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Top 10 Generative AI Applications in Process Automation

Discover the top 10 generative AI applications for process automation. Streamline your workflow and increase efficiency with cutting-edge technology.

10 Generative AI Applications in Process Automation

Given the media attention attracted by recent developments in artificial intelligence (AI) software, business owners are clamoring to understand how to use AI to improve their business processes. Start by recognizing that AI is not one thing but many things. There are several types of AI, and today, we will focus on how generative AI applications can benefit your business through process automation.

Generative AI 101

Let’s start by understanding generative AI technologies, how they work, and some common use cases.

How Does Generative AI Work?

Generative AI models use machine learning to detect patterns in a dataset and then produce new content that appears similar to that dataset. Depending on the generative model you have, the tool can intake text, images, music, voice, and code. The model can also generate new, creative content based on these different inputs.

Common Generative AI Use Cases

With a wide variety of outputs, generative AI has a massive range of use cases. It can automate processes for creating marketing content, improving customer experience through personalized interactions, and even fashioning entirely new products or services.

Applications of Generative AI in Process Automation

Here is a deeper dive into 10 applications of generative AI for process automation.

1. Create Realistic Product Prototypes

Generative AI can play a role in every stage of product development. These solutions can give you a faster way to build both digital and physical prototypes. You can automate the design process, no matter the product type, by following a few steps.

First, train the AI on past product designs or existing products you want to emulate. You can specify which features you want to keep and which you wish to change. Second, the AI can generate product designs based on your specifications. Third, if you're designing a digital product such as a website, you can simply test it on your computer. When you're making a physical product, you can use a 3D printer to check if your product works.

The AI itself can be used to test the product before you commit to building it. The model can create real-world scenarios and generate test cases to ensure the product has no design flaws. In the automotive industry, it's common to use AI to locate any product crashes before investing substantially in vehicle production.

Generative AI can also suggest upgrades in future iterations based on user feedback. This can be particularly useful if you're developing software that you'd like to improve based on how customers interact with your product.

2. Generate Personalized Content for Customers

Making a personal connection with your customers improves how they perceive your business and builds trust. This is why people still like to visit local shops where they feel valued and know the person behind the counter. Generative AI now makes it possible to make this connection with people online and at scale. 

Generative AI models can combine with machine learning to perceive customers' actions and preferences. You can segment your audience to a granular level and target them with hyper-focused messages. One example is product recommendations for an e-commerce store. The website seems to know what the customer viewed, placed in their cart, and previously purchased.

Generative AI can take this even further by sending personalized emails to customers about specific products in which they may be interested and creating a unique product description for each visitor.

3. Design Compelling Marketing Materials

Generative AI excels in producing compelling marketing content of all kinds. What would have required vast amounts of human intelligence and creativity can be achieved in just minutes. Regardless of the media you produce, generative AI can streamline the content generation process and allow you to reach your customers at scale.

If you're making marketing videos for social media, you no longer have to hire a professional voice actor to narrate your videos. AI voice-overs produce a human-sounding narration in more than 100 languages. You can reach billions of people around the world in their native language. You can use natural language processing tools to produce the script and then simply enter this into your text-to-speech program. Using this method, you can create hundreds of voice-overs in no time.

Generative AI can also produce images to accompany your marketing campaigns. All you need to do is enter a text prompt describing how you want your image to appear. You can specify your image's content, style, and aspect ratio, making it suitable for any platform. You can keep refining the prompt that you give the AI if you don’t get precisely the result you want the first time, which lets you double-check the image fits your marketing needs.

4. Enhance Data Analysis and Decision-Making Processes

Intelligent automation through generative AI in data analysis benefits businesses in several ways. One way is by helping to clean and prepare data for analysis. The time-consuming task of finding missing data and organizing the whole dataset into a user-friendly structure can be fully automated through AI machine learning. 

Once the data is ready to analyze, autoencoders can spot outliers. These deep learning models are trained on normal behavior, allowing them to spot anomalies in a dataset quickly. This capability has applications in cybersecurity, fraud detection, and manufacturing quality control. 

In addition to spotting anomalies, generative AI can spot patterns and trends. This can be particularly useful in analyzing customer behavior and forecasting sales.

The analysis of any dataset is only as accurate as the data you input. If your dataset is small, this can lead to inaccurate analyses. Generative AI can help expand a dataset by using generative adversarial networks to augment synthetic data. This additional data can then be combined with the original data to provide a more complete dataset, leading to more accurate results.

5. Develop New and Innovative Products or Services

Just as generative AI solutions can assist in making product prototypes, they can also help you to develop new, innovative products and services.

The pharmaceutical industry can apply AI to find potential new drug candidates much faster. Not only can it analyze enormous datasets much more efficiently, but it can also create simulations to test the efficacy of a new treatment. This helps to rule out ineffective options before going to live testing, saving time and money in research and development.

Generative AI tools can be an ideation partner for more creative fields, too. You can type in a list of parameters your new product needs to abide by, and the AI will suggest solutions that fit the criteria. This can be used successfully in video game development when creating new characters, levels, and storylines. 

It is also beneficial when creating educational content because it can not only suggest topics but also give you structure and fact-check the information you provide to students.

When creating new services, generative AI can identify gaps in the market. These models can then test the viability of the new service by conducting further market research. All this can be tailored against the competencies of your company, weaving a personalized solution into your existing offerings.

6. Automate Repetitive Tasks

AI technology is frequently used to automate repetitive tasks across all business areas. Why? Automating routine tasks saves time and money and reduces your error rate. 

Take, for example, data entry and processing, a commonly automated task in several industries. Financial institutions that handle millions of transactions daily would be unable to keep up if all those needed to be manually processed. AI allows these transactions to be processed almost instantaneously.

Generative AI can also streamline processes in inventory and supply management. Retail companies can call on AI to reorder new stock automatically when needed. Beyond this relatively simple task, the AI can also predict the amount of new stock to order based on purchasing volume trends.

These solutions can also benefit the manufacturing industry in counting product defects and predicting future amounts. You can also use AI for predictive maintenance on machines, ensuring that your factory runs at its desired output as regularly as possible.

7. Generate Reports and Documents

Natural language generation tools can read and summarize large documents into more easily consumed reports. You can tell the AI model to scan for specific data or phrases to check you don’t miss anything important without reading the whole document yourself.

These tools can also generate and update documents such as privacy policies and end-user agreements. Most of the document’s content is boilerplate, but it needs to be specific to your company. You can produce a legal document that covers all your bases by entering particular details related to your company.

AI does exceptionally well at summarizing large amounts of data that would take a human a long time to process. This can be used for finance, marketing, and sales to condense raw data into quickly consumable graphs, charts, and overviews. Intelligent document processing like this means you can update documents in real time, so you always have up-to-date information to make your decisions.

8. Automate Code Generation

Natural language generators don’t just understand spoken languages; they are also highly efficient at taking in and producing code. This allows developers to excel at code generation, optimization, and bug fixing.

When writing code, AI technology can offer suggestions to complete a line of code. This is similar to the auto-suggestions you may get in Google searches or when writing an email.

Language models can optimize code to make it cleaner, more readable, and bug-free. The code can also be optimized to ensure it follows specific style guidelines, maintaining consistency within a team of developers. 

Beyond improvements to existing code and productivity assistance, language models can create entire modules from scratch. You can produce a file with multiple lines of code in different programming languages that all work together by plugging in a written prompt detailing your requirements. This can dramatically improve efficiency, particularly for boilerplate chunks of code that are simple but time-consuming.

9. Create Personalized Customer Interactions

Generative AI tools can improve customer experience beyond sending relevant marketing content. AI can have a pivotal role in personalized customer service. 

Chatbots that use generative AI can deliver a personalized experience for customers as they tap into the person’s history with the company. The bots can determine if they are a new customer, someone who browsed and hasn't made a purchase yet, or a returning customer.

This information can be used to predict issues a customer may have, and you can tailor your conversations to address those pain points. Chatbots that pair with AI can also remember previous conversations and handle multiple requests. The customer may feel relieved to no longer have to explain their issue multiple times as customer service representatives transfer between different departments. 

Not only can the chatbots produce human-like speech, but they can also offer a better level of service by instantly zeroing in on a customer's issue, without placing them on hold while they look into their account. This efficiency and personalization increase the quality of customer interactions, positively reflecting back on your company.

10. Enhance Decision Support Systems

Business owners make decisions in different ways. Some people are analytical, and others prefer to go with their gut. Some make top-down decisions, and others prefer to consult with others before finalizing a decision. 

If you're an analytical decision-maker who likes to consult, you may naturally get massive benefits from the insights delivered by AI. You may treat your AI tool as another consultant because it doesn’t just summarize the data for you — it gives you recommendations. Due to AI's efficiency at analyzing data, you may become even more analytical as you analyze data more deeply through streamlined processes.

More intuitive decision-makers also make use of generative AI because it reduces the downsides of traditional analytics and consultation. You can get easy-to-understand visual reports, reducing the barriers of mounds of information and a limited amount of time. You may like that you can't offend an AI if you choose not to follow its advice; you simply take what you want.

Streamline and Automate Your Business Processes Today

If you have made a note of how one or more generative AI applications can improve your business processes, contact us today to find out how we can help you automate your operations. BP3 Global has already created automated processes to streamline operations for hundreds of major companies and proudly has a 99% success rate.


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