Robotronix | Automation

What is automation?

Automation is the application of technology, programs, robotics or processes to achieve outcomes with minimal human input.

Automation is a broad term that can cover many areas of technology where human input is minimized. This can include everything from business-specific types such as:

  • Basic automation
    • Business process management
    • Robotic process automation
  • Process automation
    • Invoice processing
    • Workflow automation
  • Artificial Intelligence (AI) automation

“Overview of IT automation”

IT automation is using a system of instructions to execute a repeated set of processes – taking the place of IT work performed manually. Automated processes can increase IT productivity and efficiency – and reduce human errors. Recently the focus on IT automation has shifted to enhanced business productivity, greater innovation and faster speed to market.

Robotronix’s Topcoder is known for its crowdsourcing capabilities and extensive community network. Recognized for the wide range of services it offers across several areas of technology, Topcoder focuses primarily on agile development, digital design and algorithms/analytics. Wipro's deep digital focus and design led approach aims to effectively deliver innovation at scale, accelerate digital transformation, and build better student experiences.

Automation trends – recent and future

Recent automation trends

The modern era of workflow automation began in about 2005 with the introduction of business process management (BPM) methodology and tools. In 2011, the release of Apple’s Siri sparked a new chapter of automation and AI-driven assistants. The trend was to move away from physical robots to computerized automation using AI software conceived in the late 80s and early 90s.

Future automation trends

Advancements likely will occur in:

Machine learning and workflow

Artificial intelligence (AI) is taking its strategic place in both operational and strategic business process management. New software enhancements to robotic process automation (RPA) will allow the technology to better observe and learn from human patterns – optimizing front- and back-office experiences. Machine learning is poised to revolutionize workflow, helping to enable companies to trigger new processes, reroute running processes and make action recommendations based on predictions.


Gartner Research has coined the term “hyperautomation” to describe the merging of machine learning, packaged software and automation tools to rapidly maximize the number of automation processes in a business – to greatly increase productivity. Hyperautomation requires a range of cognitive and automation technologies coming together to deliver both the intelligence and the power to put the intelligence into action.

Intelligent capabilities

AI-based systems will be able to remember (automating future robot configurations) and reason (predictive and probabilistic processing) so that automated systems gain the ability to learn and interact.

Intelligent industrial robots

Robots will perform multiple tasks and make decisions and work autonomously – including self-diagnostic and predictive maintenance capabilities.

AI and machine learning in automation

Recent automation trends

There are distinctions between terms:


Streamlines repetitive, instructive tasks to speed workflows. Automation encompasses everything from mundane activities, like keeping an icemaker filled, to important business functions, such as keeping a set schedule for server backups. Basic automation is programmed to perform a repetitive, usually mundane, task so humans don’t have to.

Artificial Intelligence (AI)

AI is programmed with logic and rules so that it can mimic human decision making. However, the only way AI can “learn” is if its programmers provide additional input. AI can be used in cybersecurity to detect threats such as subtle changes in user behavior or increased data transfers. AI can also be programmed to assist users on websites with chatbots that free up customer service reps from mundane questions that AI can easily answer.

Machine learning

An advanced form of AI. It can use data and experiences to “learn” over time without needing additional programming. Machine learning can recognize patterns on its own and make predictions. It uses large data sets to learn facial recognition, speech recognition and translations – and become more proficient with repeated exposure. Because machine learning software learns something new with every dataset, it can provide insights that are more sophisticated and informed.