Advances in artificial intelligence and machine learning have ushered in a new age of automation, transforming the way we work and, ultimately, the way we live.
Automation -- and in particular, robotic process automation (RPA) -- can now match or even surpass human performance across a widening range of business processes. As a technology category, RPA is rapidly expanding across multiple industries such as banking, healthcare, insurance and manufacturing as benefits like improved accuracy, efficiency and productivity become clear. Its greatest advantage, however, is not just to organizations, but also to humans, who stand to benefit from the technology.
A new study from Goldsmiths, University of London, which was commissioned by my company, found that 72% of 4,000 workers surveyed across North America, the United Kingdom, Japan and India believe AI and automation will help them do their jobs better. The respondents claim that when organizations transfer tedious, repetitive tasks to RPA bots, they are free to focus on more rewarding challenges, creativity and skills development. Unsurprisingly, these employees anticipate greater engagement and a healthier work-life balance, both of which contribute to higher productivity.
But many companies are consigning both RPA and AI technology to small-scale and proof-of-concept use cases as they continue to evolve their automation strategies. This same University of London report found that, globally, just 38% of workers use automation technology in their daily roles, and only 3% of CEOs said they’ve implemented AI at a “fundamentally operational” scale across their companies.
We anticipate a dramatic increase in the adoption of these technologies over the next several years. In fact, a study from Deloitte estimated 72% of enterprises will use RPA by 2020, leading to near-universal adoption within the next five years.
We’ve realized that the implementation of AI and automation requires organizational changes. When companies take the time to address the following five challenges, they can reach the full potential promised by AI and RPA. These include:
1. A greater focus on culture and technology: The challenge to scaling automation and AI across an organization often lies not in the technology itself, but in ensuring the company has the right culture to adopt the changes to its working environment. In contrast to popular opinion, we found that 57% of respondents believe their productivity would increase if they were given the opportunity to experiment with AI and RPA in their daily work. Too often, however, automation projects start as initiatives for a particular use case and struggle to scale.
Rather than using RPA on discrete projects, we recommend organizations establish an internal team that acts like a lean startup to learn by doing. This approach requires C-level buy-in but helps direct organizational focus on building a larger automation strategy. It can be a difficult task, so make sure to celebrate early wins and build trust in newly implemented technologies.
2. Upskilling and reskilling employees: Prevailing estimates predict automation will likely replace 30% or more of tasks but only 5% of jobs in their entirety. That means companies must upskill and reskill their existing employees by emphasizing increased social skills, empathy and creativity while simultaneously training employees to work alongside RPA bots. They should also commit to nurturing people -- not making it just about jobs. Employees realize that jobs have always evolved and always will.
3. Investing in diversity: Diversity is critical from both a human and business perspective, but globally, just 22% of AI professionals are female, according to LinkedIn (via the World Economic Forum). The lack of diversity in the cognitive technology sector, in particular, has negative economic and societal repercussions for those left behind by fast-moving technological developments.
From a business perspective, a homogenous organization encourages biases and actually limits innovation and problem-solving. When building a new organizational structure, such constraints may lead to processes and services that fail to serve every end user and customer. Companies must instead work to attract diverse talent pools that foster organizational resilience and diverse viewpoints.
4. Maintaining authenticity: The hype around AI and automation may lead to internal ambivalence about the introduction of such new technologies, hampering productivity and efficiency gains. Augmentation is not just about new technology but also about changing organizational culture. That requires buy-in and engagement from your workforce, which is encouraged by a commitment to transparency on where the company is going and how automation plays a role.
A majority of employees feel that while AI is discussed frequently, most people actually know very little about it. According to the University of London research, 53% of workers are skeptical when an organization claims its product or service has AI capabilities. It’s important to avoid overpromising and underdelivering. Instead, be clear and honest to build employee and customer trust.
5. Encourage resiliency: We don’t know every skill that will be valued in the future. Therefore, the challenge now is to promote resilient and dynamic thinking that allows organizations to respond quickly to changes wrought by augmentation and automation. That means every worker needs to embrace a growth mindset that emphasizes the flexible thinking needed to thrive in a constantly changing environment.
Automation is just beginning its ascent. With RPA, employees are free to do what humans do best: think creatively to solve the most important problems of our day and build toward the future.
