Can you tell the difference between automation and AI?
Automation and Artificial Intelligence (AI) are terms often used interchangeably in the media. Although they are similar in their abilities to streamline workflows, better efficiency and lower costs, understanding what makes them different is crucial in learning how to use them effectively.
It’s common to confuse the two, as they both have the same goals in mind, to reduce human labour and improve productivity, so read on to learn what both terms actually mean, followed by examples of each and how they can benefit you.
Automation
Automation is the application of technology to perform tasks with minimal to no human intervention. This approach is used to streamline processes, boost efficiency and reduce human error.
Engineers and developers write code that dictates how a machine or system should operate under different circumstances. These instructions then determine when and how tasks should be performed. This ensures the automation process operates smoothly and accurately.
Automation is applied across a wide range of industries, from logistics and manufacturing to finance and healthcare. In these fields, it not only improves productivity, but also safety, reliability and quality. As technology continues to grow, automation plays a key part in shaping the future of work and driving digital transformation across the global economy.
Here are a few examples of automation, and where they are of most benefit:
Fixed Automation
Fixed automation, also known as “hard automation”, refers to a type of automation in which the configuration of the manufacturing process stays permanently in a fixed location, designed to perform a specific task repeatedly. High-volume production environments benefit from fixed automation, where large numbers of identical products need to be produced.
How might I use it?
Think about the automatic email you have scheduled to send out of office, or your spam filter. These are both examples of fixed automation.
Programmable Automation
Programmable automation systems are a flexible manufacturing approach that uses reprogrammable equipment to produce a variety of products. Unlike fixed automation, this type of system is distinguished by its ability to adjust production parameters through software modifications. Low to medium demand production environments with occasional product changes benefit from programmable automation.
How might I use it?
Programmable automation is often used on a larger, more industrial scale. For example, computer numerical control (CNC) machines, that are programmed to perform specific machining tasks, such as drilling, cutting and milling materials like metal and wood.
An everyday example of programmable automation would be 3D printing, as a 3D printer can be reprogrammed to produce different items based on design files provided.
Flexible Automation
Flexible automation, also known as soft automation, is the use of adaptable and easily configurable automation that combines efficiency and adaptability to produce a variety of products and or variations of products. It is fitting for modern manufacturing, where product lifecycles are shorter and demands for customisation are higher. Unlike programmable automation, which can be programmed for different products but requires large amounts of downtime, flexible automation can be adapted rapidly and automatically.
How might I use it?
Certain platforms can automate meeting invitations, manage schedules and facilitate conversations between employees. Other platforms can enable employees to automate task assignment and track progress flexibly.
Business Process Automation (BPA)
Business Process Automation focuses on automating entire business processes, using software and technology to automate repetitive tasks and workflows, involving multiple organisational tasks and departments. This aims to increase efficiency, productivity, and optimise workflows, reducing manual efforts.
How might I use it?
Employee onboarding, customer service chatbots, payroll management, invoicing and IT helpdesk ticketing are all examples of BPA, as they are automations that streamline repetitive, rule-based tasks.
Integrated Automation
Integrated automation connects various software, hardware, and systems to seamlessly work together through computer control. It aims to reduce the complexity of multiple independent automated work processes by streamlining communication between various automated processes, synchronising all components to work efficiently with minimal human intervention.
How might I use it?
Platforms such as Microsoft Teams integrate chat, video conferencing and file sharing with automated notifications and scheduling to improve team communication and collaboration.
Artificial Intelligence
AI is technology that allows computers and machines to analyse data, learn patterns and create predictions or suggestions based on the information learned.
AI mimics human-like intelligence, processing large amounts of data, learning from experiences and adjusting to new information. These possibilities allow machines to perform tasks that once required human intelligence, but with much greater speed and precision. Unlike automation, AI can self-improve over time with no human intervention necessary.
In software applications, AI can imitate human cognitive intelligence, such as with speech recognition, decision-making, language translation, and visual perception. Humans can oversee the functionality of AI and steer it in their ideal direction, encouraging helpful and discouraging unhelpful behaviour, which the machine learns from.
There are numerous branches of AI, listed below:
Machine Learning (ML)
Machine learning is a subset of AI that includes learning from experience to perform tasks without explicit programming. These machines can create computer systems that learn from themselves by analysing data and identifying patterns, rather than by being explicitly told what to do each time.
We use machine learning every day without even realising. For example, your personalised product recommendations aren’t so specific for no reason. E-commerce platforms use machine learning to analyse user behaviour and show you products you’re likely to click on.
Natural Language Processing (NLP)
This is a branch of AI that allows computers to understand, interpret and generate human language. It combines computer science with linguistics to help machines make sense of both spoken and written text.
Think about when you use voice assistants like Siri or Alexa, automatic speech recognition converts spoken words to text and uses NLP to analyse the text. From there, it can figure out what to say in response!
Deep Learning
This is a subset of machine learning that uses neural networks to analyse large amounts of data. Deep learning algorithms can learn to recognise patterns in text, images, and video, and can be used for applications such as image classification and self-driving cars.
For example, you may use deep learning for tasks as simple as unlocking your phone. Facial recognition involves deep learning to recognise someone’s face even when changes have been made, such as a new haircut, glasses, or bad lighting obstructions.
Computer Vision
This is a field of AI that focuses on acquiring, processing, analysing and understanding digital images to make recommendations or criticise when they spot flaws or issues. These are commonly used in sectors such as healthcare, where X-rays, MRI scans, and other scans are analysed to detect health problems. In your everyday life, you may use computer vision with facial recognition or self-checkouts.
Object tracking happens within computer vision and is used in our everyday lives. For example, Many camera doorbells use object tracking (also known as 3D motion detection) to notify homeowners of any movement made.
Understanding the difference
There are many overlaps between AI and automation, but both technologies have greatly different capabilities that could significantly benefit your business. Want to know if you’d benefit from AI or automation? Get in touch with us today!
