The COVID-19 pandemic has caused organisations all over the world to reconsider their workplace. Over 80 per cent of employers will enable employees to work remotely part-time after the pandemic. In comparison, 47 per cent will allow employees to work remotely full-time, as per a Gartner survey.  

While many have adapted to a more digital-based workspace and automated them with ease using AI-based models, others are having difficulty adjusting to a more digital-based workspace. 

With the rising tide of anxiety and uncertainty around AI — anything from how many jobs will be lost to who will train the AI systems — the topic of how to accomplish human-machine collaboration has taken on new significance. After all, these mutually beneficial interactions, which are centered on augmentation rather than displacement, have the potential to increase business value while reducing the danger of job loss. 

AI fostering automation

With the rising adoption of AI-powered solutions, automation will impact the workforce. The automation technology is broadly divided into three categories:

Robotic Process Automation (RPA): The technology automates repetitive tasks or rule-based operations. An RPA bot focuses just on a consistent set of rules to a process to give rapid and efficient results. The system can not learn, adapt, or make decisions of its own. To be precise, a lot of manual administrative processes can be streamlined, thereby enabling the workforce to focus on complex tasks.

Machine Learning: Machine learning is the next step, a computer not just understands but predicts courses of action using enormous amounts of data, with an ability to improve its performance over time. Take, for instance; ML is being employed in the banking sector in the form of chatbots. These bots interact in real-time with human customers, using technologies like natural language processing (NLP) to grasp the nature of the customer's enquiry by looking at their past interactions and offering them responses.

Cognitive Augmentation: Closest to general artificial intelligence, today, cognitive computers, let's say IBM'sIBM's Watson, can manage unstructured data and respond to complicated inquiries, allowing them to accomplish tasks that previously could only be done by people.

Ways to adapt

The goal is to create a symbiotic relationship between humans intelligence and intelligent machines - what we call an "Augmented workforce". To start with, it is essential to rethink the current worker roles and business processes so that humans and AI can operate together.

Moreover, the lack of explainability of ML models is yet another reason why human-machine cooperation is required. AI lacks the capability to communicate accurately in its decision-making processes. Hence the voices for XAI (explainable AI) are making rounds. It calls for experts (humans) to examine the accuracy and logic of AI solutions and assist data scientists in improving their models.

Image Credit: Alexandre Gonfalonieri blog

Avoid quick wins: Organisations have shifted their focus on technologies and quite often look to apply them to business. Intelligent automation, on the other hand, isn't about replacing people with technology or achieving quick wins with a technological solution. Instead, businesses should adopt a holistic approach, defining a vision for a completely new customer experience or process and then implementing new automation technology to realise that goal.

Invest in the workforce: The way businesses handle the balance between AI, and its workforce will be crucial to their success. In the short term, businesses should focus on re-skilling their existing employees and parting them with the training required to use and operate with these new technologies. In the long run, the question becomes how to upskill people for new or evolving positions or how to support them when they leave the company.

Transparency is the key: Companies need to be transparent about their path towards automation, making their workers understand the need and way forward. The thing to consider is that employees will regard automation as a ticking time bomb for their employment prospects, leading to erroneous assumptions and resistance. Don't add to their existing terror. Instead, be open and honest about why the changes are being made, their potential consequences, and how the employees can participate in the transformation. 

A systematic approach to preparing the workforce becomes even more crucial when organisations progress toward more complicated automation strategies. It'sIt's important to note that machines learn by observing humans perform tasks.