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Automation with Generative AI in 2024: Benefits & 5 Use Cases

Different industries are starting to integrate generative AI solutions to their business processes. According to an IBM survey, 35% of respondents identified generative AI as one of the most prominent emerging technologies that will have the greatest impact on their businesses within the next three to five years.1

Generative AI is important to many industries as it indicates a big potential for automating various tasks. Unlike robotic process automation (RPA), as shown in Figure 1, the impact of and predictions for automation with generative AI are yet to be seen.

Figure 1. RPA market size worldwide from 2020 to 2030

Source: Statista

In this article, we will explain how automation with generative AI can benefit businesses and describe the top 5 automation use cases. Lastly, we will make some predictions regarding the future of automation through generative AI plus RPA.

How will generative AI change automation?

Natural language will emerge as a new automation language

Citizen developers can use low-code platforms like most RPA solutions to automate manual processes.

With generative AI, citizen developers can prompt to build automation solutions. For example, a description like the one below could be turned into an automation solution:

  1. Collect emails from supplier addresses found in Suppliers table in PostgreSQL.
  2. Send these emails to a service with PDF data extraction capabilities.
  3. Push extracted data to ERP

AIMultiple expects such prompt-to-automation functionality to be prevalent in most enterprise automation platforms in 2024.

More processes will be automated

Processes that were not feasible to automate previously will be possible to automate thanks to generative AI capabilities such as

  • Text understanding capabilities
  • Generating text, image or other data

Benefits of Generative AI Automation for Businesses

Generative AI will enable more automation thanks to the factors outlined above. Therefore, businesses will experience more automation benefits such as:

1- Improved efficiency & cost savings

Automation with generative design can reduce time-consuming and repetitive tasks of mundane human labor, allowing employees to focus on more creative and high-value activities.

Generative AI automation can optimize material usage and reduce costs due to the waste generated during manufacturing, making certain business processes cost effective. Automation technologies like RPA, virtual assistants and artificial intelligence can reduce operational costs as much as 30% by 2024, according to Gartner’s predictions.2

2- Scalability

Automation using generative AI can help businesses scale up their operations to meet growing demands that are hard to catch up with traditional methods, without incurring additional costs.

3- Reduced errors and rework

Automation with generative design can help eliminate human error, reducing the likelihood of errors and the need for rework.

4- Faster product iterations

Content creation process can become immensely faster when automated with generative AI. Generative AI is a valuable tool for creating content and design options in a short period, allowing content creators and designers to evaluate and refine products more quickly.

5 Generative AI Automation Use Cases

1- Content creation automation

Content creation or text generation can be automated with generative AI using natural language processing (NLP) algorithms and large language models like ChatGPT. These models are trained on large datasets of existing content examples to learn the patterns and styles of effective content.

Content creation with ChatGPT automation or generative AI automation, in general, can facilitate tasks such as:

  • Blog post generation
  • Product description generation
  • Video script generation

2- Image generation automation

Image generation can be automated with generative AI using deep learning algorithms and generative models, such as generative adversarial networks (GANs). These models are trained on large datasets of images to learn the underlying patterns and features of the visual input data, and can then generate new images based on that learning.

Automation of image generation can facilitate tasks such as:

  • Artistic style transfer
  • Product design
  • Logo design

3- Marketing automation

Automation is vital for marketing. 68% of B2B marketers implement automation in their marketing strategy.3 And artificial intelligence is playing an important role in marketing automation.

Marketing can be further automated with generative AI using a variety of techniques and applications to generate, personalize, and optimize marketing campaigns. Here are some ways in which generative AI can automate tasks for marketing:

  • Personalization of marketing messages and content to specific target audiences, based on the data analysis of their demographics, interests, and behaviors
  • Copywriting for generating ad copy, social media posts, email subject lines, and product descriptions
  • A/B testing of marketing campaigns, by generating different variations of content and testing them against each other to determine which performs best

4- Customer service automation

Customer service can be automated with generative AI as conversational AI models can understand and respond to customer queries and requests. Generative AI can automate certain tasks in customer service in certain ways such as:

  • Chatbots integrated with messaging apps, websites, and other customer service channels to provide 24/7 support
  • Email automation for enabling responses to common customer queries and requests received via email
  • Self-service portals to provide personalized recommendations and solutions to customers based on their query and history

5- Code-writing automation

Code writing can be automated with generative AI that can generate code based on natural language input. It can facilitate programmers and software developers in certain laborious tasks such as:

  • Code optimization
  • Bug detection
  • Code completion

Figure 2. An example of ChatGPT generating code for the given prompt and explaining it

What is the future of automation with generative AI and robotic process automation (RPA)?

As another class of automation technologies, RPA consists of bots and software to automate the way most businesses operate. According to Gartner, 90% of businesses already have implemented RPA.4

Increase in productivity

Generative AI and RPA are both powerful tools for automating repetitive tasks and increasing productivity. The integration of these two technologies could lead to even greater efficiency and accuracy in a wide range of applications, from customer service to manufacturing.

Collaboration between humans and machines

While automation with generative AI and RPA can help to increase efficiency and productivity, it is important to remember that humans still play a vital role in many industries and applications. In the future, we can expect to see increased collaboration between humans and machines, as automation is used to augment human capabilities and improve overall performance. Plus, studies show that people are willing to interact with humans in the future rather than machines.

Figure 3. Percentage of people favoring human interaction rather than machine interaction

Source: PwC

Potential risks of automation

However, as automation with generative AI and RPA becomes more widespread, there will be important ethical considerations to take into account, such as the potential for job displacement (see Figure 4) and the need to ensure that automation is used responsibly and ethically. 

Figure 4. Percentage of existing jobs at potential risk of automation, by gender and in total

Source: PwC

You can learn about other ethical risks from our article on the ethical considerations posed by generative AI.

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Cem Dilmegani
Principal Analyst
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Cem Dilmegani
Principal Analyst

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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