Organizations around the world are using automation to maximize the output of their most valuable assets – their people. By automating previously time-consuming and largely manual tasks, employees can refocus on higher-value work. The most significant investment is seen in robotic process automation (RPA). RPA takes the form of programmable software that mimics how people work. A virtual workforce of robots, or bots, can perform tasks at greater speed and scale than what’s humanly possible.
The convergence of RPA and digital is moving the goal from simply adopting task automation for productivity gains to achieving intelligent automation for faster, more insightful decision making. Intelligent Automation (IA), which includes technologies such as machine learning and dynamic workflow, delivers exponential value by learning and adapting as it automates.
Reaping the benefits of intelligent automation
The foundation of many business operations is automation and, with technology continually and rapidly advancing, business leaders are increasingly thinking about what will be possible next.
Looking beyond RPA, previously hidden opportunities are revealing themselves. A combination of automation, AI, and data analytics are allowing companies to realize the benefits of intelligent automation. In this new era, companies are enhancing automation with learning and judgment strategies to deliver cognition similar to the human brain.
Take Google’s AlphaGo program as an example. The program mastered the ancient board game Go in a matter of days. A game that many people believed only humans could excel in, since it requires intuition and abstract thinking. But, through machine learning, AlphaGo was able to recognize patterns and determine the next best moves on its own. Most surprising of all, by forming its own strategies, AlphaGo went on to defeat some of the world’s best human players.
Some businesses are already reaping the benefits of the same intelligent automation that powers AlphaGo. They have evolved beyond basic, routine automation and structured data. By adding intelligence to automation, they are exploring reasoning, knowledge, planning, learning, and natural language processing capabilities.
Are you ready to take the lead?
When intelligent automation reaches its full potential, it will amplify, and not simply replace, human effort. Even with AlphaGo, many of the moves made by the program inspired human players to rethink their own strategies that had otherwise remained largely the same for thousands of years. In the same way, intelligent automation can allow users to take a step back and improve established ways of doing business.
While technology is essential to intelligent automation, people are at the heart of any initiative. After all, if the future of your business is automation, who will make it happen? Who will teach the systems the current way of doing things, how to recognize what you value most, and how to deliver it? You will. After all, no one understands your business and its processes better than you.
Intelligent automation begins and ends with people. Sometimes, there’s no substitute for human intelligence. Especially when there’s a need to use complex business rules, call on judgment to determine the proper course of action or use discretion to navigate gray areas. You need deep knowledge of your business and industry to guide automation toward real, significant returns.
Of course, automation doesn’t become intelligent overnight. There are three key stages every organization must experience on its journey toward intelligent automation.
For intelligent automation to be successful, you must understand the relationship between people and machines. As business processes are increasingly automated, preparing your workforce to excel in this new environment is critical. During planning, it’s also important to consider how to embed automation seamlessly into existing programs and initiatives, without disrupting other parts of the business.
A major part of the planning process is identifying where intelligent automation can deliver the most value. This requires objectively reviewing processes and the specific activities within them. You need to determine what can be automated by basic robots, and what requires advanced technologies like machine learning, natural language processing or computer vision. In your assessment, consider the nature of the process, data inputs, risks, controls, supervision, and stability.
And, lastly, remember that automating a broken process won’t fix it. A process should be stable and mature before applying automation. Just because a process can be automated, doesn’t mean that it should be. Especially if you can’t identify the potential benefits and ROI.
2. Change management
Intelligent automation will undoubtedly change how your business works. For a smooth transition, you need a change management strategy. This includes an execution roadmap, an enterprise operating model, and a proven method for measuring ROI. You will also want to establish centralized operations and embed intelligent automation into existing programs and initiatives.
When deploying intelligent automation at scale, leadership should engage key stakeholders from the start to ensure buy-in, adoption, and to prepare current employees to learn to work in tandem with AI. According to our AI 360 study, 80% of workers say they are willing to learn new skills to take advantage of AI, yet only only 35% of workers report such options are available at their companies – and only 21% say they have participated in said training. Providing training helps people understand how automation will enhance, and not replace, their jobs, inspiring them to be more confident in the workplace. Forming a dedicated communications team tasked with raising awareness of the benefits can help, too.
Any organization deploying intelligent automation at scale needs to establish a governance framework. This framework will determine who oversees the technology, who will make the major decisions, and who will manage escalations.
The bigger the role automation plays in your organization’s infrastructure and security, the more important governance becomes. You should be able to monitor performance, including exceptions and errors. There should also be command and control to ensure intelligent automation is making the right choices. This is why humans with industry expertise will always have a role in the automated future.
Looking to the future
Your intelligent automation journey will be ongoing. In the future, new technologies will appear and existing technologies will converge to form new cognitive capabilities. But, we shouldn’t fear change. The future of intelligent automation will lead businesses toward more adaptive processes that help leaders uncover greater ROI from their human, and robotic, resources.