Today, organizations must do more with less. The pace of innovation has increased exponentially, yet resources remain the same (or are dwindling). Between talent shortages, long development cycles that rely on traditional programming languages, and technology teams that are already stretched perilously thin, many businesses have glaring operational problems they simply can’t solve with their current resources.
But two technologies offer a solution, promising rapid development and ultra-fast time to value for investments:
AI. Artificial intelligence (AI) has a wide range of applications—from using generative AI and natural language processing to create code or interfaces to decision-based AI that enables greater process orchestration and data processing.
Low-code. Low-code tools expedite development processes via visual interfaces. They also keep AI in check by enabling strong governance that reduces the risk inherent in generative AI-based development.
Together, AI and low-code make a powerful combination that enables both developers and non-technical users with limited or no coding experience to build valuable applications.
Today, we’ll talk about four things to know about AI and low-code development—from applications of the technologies to reasons why the two work together so synergistically.
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Applications are built on forms, and creating them takes time. Typically, you’d have to use traditional manual coding techniques that involve front-end development and CSS to style the form, back-end coding to process data, database work to store it properly and tune the performance, and a whole lot more.
Or you could just upload a PDF form into Appian.
With Appian’s new AI Copilot feature, available as part of our 23.3 launch, you can upload a PDF and have Appian generate a well-designed form that works perfectly within your applications:
With Appian, you can generate an interface from a PDF form in just seconds—and all the extra work is done for you. It’s critical to build strong interfaces to drive adoption among your users. And following strong UX-design principles ensures people can accomplish their tasks quickly, leading to immense time and cost savings.
How much time do you think your organization spends on processing documents (filing them out, sending them to the right people, and inputting data to the correct system)? Hundreds of employee hours? Thousands? What about correcting errors?
AI can handle a lot of this for you. For example, in the Appian AI Skill Designer, you can create private, custom models trained on your own data. Appian AI Skills covers a number of tasks, including:
Document classification: AI can automatically understand and categorize the type of document it receives—from bills to tax documents to medical forms and more. This makes it easy to know how best to route information.
Document extraction: The AI can pull critical information from a document and prepare it for use in your applications. When combined with document classification, this helps automate the vast majority of document processing, freeing up workers for other tasks and reducing manual data entry errors.
Email classification: You can also build an AI model that classifies incoming emails so you can then route the emails to the appropriate team or worker. You simply upload a representative sample batch of emails, then the system will train on your data. With this AI Skill, you can save a significant amount of time by routing to the appropriate group.
Simply create these skills, then drag and drop them onto your low-code canvas so they can become part of a process. And you can easily tweak and modify the skills to optimize model performance whenever you need.
[ Want to succeed at AI? Get specific about your use cases. Learn how by watching the Appian World presentation: 6 Ways AI Makes a Difference to Your Business. ]
McKinsey notes that generative AI could dramatically improve development speed—but that it requires additional features to truly maximize the benefits and avoid potential risks. With generative AI alone, developers have to understand the technology, coding languages, and programming frameworks they’re working with to be able to generate rapid results and do so without introducing errors—or even security vulnerabilities.
Platforms that offer low-code development and design make this a non-issue. With built-in governance and robust security infrastructure in place, placing generative AI into a wider low-code context helps you achieve the rapid speed you want with far greater quality and fewer risks.
For example, take the case of an organization working in a highly regulated industry like financial services. With generative AI alone, you’d have the AI create code, but you’d need to check it to ensure it complies with the latest regulations and doesn’t introduce any vulnerabilities that could lead to a data breach. This requires a lot of expertise that generative AI alone simply can’t provide. A strong platform with multiple compliance and security certifications reduces the knowledge barrier and can help you avoid potential business risks. This is only one example, but having a strong AI-powered process platform that includes low-code gives you a significant amount of additional tools that supercharge generative AI and help you realize its full potential.
Building an application or deploying technology is not the end goal—providing business value is. This is the goal behind digital transformation: to change the way organizations do business in a way that produces massive ROI.
Building on the previous point about combining generative AI and low-code in a platform, AI-powered process platforms enable you to orchestrate full end-to-end processes using multiple hyperautomation tools. You can build solutions to handle small tasks, such as invoice management, or bigger activities, such as an entire billing process. The best platforms provide this power, where AI is only one tool among several—including robotic process automation (RPA), API integrations, business rules, and more.
Low-code and AI are force multipliers for both development teams and business units. When you place low-code and AI into the context of a wider AI-powered process platform, you get other tools to speed up development as well as business processes. Consider just a few of these tools:
Data fabric: A data fabric architecture allows you to unify data from multiple systems to enable secure and easy access to enterprise data and deliver a 360° view of the business.
Process automation tools: A good platform will offer multiple built-in tools to connect people, systems, bots, AI, and business rules in end-to-end process automation. This helps not only speed up development, but also offers the ability to speed up the entire enterprise with up to 95% faster operational processes.
Process mining: Process mining capabilities allow you to mine the data generated by your solutions to automatically identify bottlenecks, process non-conformances, and the root cause of issues inhibiting your digital transformation goals.
Total experience: Instead of having to have strong knowledge about code across devices, a good platform will offer the ability to design seamless, beautiful experiences across desktop and mobile devices.
Want to learn more about AI and low-code? Watch our latest release webinar replay to learn more.