AI Automation
With the advancements in generative AI and the field of AI-based systems, businesses are discovering new approaches to creating more effective procedures and applying revolutionary changes that will last for years to come.


Many people are concerned about how generative AI may affect business consumers, staff, and regulatory compliance. We’ll examine how to securely and successfully integrate AI technology into your automation and how to use language models and other generative AI automation to revolutionise your company.
What is AI Automation?
Automation, often known as robotic process automation (RPA), started with robots carrying out routine operations. Thanks to the development of artificial intelligence (AI), automation can now link systems, orchestrate work, and handle end-to-end operations. We refer to this relationship between RPA, AI, and business process management (BPM) as intelligent automation (IA).
- RPA performs repetitive tasks.
- AI mimics human thinking.
- BPM automates workflows.
- IA combines RPA, AI, and BPM.
- Enterprise AI integrates AI more tightly with automation and orchestration. Think of it like AI plus IA.
Enterprise AI, further developing IA, will incorporate novel AI ideas such as agentic AI and agentic process automation. This notion of automating AI is referred to as “AI automation.”
Is AI the Same as Automation?
No, automation and AI are not the same. Writing a business proposal is one of the activities that AI itself can perform. However, combined automation and AI can accomplish far more than alone. Cognitive automation is the result of that collaboration.
Automation reduces the amount of physical labour required for everyday operations by deploying robots to carry out a set of rule-based instructions that humans have specified. The robots can only finish the work if the activity is within the developer’s programming.
When AI is integrated with RPA and other automation technologies in an Enterprise AI solution, robots can use the general frameworks that humans have established to decide how to proceed. Thanks to its machine learning skills, AI can learn from its activities and gradually enhance its performance.
In a nutshell, this combination produces intelligent automation in the following ways:
- AI uses ML, neural networks and complex algorithms to analyse structured and unstructured data. It’s the cognitive decision-making side of IA/Enterprise AI.
- BPM automates workflows and connects people and systems.
- RPA completes simple administrative tasks such as filling out forms and extracting data.
AI as a technology can also include:
- Machine learning (ML)
- Natural language processing (NLP)
- Computer vision
- Deep learning techniques

What is an Example of Automation and AI Working Together?
AI automation technologies, often known as enterprise AI or intelligent automation, enable businesses to enhance their human workforce with these IA digital workers to optimise business procedures. These digital workers may also be known as “enterprise agents” under Enterprise AI or as AI workers.
In addition to alleviating labour and skill shortages, this frees workers from tedious, repetitive work so they may concentrate on more important strategic projects.
Chatbots with AI capabilities or virtual assistants are excellent examples of this. Customer support departments frequently get thousands of emails daily, which is too much for a few employees to handle effectively and quickly during an eight-hour workday.
However, AI chatbots operate around the clock to minimise client wait times by rapidly answering customer enquiries.
If the chatbot is unable to respond to a customer’s query, a human agent takes over the discussion. As a result of the reduction in wait times and backlogs, employees may concentrate on more complicated situations.

How Can You Automate More with AI?
You may increase your company skills by combining automation with AI (or gen AI):
Generative AI understands and produces text and picture material to supplement labour using simulated human intelligence. Gen AI can respond to consumer questions and support decision-making using natural language processing. We are extending our intelligent automation with generative AI to help organisations automate increasingly complicated processes.
Process discovery may find bottlenecks and areas for improvement by using AI to track behaviour in real-time and derive insights from that behaviour. Following the discovery phase, it creates a process map to assist your teams in creating more automation.
Machine learning (ML) is used for data processing and analysis in intelligent document processing (IDP). Purchase orders, application forms, and invoices are examples of semi-structured and structured documents from which IDP may extract and validate data.
By putting gen AI into practice, IDP can go beyond process validation to comprehend a document’s context and purpose and choose how to use that data, which can speed up your time to market.
Also, read about AI for accountants.
How Do I Use AI and Automation?
AI automation is incredibly flexible. It can assist organisations in increasing their decision-making processes, decreasing mistakes, and increasing efficiency. Let’s examine a few use scenarios from the industry:
What are Examples of AI Automation?

Customer Service
Suppose a customer has a problem and wants it fixed immediately. AI-powered solutions can expedite the resolution of client complaints or forward more complex instances to a service representative, giving your customers a smoother experience.

Financial Services and Banking
IA can automate administrative procedures, including anti-money laundering (AML) reporting and know-your-customer (KYC) ID verification, and digitise the lending process. Real-time transaction data analysis by AI algorithms can identify odd trends and perhaps fraudulent activity.

Insurance
Underwriting, claims processing, regulatory compliance, and fraud detection are just a few of the standard insurance processes that IA can expedite. To expedite the claims decision process, digital workers can automatically gather data from many or disjointed sources and notify agents of pertinent information.

Manufacturing
AI for business analytics can help manufacturers increase productivity and product quality while lowering unscheduled downtime. AI can analyse supply chain data to optimise distribution routes and inventory levels. Additionally, IA aids in predictive maintenance by locating slowdowns that result in yield losses.

Healthcare
Clinical personnel may arrange patient medical records and histories using automation, and patients can schedule appointments. By evaluating medical pictures such as MRIs and X-rays, AI can help with medical diagnosis, enabling physicians to spot problems and provide patients with the appropriate care more quickly.
What Are the Benefits of AI Automation?
More companies are using AI-powered automation because of its financial advantages. AI’s enormous processing capacity boosts automation’s speed, effectiveness, and scalability, improving its return on investment (ROI).
Team Productivity
Like an AI agent, an AI automated assistant enhances your team's work by implementing AI use cases across systems, from summarising content to offering insightful information for decision-making. AI systems are capable of processing enormous volumes of data quickly and continuously.
Customer Experience
Automated systems produce higher-quality, more dependable, and consistent outputs - whether products, customer service, or a variety of services.
Integration and Scalability
If you use quality data, your homegrown AI can expand your operations quickly while preserving security and compliance. It may provide individualised and condensed material for simpler access to pertinent information and use natural language to request automation across systems. An AI workforce may be readily scaled to assist your human workforce with capacity and resources.
Cost Reduction
Automated solutions help increase accuracy and consistency while optimising resource allocation. This can boost output and save expenses related to duplication of effort and rework.
Digital Transformation
Generative AI transforms the nature of work and allows individuals to view your company's automation journey in a new way. Gen AI makes it possible for non-tech developers to swiftly design automation that adheres to best practice rules and laws by using natural language prompts.
How Does AI Automation Software Work?
Artificial intelligence software comes in various forms. Before choosing an automation technology, consider your business objectives and the processes you wish to automate. Let’s examine a few key features of AI automation software.

Foundation Model
Pre-trained models, known as foundational models, form the basis for various NLP and other AI applications. These models are usually trained on enormous volumes of text and data to learn to comprehend and produce language similar to humans and optimise for specific applications.

Cloud Services
While preserving a high degree of security and governance, cloud automation enables businesses to operate without delays or needing specialised knowledge. Cloud computing seeks to reduce the total cost of ownership so that businesses can completely implement, maintain, and update their automation program on the cloud. Hybrid cloud deployment solutions are also available from several cloud providers.
Automate Responsibly
Innovations in technology are expanding thanks to AI-powered solutions, particularly generative AI. Your company must guarantee compliance and data security before deploying applications using AI guidelines since legislation around these technologies has changed. The following are some things to think about:

Quality Model
Integrate with corporate language learning models (LLMs) of the highest calibre that can safeguard your data.
Human-in-the-Loop
Integrate human supervision into AI-driven processes to guarantee that the results are precise and consistent with your company's plans.
Continuously Monitor
To avoid unwanted access and guarantee compliance, set up audit trails for your automation and monitor user behaviour.
Set Parameters
To protect your and your customers' data, provide access to the appropriate individuals.
AI Governance
Monitor your AI operations, such as the documentation of your AI models and auditing pipelines, to demonstrate how your AI is developed and tested, how it performs over time, and any possible hazards. AI governance is crucial in highly regulated sectors because it helps prevent fines and guarantees transparency.
Key Takeaways
We now know that intelligent automation, or AI automation, streamlines corporate processes by combining AI’s cognitive “thinking” powers with RPA’s ” task-performing ” skills. Additionally, the automation options have expanded significantly with the introduction of Gen AI in AI organisations.
The following are your main conclusions about using AI to automate more:

Ensure your AI training models have sound data security, quality, and AI governance.

Consider how you can maximise your company's advantages of IA and enterprise AI.

Before deployment, create a plan for your automation.
Also, check out the 6 ways AI is changing business.
Free Automation Review
Identify where automation can save you time and money within your organisation with a free automation review.


