7 Capabilities to Look for in Low-Code AI Tools

Artificial intelligence (AI) can transform the way your enterprise does business—but if you can’t quickly implement AI in your business processes, you’ll just as quickly fall behind competitors. This is where low-code AI tools can help.

Over the past decade, low-code platforms have enabled software engineers, professional developers, and employees with minimal coding experience to build new digital, automated solutions using drag-and-drop interfaces. Paired, low-code and AI tools are a powerful option for optimizing entire enterprise processes. 

This blog post covers seven capabilities you should look for in low-code AI tools to get the most speed and efficiency with the least risk. 

Low-code AI tools should make it easy to build custom AI models—they shouldn’t require you to hire an extensive team of data scientists and data engineers or invest heavily in new infrastructure. For example, with Appian AI Skills, if you want to create a high-quality model to classify and extract information from incoming documents, you simply upload a batch of documents and have Appian perform the model training process on your behalf (then review and tweak the results yourself as needed). Easy as that, this document extraction and classification AI model—trained on your own data—lets you save you time, achieve incredible accuracy, and shave hours off a manual process.

To help developers create new digital solutions even faster, look for low-code AI tools that automate elements of workflow creation. For example, Appian enables developers to go from a PDF to a fully-designed application interface form in just a few clicks. That means developers avoid spending time building front-end code, transforming data and preparing it for databases, and styling interfaces with CSS. Instead, they let AI do the work and tweak the output as needed in Appian’s low-code design studio.

Board members and business leaders alike are mandating the use of AI in business. It’s not really a question of “Will you use AI?” but rather “How will you use AI?” But keep this in mind: simply meeting the mandate to use AI in your business isn’t enough; you need to get a tangible return on your investment. 

AI process platforms that take a low-code approach are purpose-built to help organizations design, automate, and optimize end-to-end processes. This way, you can place AI into a large process and have it immediately generate real value. 

For instance, you might already have mapped out a customer service process involving multiple apps. With a platform approach, you can easily integrate generative AI tools that incorporate natural language processing into your customer service applications to help reps craft effective response emails fast. And the impact on the business is immediate.

Low-code AI may grab much of the spotlight, but achieving end-to-end process optimization requires multiple tools, including robotic process automation (RPA), API integrations, and workflow design. AI isn’t a skeleton key—sometimes, an RPA bot is what’s needed to do the trick. For example, procedural, step-by-step tasks like entering data into a system lacking an API would be better served by RPA, which can be more precise than AI since they are programmed with specific business rules (especially considering the possibility of AI hallucinations). 

Remember that AI is one tool among many, and the best low-code AI tools will provide multiple automation capabilities.

AI depends on data. Whether you’re using AI to route emails, generate interfaces, study metrics to make predictions, or produce data visualizations, everything relies on your underlying data infrastructure. Yet, too often, data remains locked in disparate data silos, making it challenging to operationalize AI. 

Look for low-code AI tools that are paired with data fabric capabilities, which help unify enterprise data and provide a 360-degree view across systems. Instead of migrating data, a data fabric allows you to work with your disparate data sources in a unified virtual data layer. With a data fabric, you don’t have to move or refactor data to make it available for use by AI models.

To enable the data-driven decisions your business needs to move forward confidently, look for low-code AI tools that give business users tools to explore enterprise data. A conversational AI chatbot is a user-friendly way to accomplish this. When you add analytics capabilities, it also helps users discover trends in the data. 

If you’re an Appian customer and use Appian for case management, you could use this aspect of Appian AI Copilot to synthesize case information, understand its history, and suggest or summarize next steps.

Many AI tools available on the market come with privacy risks. While some companies choose to take on this risk, heavily regulated industries like healthcare, pharmaceuticals, or public sector organizations can’t take chances. Accidentally leaking protected health information will lead to heavy fines. Look for low-code AI tools that are part of a platform that has already invested greatly in security and compliance. 

Beyond that, low-code AI tools include governance frameworks that ensure you don’t unknowingly introduce security concerns. Most of the coding has been completed by teams of developers and reviewed by security experts. You won’t have to worry about introducing vulnerabilities due to AI hallucinations or training issues—the low-code platform development team has done the work on your behalf. 

In the AI era, all organizations face incredible pressure to innovate fast. You’ll lead the pack if you can leverage enterprise AI in a way that quickly generates solid value for your business.

Combining AI with low-code can help you do just that by streamlining development and offering a seamless way of integrating AI into your operations. These tools also come with the added bonus of built-in security and compliance features to help protect your reputation (and reduce your risk of hefty fines). In a nutshell, low-code offers a no-nonsense way to quickly and safely get your business ahead in the AI game.