility
LCNC also helps businesses quickly adapt to changing circumstances and market demands.
Many of these tools are equipped with pre-built algorithms and ML models. This enables teams to constantly swap in the latest large language models and other components such as APIs, helping businesses keep up with the rapid pace of AI advancements.
Organizations can also use LCNC to quickly experiment with different ideas. Teams leverage LCNC’s rapid prototyping and testing capabilities, allowing them to validate and gather feedback on potential AI applications.
Increased productivity and resource efficiency
LCNC tools allow businesses to be more resource-efficient, both in terms of cost expenditure and team member labor. By helping to automate tasks such as data cleaning, model training, and error detection, team members can focus on more high-level, business-critical efforts.
Leveraging LCNC also increases the time-to-market for businesses building AI applications, as it eliminates the need for lengthy and costly development cycles. It’s estimated that low-code application development is 10 to 20 times quicker than usual coding methods.
Examples of low-code/no-code platforms
There are so many LCNC platforms to choose from – here are a few of the most powerful tools that businesses can adopt.
Microsoft Power Platform is a collection of low-code tools that help businesses build apps, automate workflows, and analyze data. For example, it includes Power Apps, which enables users to build apps from scratch with AI, and Power Automate, which automates repetitive tasks and workflows.
Salesforce’s Lightning Platform is another example of a powerful LCNC tool that helps teams create business process automation apps, with no need to code. With this platform, organizations can transform complex processes and Salesforce data into custom apps and intelligent workflows.
ServiceNow is also empowering businesses to innovate with its low-code and intelligent automation tools. Teams can build new workflow apps and intelligent automation with the platform’s suite of AI-powered tools.
Low-code/No-code Use Cases
Now we’ve discussed the benefits of LCNC for AI app development, let’s explore some real-world examples of where it could be leveraged.
In human resources, teams can use LCNC to automate elements of the hiring process. For example, they might use it to build an AI resume filtering tool that’s trained on their own data and analyzes resumes for matching skills and qualifications. They might also use LCNC to create workflows that automate onboarding processes, such as training schedules and collecting documentation.
For the supply chain industry, LCNC enables teams to implement AI models to predict customer demand and automate inventory management. They can also use it to optimize delivery routes and schedules, reducing transportation costs and improving delivery times.
For business process automation, the opportunities for AI app building with LCNC are endless. Just a few examples include document processing, data analysis and reporting, workflow automation, and compliance monitoring.
Within the realm of customer service, businesses can deploy LCNC to build AI chatbots that handle and resolve customer queries and recommend products. They might also leverage it to analyze customer feedback for trends and sentiment and automate the consolidation of customer inquiries across platforms.
How to Leverage Low-code/No-code for AI Success
So, how can businesses implement LCNC tools to build impactful AI applications? Let’s explore.
First of all, it’s crucial that organizations align AI application ideas with business objectives from the start. Teams should work to define high-impact use cases for AI based on the value they would deliver and perceived ROI. Even the most impressive AI application is useless if it doesn’t actually support business goals. Iterative testing and user feedback can help organizations establish the ideas that hold the most potential.
Next, businesses should consider the kind of IT oversight that will be necessary to leverage LCNC correctly and to its full potential. Even though NCLC eliminates the need for large teams of data scientists and technical staff, companies need to ensure that the performance, compliance, and security of the platforms used are being monitored and logged by IT professionals.
Data governance is also a crucial component of building accurate and ethical AI tools. Organizations should implement a data governance policy around the collection, processing, and storage of data with AI applications built using the LCNC tool. IT teams should also ensure compliance with the relevant data privacy and security regulations.
Finally, the team members using LCNC tools should have access to training that helps them make full use of the platform. Ethical AI use is again important here and may require dedicated guidance and training to ensure employees understand the boundaries of what AI can – and should – do on its own.
Low-Code, High Impact
LCNC could be the key in the door for businesses eager to deploy custom AI apps, without having to build out an expert AI team and spend months on data preparation and solution development. With LCNC, businesses can rapidly tap into the potential of AI to drive scalability, save on costs, and empower their teams.
