Let's start with the simple statement: no one could have predicted what we all lived through during 2020. This article's focus is to take a retrospective look at the events that drove 2020 forward and assess the impact these events have had on AI and ML related technologies.
2020 Was So "#2020."
Let's start with the single event that has accelerated automation: work from home. The legal requirement for businesses to close offices and require their employees to work from home has had more impact on the drive towards automation than any single event. For the first time, millions of people were forced to work out of their homes, we had to use technology to communicate, and for business to keep working, leverage technology in whatever way we can. In many ways, COVID-19 forced businesses into accepting that they are digitally run companies.
We have now had nine months to adapt to "work from home" as a daily standard. Digital technologies have been at the center of our adaption. We are now embracing RPA, AIOps, and many other automation services to accelerate our work. Microsoft, AWS, and other companies are accelerating their No-Code/Low-Code automation tools. Indeed, automation has brought about a new standard, and we may never go back to working in the office in the same we as we have in the past.
For many companies, RPA is the first step towards automation. The accelerated demand for digital in 2020 looked to RPA to reduce risk and burden on Work from Home employees. In many ways, RPA is becoming the backbone for cost-effective process changes, and the CIOs are taking it up. Many enterprises seek to use RPA, but they require process change and ask for low-code capabilities to assist them in making this kind of change.
From an employee's point of view, when you see the demand for new skills required at an early stage, you would also be looking at emerging skills like data analytics, AI, and other similar new skills. So, many different skill sets will also arise in the next few years to help enterprises replace legacy systems with RPA.
The cost-effectiveness of a complete, end to end automation of an enterprise's processes is hard to ignore. The Work from Home economy is forcing companies to look at making the best of the RPA technology, using it to complement the work done by their employees rather than replacing their jobs. They are moving up the value chain by putting a lot of value in the employees' information work.
As with RPA, AIOps was galvanized in 2020. The value of AIOps to the business is to allow the organization to make informed decisions and take immediate action. The goal of AIOps is to create a connected system of information and intelligence in which an organization can take action before an issue becomes a problem. Placing barriers such as work from home, increased demand on digital services, and continued reliance on Cloud providers has exposed the need for automated monitoring of your networks and infrastructures.
DevOps requires focus and a continuous, evolutionary process. At the core of DevOps is a focus on continuous integration and continuous delivery. It requires implementing an orchestration engine and a constant delivery orchestration engine to allow developers to build, test, and deploy the desired product to end-users.
The ability to manage and process all the data required for a successful AIOps deployment is a critical factor in enabling any organization to benefit from the value of an AI-powered customer experience platform. Data management platforms allow organizations to access the information they need from various data sources, analyze it, and make use of the insights they've obtained.
Again, 2020 was a catalyst to drive demand for AI. Of particular focus is the order for AI to replace in-person conversations. With the lockdown impacting customer and employee relationships for months, there had to be an alternative. To this end, AI for chatbots and automated services contributed towards reducing customer anxiety.
At least 80% of businesses have a competitive advantage in the AI-powered customer experience platforms. Examples of AI-powered customer experience platforms include chatbots, voice assistance, and digital assistants. Customers are increasingly expecting to interact with chatbots and digital assistants in a human-like, intuitive, and intelligent way.
AI-powered customer experience platforms help IT organizations take the guesswork out of dealing with support tickets. For instance, customers who experience problems with their devices or with voice recognition or online chat can get answers to their questions without involving a support representative.
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What Will Happen in 2021?
The year 2020 is a once in a century defining year. The impact of COVID-19 will be felt for years to come. The hope is that 2021 will not be as disruptive to our lives as 2020. With that said, I do not think we will be stepping back. The value automated services offer has exceeded most metrics. Expect companies to continue to double down on their investment in automation as we move into a calmer 2021.
To be prepared to take advantage of the trends toward automation in 2021, you should look into certification in AI, AIOps, and RPA. Simplilearn has various courses, such as Introduction to Robotic Process Automation (RPA), Artificial Intelligence Engineer, and Post Graduate Program in DevOps, that will position you for a career boost with the automation wave.