Here’s the paradox: it takes people to automate. Enterprises are moving aggressively to automate as many of their processes as possible, through artificial intelligence, machine learning and robotic process automation. Automation opens up new types of career opportunities, from programming to training. Automation also liberates employees for higher-level tasks. But it can’t simply be inserted into operations without forethought and consideration of the wider impact.
That’s the word coming out of a survey of 4,000 employees released by Automation Anywhere. Overall, people don’t fear automation — if anything, most welcome it. They express high levels of curiosity as to how AI can help them do their jobs better. Almost three quarters (72 percent) see the technology as something they work with, rather than something that will replace them. This is opposed to just eight percent of respondents who strongly feel the opposite.
A majority (57 percent) of employees say their productivity would accelerate in the long run if their organization provided more opportunities to trial different types of automation or AI, compared to just 16 percent who feel things will bog down.
Currently, 38 percent of employees use some form of automation to perform their jobs, and there is an expectation that this number will continue to increase.
The survey’s authors, led by Dr. Chris Brauer of the University of London, says the key to automation is not wiping away and replacing human workers, but finding ways for human and digital workers to work side by side, complementing one another’s skills. “We found that augmented companies not only enjoyed 28 percent greater performance levels, but also scored 33 percent higher on factors deemed to make a workplace more ‘human,'” he points out.
“Automation can make work more human by allowing people to transfer simpler tasks and processes to machines,” the survey report’s authors state. This “frees up resources – time, money, effort, brainpower – to be reinvested in the human workforce, through skill development, learning new things, being creative, solving complex problems, spending more time interacting with customers and developing the business.”
Organizations need to build cultures that evolve as technology is added. By optimizing for immediate productivity gains without creating a culture of support and advancing skills, there will only be temporary spurts in efficiency without long-term performance sustainability. Brauer and his co-authors suggest the following courses of action to introduce AI, RPA and other technology strategies in a smart and strategic way:
Run in parallel: “Start small and build a foundation. RPA runs on top of existing information systems, enabling lightweight implementation that almost immediately begins to achieve ROI without changing the IT back end. However, building a foundation for augmentation means thinking about the organization as a whole and then finding use cases to run the new systems at the same time as keeping the traditional methods in place. When people begin to feel the efficiency of the augmentation, start to phase out the traditional approach.”
Act like a startup: “Startups serve to test a new idea and find out if it can create and deliver the value its founding entrepreneurs conceived. This involves a lot of fast learning on the fly, a good approach for moving into uncharted territory. By creating a small internal start-up, this new unit is unburdened from the procedures and risk checking that comes with formal oversight, and free to dedicate its focus on the experimentation needed
to test the new idea.”
Protect people, not jobs. “As tasks moves from the human to the automated system, it becomes the responsibility of the human to oversee the system. As algorithms are unable to conceptualize in a general context, human oversight remains critical. Empower employees to rewrite their job descriptions to reflect this new responsibility, and to decide how they will use any time freed by the absence of repetitive tasks.”
Set up a center of excellence: This center or team would be dedicated to reskilling your workforce and supporting their needs involving RPA and AI technologies. This dedicated unit should develop a knowledge base and library of reusable solutions, accessible companywide.”
Seek diverse talent pools: “Build a workforce with resilience and a growth mindset, focusing on diverse minds rather than only skills and capabilities. Build internships to promote learning, ensure development opportunities, and address the hiring gap now.”
Keep things simple, and build case studies of success stories: “It’s important to show this level of clarity because you care about people’s interests, not just because you need to be perceived as caring about people’s interests. Additionally, a business shouldn’t make claims about their use of AI to come off contemporary if people later find out that you don’t use AI at all. Be a leader in creating ethical guidelines for your company.”
Emphasize transparency: “Demonstrate governance, adhere to regulation and be transparent about internal policies, procedures, and code of conduct for the ethical and honest use of automation and AI. Periodically report the status of automation in your organization and how it measures up to the rest of your operating environment. Use clear language – avoid overly buzzword heavy marketing, and don’t use wording that blurs or confuses meanings.”
Take a collaborative approach to automation: “Considerations that must be taken into account: decentralized workforce (who is touching the data? Where? What happens to their access when they leave?), decentralized office structures (what third party systems does the data pass through? Are they secure? Is the data protected?), are your AI and automation systems auditable? How are they being monitored to ensure systems are working according to design? Successful automation adopters take a participative and collaborative approach, and enable quick decision making to facilitate speed and scale.”