# AI Forms \| Use Cases, Examples & Solutions Sep 26, 2025 by Ronan McQuillan AI forms are becoming an increasingly critical component within all sorts of workflows. After all, forms are some of the basic building blocks of how we empower users to interact with data and processes. With the ever-growing prevalence of AI, it only stands to reason that form-building would be one of the areas that’s most impacted. What’s tricky, though, is that the term `AI form` can refer to a few fairly different things, depending on context. Of course, one important element of this is utilizing AI tools to help us output form UIs more quickly and easily, often from a single natural language input. This is the aspect that most standalone form-builders prioritize. However, the term AI forms encompasses a wider range of solutions besides this, including traditional forms that trigger AI-powered processing downstream, as well as any form UIs that are relied on for human interaction within agentic workflows. In this comprehensive guide, we’re diving deep into everything you need to know about what AI forms are, how they’re used, and how we can arrive at solutions that meet our specific requirements. Specifically, we’ll be covering: - [What are AI forms?](/content/blog/ai-forms/#what-are-ai-forms/index.html) - [AI-generated forms](/content/blog/ai-forms/#ai-generated-forms/index.html) - [Triggering LLM operations on form submissions](/content/blog/ai-forms/#triggering-llm-operations-on-form-submissions/index.html) - [Forms within AI-powered workflows](/content/blog/ai-forms/#forms-within-ai-powered-workflows/index.html) - [What’s behind the growth of AI forms](/content/blog/ai-forms/#what-is-behind-the-growth-of-ai-forms/index.html) - [How are AI forms being used?](/content/blog/ai-forms/#how-are-ai-forms-being-used/index.html) - [Key use cases](/content/blog/ai-forms/#key-use-cases/index.html) - [User personas](/content/blog/ai-forms/#user-personas/index.html) - [Tooling, solutions, and systems design for AI forms](/content/blog/ai-forms/#tooling-solutions-and-systems-design-for-ai-forms/index.html) Let’s start with the basics. ## What are AI forms? As we said at the outset, AI forms can refer to a few distinct things in different contexts. Broadly, though, what these have in common is that they involve utilizing LLM capabilities, either within the tooling we use to output forms or in the actual form solutions themselves. For example, using AI to provide feedback on users' form inputs in real time. To make things easier throughout the course of this guide, we’re going to be more careful with our terminology. So, we can distinguish between `AI-generated forms`, as in tools that have been created using AI, and `AI forms`, in the true sense of being forms that themselves utilize AI. ### AI-generated forms As we just alluded to, AI-generated forms are form UIs that have been created, at least in part, using AI. Nowadays, most of the prominent form builder platforms offer form generation from natural language inputs. Others will allow us to generate form UIs from documents using optical character recognition (OCR). For example, we could submit a prompt to create a `Contact Us` form, and the tool would output a working form, with an appropriate data schema, which we can further customize to our needs. However, it’s not necessarily the appropriate option for using AI to output forms in all cases, especially as these types of form generators are typically highly opinionated. So, if we have more advanced needs from a UI-perspective, for instance creating [dynamic forms](/content/blog/app-building/dynamic-forms/index.html), we might utilize AI to create our data model, but use more traditional methods to build the form itself. Alternatively, we might wish to use a specific existing data source and leverage AI to generate forms on top of this. The key goal of AI-generated forms generally is to expedite the process of creating custom code by reducing the amount that we need to build from scratch. ### Triggering LLM operations on form submissions An equally important type of AI form involves using form submissions to initiate some kind of AI processing downstream. In other words, we collect form data as normal and then use this information to populate a predefined request for an LLM. Depending on the complexity of what we’re building, this could mean: - Populating specific variables within a pre-written prompt. - Providing inputs for a deterministic automation rule that leverages an LLM for specific functions, such as translation or categorization. - Sending instructions to non-deterministic or agentic AI workflows. In each of these cases, the high-level goal is the same. We’re generally using AI to perform some of the follow-on actions from a form submission that we’d otherwise rely on human action or traditional workflow automation tools for. ### Forms within AI-powered workflows Lastly, an important emerging use case is empowering autonomous AI systems to generate appropriate forms when they need structured inputs, as part of a human-in-the-loop workflow. Essentially, this is a type of [tool calling](/content/blog/ai-agents/tool-calling/index.html), where we empower AI agents with the ability to generate forms as a callable function. In either case, the bigger challenge is for the AI system to determine that it needs human input and to define the required schema for this. ## What is behind the growth of AI forms? Now that we have a strong grasp of what AI forms are and some of the specific configurations of these that we might want to opt for, it’s worth thinking in more detail about some of the practical reasons that their popularity has exploded in recent years. ### Benefits The main benefit of AI-generated forms is enabling us to output custom forms more quickly and easily. This saves time and money on outputting forms. For forms that interact with AI systems and LLM-powered automations, the benefits are largely tied to efficiency and cost-effectiveness. This includes reducing costs by lowering the need for human actions within workflows, as well as expanding the scope of tasks that can be automated, compared to strictly deterministic workflow automations. ### Challenges One issue with AI form builders is that, unless we have quite generic needs, we’re unlikely to get the exact form we want on the first pass, especially with regard to its schema. The biggest difficulty with other types of AI forms comes down to tooling and architecture. AI workflow management is a rapidly evolving field, meaning that there are a huge number of platforms and frameworks that we might rely on for LLM-powered automations. ## How are AI forms being used? ### Key use cases AI-generated forms are especially beneficial in situations where we need to create large numbers of forms quickly without extensive development resources. ### User personas AI form generators are largely aimed at less technical colleagues, making it a great fit for teams in non-IT departments, such as HR, sales, marketing, and customer success. ## Tooling, solutions, and systems design for AI forms ### AI form builders AI form generators are ready-to-use solutions for outputting working forms from natural language inputs. ### Other AI-coding solutions Utilizing AI to generate individual elements of our form rather than a complete solution is another approach many organizations take. ### AI-powered processing on form submissions This type of AI form works by enabling users to submit values, which are then populated as dynamic variables in a pre-constructed LLM prompt. ### Dynamic form generation within agentic workflows Enables autonomous AI systems to create a form independently when they determine that this is needed to progress a workflow.