As we head into 2019, the increased pervasiveness of artificial intelligence in applications paired with customers' expectations for instant digital transactions is prompting organizations to reimagine how they will structure processes, operations and personnel to deliver excellent customer experiences.
An important undertaking for enterprises is to examine how business leaders should approach managing a hybrid human-digital workforce.
According to Genpact research, 79 percent of AI leaders–companies generating the greatest impact from AI–expect their employees to be comfortable working alongside robots by 2020. Yet, this carries significant implications relative to reskilling, resourcing, and change management.
How should leaders begin to prepare? In this eWEEK Data Points article, we present six recommendations from Sanjay Srivastava, chief digital officer at Genpact.
Data Point No. 1: Start thinking about managing a digital workforce now, not tomorrow.
As new technologies continue to disrupt traditional business models, companies need to design and implement structures and processes that address these changes. With this comes a new digital workforce that combines man and machine to augment the capacity of each worker.
Data Point No. 2: Understand change management and why a smart approach is necessary.
Often, companies overlook change management, which will create problems down the road – especially as some workers only consider the negative consequences of adding robots to the workforce. Companies need a clear and actionable change management strategy that will help mitigate risk and drive more successful implementations.
Data Point No. 3: Establish a strong governance protocol.
In order for companies to manage a digital workforce successfully, they must centralize their workflow orchestration into a single view across locations, environments, and systems, which provides increased visibility across the entire workforce. Companies with strong governance protocols can easily identify any disruptions and deploy quick fixes for any issues.
Data Point No. 4: “Visualize” your operational workbench.
In the past, companies could easily track when employees clocked in, clocked out and if they didn’t show up for work. With the integration of robots, it’s difficult to track if a robot experiences a glitch. For instance, if there is a coding glitch in a CRM system, it can take time to isolate and potentially disrupt P&L numbers weeks after. A potential solution is to develop a “visualization dashboard” to track robots and critical assets.
Data Point No. 5: Be mindful of AI bias.
AI bias can manifest itself in a number of ways (recruiting, sales, customer service), which can have unintended effects relative to managing a digital workforce. Often, the problem lies with faulty data input from humans – stemming from inherent human biases, bots emulating negative language that produces negative content. To avoid this, it’s critical for humans to identify conscious and unconscious biases, while training machines, to avoid these negative ramifications.
Data Point No. 6: Know AI’s limitations.
There’s a common misconception that AI is more mature than it is – particularly in business. Understanding how far businesses can go with deploying AI solutions, and being aware of its inherent limitations, can help organizations better manage digital workforce planning.