Organizations are adopting a new breed of automation. How business leaders prepare for this new era of automation will make or break organizations.
Organizations are adopting a new breed of automation. Many believe technology will vastly improve business and society. Others fear it will replace human workers and pose an existential threat to the way we live.
This conflicted view of intelligent automation (IA) — encompassing both robotic process automation (RPA) and artificial intelligence (AI) — reflects the mood 150 years ago when electricity began to transform the global economy. Power introduced new products. It changed how we communicate, work and live in ways few had thought possible.
How business leaders prepare for this new era of automation will make or break organizations. Nineteenth and early twentieth century humans adjusted to working in the new electric world in the same way today's workers will learn how to collaborate with AI and intelligent machines. Here are three ways leaders can prepare their workforce, and themselves, by understanding that while AI is very different than anything that has come before, we do have a historical blueprint, electricity.
Leaders need to build a learning culture that embraces innovation and experimentation. The speed of change demands a workforce that can adapt fast. They must identify challenges and opportunities in non-linear ways. This learning culture will help employees understand machine-learning-led technologies and business models. It will also reveal opportunities to partner with traditional allies and former competitors within and outside their industry sectors.
Working with AI requires the ability to collaborate with technology in an intellectual way. This involves embracing new broad-based cognitive skills and creativity to understand how AI adds value to the business as a whole. In the future, knowing how to code, having legal expertise, or even practicing medicine won't be enough if these professionals can't envision how AI will enable their organization to do the work better.
Machine learning is a feature of AI that allows applications to learn from exposure to data and feedback from people. Governing what machines learn and allowing them to build upon the knowledge they gain by interacting with customers or employees will be crucial in delivering a well-rounded machine education.
One of the largest banks in the world is developing advanced AI conversational technologies that will bring customers closer to the bank. However, in the early days of deployment these technologies are limited and add less upfront value for customers since AI apps need time to learn, get exposed to data and receive feedback and adjustment. However, understanding how these technologies improve and being able to explain how the systems are operating and making decisions are critical to the deployment scope and governance decisions.
The electricity era introduced power for illumination, communication and automation that greatly enhanced productivity by giving workers better conditions, including lights and motors, to improve the speed and quality of their work. Light allowed 24-hour productivity and electric motors powered machinery and tools that enhanced the skills, comfort and speed of labor. The AI era will have an even greater effect. AI is a metaphor to electricity in terms of its ability to illuminate data and provide insights that were previously unseen. AI also is a fundamental power source for automation and intelligent communication, allowing machines to be more autonomous while still working alongside and for people. Like electricity, AI on its own, does little. It must have a well-engineered application that it can power.
The challenge for business is to use AI to improve productivity and quality. Humans are required to invent the applications and then train, monitor, govern, and improve the processes of AI automated and augmented work. The human-machine partnership can improve product and service standards and consistency. It can also enable businesses to re-imagine the way they interact with customers. If done well, employees will be able to focus on work that is more satisfying while also delivering more business value and a better customer experience.
Working alongside automated counterparts can also help make work more rewarding by reducing repetitive tasks like time and expense sheets. We've built an expense reader based on AI that reads the tax law and recommends decisions on how expenses can be justified, taking feedback from experts and learning as it is exposed to more transactions. The system frees time for highly skilled people to solve problems, interact with clients and do more interesting, valuable, and innovative tasks.
In the late nineteenth century, a fresh generation of leaders created new businesses and reshaped sectors by embracing innovation — even when they didn't understand its potential. To understand the potential of IA, today's leaders must think in exponential and existential terms. Even if they can't completely visualize what the future looks like, they can establish learning cultures, teach AI the right way, and rethink productivity to realize the power of human and machine collaboration.