Today we are entering into the 4th Industrial Revolution, where machines are talking to each other and the human. We can’t simply discuss one technology in isolation as most of the technologies are driven by other technology be it Machine Learning, Artificial Intelligence, AR/VR, Robotics, and RPA, Sensors or iIOT, or many other technologies. And the fact is that Data plays a vital role here. That is why I must say the technologies are supported by Big Data and related platforms.
Data is the New oil is an old term, today data is much more valuable than fossil oil.
It is not easy to discuss all the aspects of Industry 4.0 related technologies, but today we will discuss mainly AI and RPA and the transformation during the pandemic which is for sure accelerated.
The major difference between AI and RPA is that AI is viewed as a form of technology to replace human labor and automate end-to-end (unattended automation). RPA uses structured inputs and logic, while AI uses unstructured inputs and develops its own logic.
RPA is used to work in conjunction with people by automating repetitive processes (attended automation),
Before we go deep into AI and RPA, let me first begin by clarifying some basic concepts.
Artificial Intelligence
The Oxford Dictionary defines Artificial Intelligence (AI) as the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.
Artificial intelligence (AI) relates to computer engineering and the purpose is to create machines or systems that behave like humans.
AI Applications
And talking about AI and its applications. Some of them can be ;
- Decision-making in real-life situations with reasoning, explanation, and advice. We had decision support systems, but not the decision making systems so AI can help to make decision, that might include like approving or rejecting a loan request and so on. Where the AI can provide the reasoning for approving or rejecting and can also advise.
- Communication with Customer has been seen by banks, customer support services and so on. In the form of chatbots which can communicate and respond in natural language similar to human.
- Future Predictions using the nueral system. This works by similating the Intelligence.
- Robotics where AI responds based on sensors (motion, speed, light, heat, impact, sound, and so on.)
Business and Artificial Intelligence
Usually, AI design is inspired by the structure of Huaman Brain. As people make decisions based on conclusions rather than definitive rules. Similarly, AI makes informed decisions by informed choices and by identifying the pattern of the data.
The type of data that we are talking about here is referred to as machine learning and deep learning.
AI can be adopted by a variety of industries, including retail and manufacturing. And the good news is that businesses don’t need to develop AI, they just need to adopt the technologies that will be integrated with AI, as Google, Microsoft, and many tech companies are integrating AI as an intelligence layer across their entire tech stack.
Businesses can employ AI for everything from mining social data to driving engagement in customer relationship management (CRM) to optimizing logistics and efficiency when it comes to tracking and managing assets.
ML is playing a key role in the development of AI, noted Luke Tang, General Manager of TechCode’s Global AI+ Accelerator program, which incubates AI startups and helps companies incorporate AI on top of their existing products and services.
Integrating AI into any organization is serious work.
It takes in-depth knowledge, swathes of time, and a dedication to accuracy. Moreover, to implement it successfully, don’t just follow the trends: instead, focus on how AI can add value to your particular business and determine where it’s needed the most.
Then, with the support and experience of a domain specialist, you can put your ideas to work and create long-term value using the demanding field that is artificial intelligence.
Robotics Process Automation (RPA)
Every automation project has to start somewhere. We have been using business Applications like ERP to Automate the business process but RPA is much more than that. RPA is a form of business process automation that allows anyone to define a set of instructions for a robot or ‘bot’ to perform.
RPA bots are capable of mimicking most human-computer interactions to carry out a ton of error-free tasks, at high volume and speed.
Robotic process automation (RPA) streamlines workflows, which makes organizations more profitable, flexible, and responsive. It also increases employee satisfaction, engagement, and productivity by removing mundane tasks from their workdays.
Today we can see that RPA can check the emails, download the attachment, feed the data from the attachment to ERP. Run various tasks on a computer that human usually does. But RPA is not limited to this only there are many RPA applications and some are listed here.
RPA Applications
There are many use cases, where RPA can benefit SMBs and Large Enterprises.
- Sales Order Process – Enquiry to Quote and Order to Cash
- Purchase Order Process – RFQ to Purchase Order and Payment
- Data Automation (Extraction, Cleansing, Entry, Update, Validate)
- Prepare Reports and Email
- CRM – Updating Customers Information,
- Support Functions L1
- IT Automation (Software Installation, Backup and Validation, Support from Vendor.
- Finance (Bank Reconciliation, Budget Preparation, P&L Reports etc)
- Human resource (Candidate Sourcing, Background Check, Employer Verification etc)
- Validating Physical Inventory, Verifiying the records.
- Banking (Verif Physical Records, OCR, Signature, loan approval and so on)
- Retail : Promotion, Product segments, Marketing, invoicing, returns etc
RPA in Business
By implementing RPA companies can relieve human workers of repetitive tasks. RPA emulates human interaction with a computer interface, such as a CRM system, spreadsheet, or website, to automatically input data, collect and file information, and generally execute multi-step processes. By saying this, we can’t limit RPA to one aspect only.
For example, Finance robotics is evolving from simple individual task automation to full process automation that could improve the accuracy of financial analysis and forecasts. Automating finance processes requires combining finance robotics with other intelligent automation technologies.
The global RPA market was worth $271 million in 2016, and in 2020 that number hit $2.5 billion, an enormous increase by any metric.
The Transformation during the pandemic
There is no doubt that digitization has accelerated during the current pandemic, and will not be temporary but permanent. RPA is non-invasive and can be rapidly implemented to accelerate digital transformation. And it’s ideal for automating workflows that involve legacy systems that lack APIs, virtual desktop infrastructures (VDIs), or database access. Whereas during the pandemic, many businesses implemented AI, we have seen chatbots and voice bots have been communicating with us to take our requirements and respond to our queries.