Top 4 Challenges In Implementing Intelligent Automation

Intelligent automation is one of the most important technologies for increasing company efficiency and resiliency. Gartner listed it as its #1 strategic tech trend, and its significance will only grow in the coming years, surpassing traditional rule-based Robotic Process Automation (RPA) in favor of this new RPA fueled with artificial intelligence (AI) capabilities.

With intelligent automation, companies are already: 

• Processing extremely high volumes of unstructured as well as structured data
• Increasing worker productivity
• Enhancing operational efficiency
• Reducing costs
• Moving employees to higher value, more strategic work

According to Deloitte, 73% of senior executives say their organizations have already started on a path to intelligent automation—a dramatic 58% leap from the meager 16% reported in 2019. But just three in 10 have moved beyond the pilot stage.

With the majority of business leaders acknowledging the critical importance of intelligent automation, why is it taking them so long to go further? In this blog, we’ll take a look at the four top challenges to a successful intelligent automation deployment:

#1  Fragmented processes

Deploying intelligent automation is much more than simply attempting to automate what is already being done. Today’s companies have hundreds of different processes, most of them fragmented into silos by functional departments or divisions. Yet, many important business processes transcend organizational boundaries. HR hiring and onboarding processes affect payroll, finance, and IT. Yet, all too often, these processes are disconnected as documents or data are thrown over the proverbial wall to the person in the next department.

Intelligent automation can play a major role in re-engineering these siloed processes by enabling lean and cost-efficient operations at substantially higher speeds and 100% accuracy in comparison to traditional approaches. Those workers who struggle with multiple systems to complete a single task can be freed of repetitive (and error-prone) manual keyboarding or button-pushing to focus on higher-value work.

But before this can happen, the employees who do the work need to be involved. Process re-engineering professionals and consultants are useful, but also engage the people who know the processes intimately. And make sure to listen to them—their input will be invaluable.

#2  Lack of IT readiness

Intelligent automation requires significant support from IT. Unlike traditional RPA, which can be implemented by business units with little—if any—IT support, intelligent automation requires much more compute and storage and other infrastructure resources—and not just on-premises resources. Intelligent automation, by definition, should, in most cases, be based in the cloud for scalability and capacity reasons. And this will almost certainly require cooperation from, if not collaboration with, a fully prepared IT team that is familiar with—if not already operating in—the cloud.

#3  Employee resistance to change

Technology is just one aspect of intelligent automation. The human factor is also essential. From the beginning, businesses need to carefully consider how coming changes to roles, processes, tasks, and ways of working will affect employees. Even at the organizations surveyed by Deloitte that was in the process of scaling intelligent automation, 58% had not yet performed this kind of assessment. This view of intelligent automation—leaving the human out of the picture—is myopic and will not pay off in the long term.

A holistic approach is needed that promotes resiliency and adaptivity by focusing first and foremost on the employees. More than half of enterprises surveyed by Deloitte (59%) are retraining employees on process skills like active listening and critical thinking, and an equal number are providing retraining in cognitive abilities such as creativity and problem-solving.

#4  Lack of a clear vision

Getting it right means integrating vision and strategy. Many companies are implementing intelligent automation in a piecemeal fashion, led by either IT or business units, but without an overall strategy. According to Deloitte, only 26% of companies that are piloting automation—and 38% of those implementing and scaling—have an enterprisewide intelligent automation strategy.

What’s needed in such cases: involvement and sponsorship from the C-Suite as well as a federated model of intelligent automation governance that involves a centralized Center of Excellence (CoE) that sets standards and provides guidance to business units that are engaged in the actual initiatives.

Intelligent automation is a continuing journey

Enterprises are eager to embark on their intelligent automation journeys. But few are currently doing it successfully at scale. Fragmented processes, lack of IT readiness, and lack of a clear, enterprise-wide vision are holding businesses back from seizing all the opportunities that intelligent automation offers. By addressing these four roadblocks directly with an engaged C-suite team, and a federated Intelligent Automation CoE that engages the business users who will be most affected by the transformations that lie ahead, businesses will drive much more successful intelligent automation initiatives to gain a truly competitive edge.