Typically, we see the most successful companies do three things.
1. Ramp up the success to new areas of IT
At this stage, the team is likely to move beyond basic help-desk level 0/1 incidents and pursue the automation of more advanced level-2 and level3 tickets. The team should also expand beyond incidents and begin working on using IPA for monitoring, dashboarding, and analytics, moving from the help desk to the data center, the network, and even application-maintenance organizations.
The long-term success of the automation program is contingent on how quickly the IPA bots are adopted within the IT organization. That depends on how effective leadership is in providing dedicated training and ongoing support, as well as building up a network of internal “reference cases.” The goal is to build on the successes to find new and more advanced use cases and opportunities within IT (as a precursor for generating demand across the wider organization).
Providing incentives for IT employees in the form of bonus payments or recognition in competitions can be effective. At this point, the CIO needs to invest in capabilities that support scale, such as risk management and IT infrastructure management. These are different from those capabilities needed for pilots, which focus on getting the technology right, demonstrating value, convincing nonbelievers, and so on. Leaders sometimes mix up up the two and underestimate what’s most important about each.
2. Get the word out
With a solid foundation of experience and capabilities in place, the CIO can begin to actively position him- or herself as both an advisor and enabler for the rest of the business. In practice, that means reaching out to leaders across various functions to inform them about the specific benefits of IPA, understanding their priorities and how to best implement and support the technologies, and identifying potential security issues through bots. IPA is by its nature disruptive.
A CIO should have a clear sense of when IPA technologies will augment or replace human workers and put in place a program of clear communications and activities for each outcome.
3. Explore advanced elements of IPA
While most IT organizations have focused on simple process automation (and to a lesser extent, machine learning and natural-language processing), the future belongs to artificial intelligence (AI) and cognitive learning, which have the potential to manage complex IT tasks.
Although still somewhat futuristic, the solutions are already emerging, and we expect them to rapidly mature over the next several years. But it takes time to build up the skills and experience needed to use AI effectively, in part because there is still a lot of confusion about what AI actually is.
The only way to overcome that confusion is to start working on AI projects. Companies that are building up expertise in this area are developing data lakes, creating meaningful tags for that data, and then dedicating engineers to build and train algorithms to act on that data.