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3 Ways Human-Machine Collaboration Increases Employee Productivity

February 24, 2022 Collaboration and Productivity
scott clark
By Scott Clark

Artificial intelligence and machine learning are being integrated into our everyday lives, enhancing customer experience and providing added convenience and efficiencies that would not be possible otherwise.

As the technology advances, an increasing number of businesses are turning to these new technologies to drive their growth, not just with consumers but also internally with employees and stakeholders.

Here are three key ways companies are utilizing human-machine collaboration to boost employee productivity and job satisfaction.

No. 1: Chatbots to Help Employees Work Better

Recent research by Oracle indicates that both customers and employees would rather interact with a chatbot than a live person. According to the study, 64 percent of people trust a robot more than their manager, mainly due to AI's ability to provide unbiased information.

But the real appeal of the technology isn't about having a conversation with an AI-based bot. Rather, end users prefer the speed and convenience of chatbots, which rely upon natural language processing (NLP) and an understanding of language to support queries. Although more complex queries still require human interaction for now, AI and machine learning have improved the ability of chatbots to have full-fledged conversations.

In the workplace, AI chatbots are available for employees around the clock, which adds convenience for employees seeking answers to common questions relating to common questions about employee benefits, scheduling, insurance, vacation and sick time. In turn, by allowing some HR processes to be accomplished without human intervention, chatbots offer a better allocation of HR staff's time toward more complex and detailed tasks — while increasing productivity. 

Steven Petruk, president of the global outsourcing division at CGS, an application development, enterprise learning and business process outsourcing company, said the success of AI stems, in part, from the fact that organizations are looking for alternative and creative solutions to succeed in a post-pandemic economy, and AI and automation allow them to increase productivity without the need for more resources.

Avner Brodsky, CEO of smartwatch review site Superwatches, said companies that use both humans and AI have a competitive advantage. "A consulting group from Boston conducted a survey in 2020 and found that companies that incorporated human-machine collaboration were 'best positioned for success,'" he said, adding that another study, conducted by Automation Anywhere, revealed that 72 percent of workers said that AI and automation helped them do their jobs better.

"AI can do things that humans don't want to do/struggle with, whereas humans can do creative and social tasks that AI could not," Brodsky said. "Not only can companies save money by using AI to do the 'repetitive work,' but human employees are able to focus their skills on more creative outlets and, therefore, be more productive."

Related Article: 5 Ways Chatbots Improve Employee Experience

No. 2: Robotic Process Automation to Streamline Processes

Robotic process automation (RPA) can be used to streamline critical business processes, improve performance and gain process efficiency. It is typically used to automate mundane and redundant tasks that would otherwise take up employees’ valuable time. RPA is also useful for data re-entry, running multiple applications at the same time and sequencing basic mouse/keyboard operations, including clicking, selection and copying and pasting. 

Today, businesses use RPA in many ways. Preeti Lobo, practice director, business integration and automation at Apps Associates, an enterprise application services provider, said processes that are critical to the business, such as recognizing revenue on time, accurate reporting on revenue and getting orders loaded into the system are all processes that can be delegated to a bot, ensuring error-free processing, customer satisfaction and accurate reporting.

When combined with NLP and RPA, AI is referred to as intelligent automation (IA) and useful for automating the management of detailed documents and real-time decision-making. RPA applications can capture and interpret transaction processing data, manipulate data, trigger responses and communicate with other technology platforms.

Through these functions, RPA is able to reduce the costs associated with staffing, decrease human error and automate higher order tasks that previously required human intervention. 

Related Article: What Intelligent Process Automation Can Contribute to the Hybrid Workplace

No. 3: AI-Based Decision-Making to Boost Productivity

AI-based decision-making is being integrated into many repetitive enterprise tasks, narrowing down choices to the point where human staff can fine-tune the processes involved. Petruk’s company, CGS, was able to use AI as part of the pre-employment process, enhancing recruiting efficiency and increasing the productivity of hiring teams.

"Through a recent integration of a pre-employment assessment platform in the recruitment process, CGS was able to align candidate profiles with job requirements to quickly ramp up services and deliver a more mature support team to address customers' needs," said Petruk.

Using artificial intelligence, the company's outsourcing business added more than 500 customer agents and shortened the recruiting-to-onboarding timeline by 40 percent, he said. By doing the “heavy lifting” of the application review process, AI and machine learning can save companies significant time and effort.

"Adding AI was also critical to the company’s ability to reduce employee attrition during the training/nesting phase by minimizing mismatched expectations," said Petruk. "By rapidly getting quality resources on staff, the business experienced a 15 percent improvement to customer satisfaction while optimizing customer effort.”

Related Article: How HR Teams Can Boost Productivity in the Digital Workplace

Concerns About AI and Robotics

There is a lot of debate about how robots, artificial intelligence and machine learning are going to take over jobs and eventually rule our lives. Elon Musk has said that artificial intelligence will be vastly smarter than humans and would overtake the human race by 2025. In 2018 at the South by Southwest (SXSW) tech conference in Austin, Texas, he stated that AI is far more dangerous than nukes, and raised concerns that there is no regulatory body overseeing its development. 

Musk is not alone in his concerns about AI. Scientist Stephen Hawking warned that AI will either be the best thing that’s ever happened to us or the worst. "If we’re not careful, it very well may be the last thing,” he said. 

While many say that the possibility of such potentialities is still decades away, now is the time for AI to be developed around a framework of ethics and morality. Ethical AI, as it is called, is already being touted by the largest tech companies, and Google and Microsoft have both published ethical AI principles.

Microsoft puts its ethical standards into practice through its Office of Responsible AI (ORA), the AI, Ethics and Effects in Engineering and Research (Aether) Committee, and Responsible AI Strategy in Engineering (RAISE).

Google has committed that while it will work with government entities on AI technologies for cybersecurity, training, military recruitment, veterans’ healthcare and search and rescue, it will not develop AI-based weapons or other technologies “whose principal purpose or implementation is to cause or directly facilitate injury to people.”

A more common concern is that AI and RPA will eliminate jobs that would otherwise be done by humans. For proponents, the hope is that AI and RPA will augment, rather than take away, human jobs. In fact, as these three examples illustrate, AI-based technology has the power to enhance and increase productivity and job satisfaction. 


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