The Hyperautomation Landscape in 2024

Transforming IT with AI, Low-Code, and Citizen Development

As businesses seek to become more agile, efficient, and competitive in the digital age, hyperautomation has emerged as a game-changing approach to transforming processes and operations. Hyperautomation takes the concept of automation to a new level by leveraging advanced technologies such as artificial intelligence (AI), machine learning (ML), robotic process automation (RPA), and now, generative AI (GenAI). The 2024 IT landscape is marked by a dramatic shift where not only IT specialists but also non-technical users are empowered to automate through low-code platforms and citizen development.

This article explores the current hyperautomation landscape, the role of AI and GenAI in its evolution, and the types of tools driving this transformation. We will also look at key market leaders shaping the future of hyperautomation.

The Evolution of Hyperautomation

Initially, automation focused on specific, repetitive tasks, largely handled by robotic process automation (RPA) tools that mimicked human actions in structured, rule-based environments. Over time, businesses realized that traditional RPA alone couldn’t address more complex, cognitive tasks that required decision-making, analysis, or the processing of unstructured data.

Enter AI and machine learning, which allowed automation tools to move beyond rigid rules to systems that learn and adapt based on data. By 2019, Gartner coined the term hyperautomation to describe a more comprehensive approach to automation that integrates AI, process mining, RPA, and intelligent business management systems (iBPMS). Hyperautomation emphasizes the automation of not just tasks but entire business processes, from discovery and monitoring to optimization and execution.

AI and GenAI’s Role in Hyperautomation

AI and generative AI (GenAI) are playing pivotal roles in reshaping hyperautomation:

- AI-driven process discovery and analytics help organizations identify automation opportunities by analyzing workflows, bottlenecks, and inefficiencies. These insights feed into more intelligent automation pipelines.

- Generative AI enhances hyperautomation by producing content, code, and decision logic that were once only possible through human input. For example, GenAI can create business documents, respond to customer inquiries, and even generate snippets of code for software development, which greatly speeds up automation efforts.

- AI for unstructured data allows hyperautomation tools to handle complex data types, such as text, images, and voice. NLP (Natural Language Processing) technologies help chatbots and virtual assistants automate customer support tasks, while AI-based image recognition systems can analyze data in healthcare or logistics.

AI’s ability to make sense of vast amounts of data in real time, coupled with GenAI’s capability to generate new content or solutions, enables hyperautomation systems to tackle a wide range of previously unreachable tasks.

Low-Code and Citizen Development: Democratizing Automation

One of the most significant shifts in today’s hyperautomation landscape is the rise of low-code platforms and citizen development. Traditionally, automating processes required deep technical expertise and coding skills, limiting automation initiatives to IT professionals. However, low-code and no-code platforms are changing that paradigm.

- Low-code platforms allow users to design automated workflows using drag-and-drop interfaces and pre-built components, minimizing the need for custom code. These platforms enable faster deployment of automation solutions and reduce the dependence on IT teams for every automation project.

- Citizen developers—business users without formal coding skills—are now able to build simple automations using these platforms. This democratization of automation allows organizations to scale automation efforts across departments, from HR and finance to marketing and customer service, freeing up IT resources for more complex projects.

Key low-code tools, such as Microsoft Power Automate, Appian, and OutSystems, enable business users to automate repetitive tasks, integrate different systems, and create custom applications with minimal technical expertise.

Types of Automation and Corresponding Tools

Different aspects of business automation can be categorized based on the complexity of the tasks and the type of data involved. Here’s a breakdown of the types of automation and the tools best suited for each:

1. Task Automation (RPA):  

   - Focus: Repetitive, structured tasks like data entry, processing invoices, and managing databases.  

   - Tools: UiPath, Automation Anywhere, Blue Prism are leaders in this space, offering RPA platforms that can handle rule-based tasks across different applications.

2. Process Automation (BPM/iBPMS):  

   - Focus: Automating end-to-end business processes, often integrating multiple systems and stakeholders.  

   - Tools: Appian, Pegasystems, IBM’s Business Automation Workflow are key players, providing intelligent business process management systems (iBPMS) that orchestrate workflows across departments.

3. Cognitive Automation (AI and ML):  

   - Focus: Automating tasks that require decision-making, interpretation of unstructured data, and predictions based on historical data.  

   - Tools: IBM Watson, Google AI, Microsoft Azure AI provide AI-powered capabilities that can analyze large datasets, perform natural language processing, and deliver predictive analytics.

4. Document and Content Automation (AI and GenAI):  

   - Focus: Handling unstructured data such as documents, emails, and contracts. GenAI tools can generate, categorize, and summarize content.  

   - Tools: OpenAI’s GPT models (used by ChatGPT, Microsoft Copilot), Google’s Bard, and IBM Watson Discovery are examples of GenAI technologies used to automate document-heavy tasks.

5. Citizen Automation (Low-Code/No-Code Platforms):  

   - Focus: Allowing non-technical users to automate workflows, integrate apps, and create solutions.  

   - Tools: Microsoft Power Automate, Zapier, Appian, and OutSystems enable business users to automate without writing code, thereby expanding the reach of automation across the organization.

In 2024, hyperautomation is no longer just about automating repetitive, mundane tasks. With the integration of AI, generative AI, and low-code platforms, it’s about enabling organizations to automate more sophisticated, end-to-end processes and empowering non-technical users to drive automation initiatives. The shift from task-based automation to process-driven, intelligent automation is transforming industries, making hyperautomation an essential part of every enterprise’s digital transformation strategy.

As hyperautomation evolves, businesses that leverage the right combination of RPA, AI, low-code, and GenAI technologies will stay ahead in the race to become more efficient, agile, and innovative.