Machines have a centuries-old tradition of automating physical labor that previously relied on humans. In the past several decades, computers started to automate transactional tasks, which greatly amplified the ability of organizations to execute complex processes at scale. More recently, Artificial Intelligence (AI) has begun to automate cognitive tasks, which is completely reinventing concepts of digital productivity.

Now we stand at the dawn of a new automation era in which AI is gaining the ability to design new automations independently through what is known as Intelligent Automation (IA). While the impact of IA on business productivity and efficiency are easy to imagine, the effects on companies’ bottom lines through ROI promise to be just as substantial. In this post, we’ll look at several ways that IA promises to accelerate an organization’s ROI.

Augmenting Automation Creation

One of the most direct results of IA is a decreasing reliance on human labor to craft new automations. Most IA technologies still require some level of human intermediation, but humans are far less central to the process than in previous technological eras. For example, the autonomic framework 1Desk can observe a human worker, resolve an issue and then recommend a new automation based on those actions. Similarly, the intelligent RPA platform 1RPA can independently structure unstructured data (an often arduous task), which supports the rapid creation of new automations.

By augmenting the automation creation process, IA functionality delivers several positive implications: 1) IA empowers automation engineers to create more automations more efficiently, and 2) it opens the process to non-coders and other users who lack advanced computing degrees. IA allows companies to add additional automation affordably and reinvest those savings into other parts of the business.

The Optimization of Automations

IA systems have the power to A/B test different flavors of automations at scale, which they can use to quantifiably discern which formulation produces the best outcomes. For example, if an IA system is tasked with creating an automated email marketing campaign that will drive more conversions, it could independently attempt a few different variations of the same campaign, e.g. sending emails on different days or times, targeting different customer segments, or using different content elements within the email. Furthermore, an IA solution can record and retain the lessons learned from these experiments to build better automations moving forward. With IA, companies will not only have more automations, but will have more powerful ones.

Talk to Action

There are various forms of AI, including conversational AI which allows users to engage with a digital system simply through natural language. When you combine IA with conversational AI platforms such as Amelia, users can issue top level commands to create or edit automations. For example, a HR director could simply say, “Please ensure that all new hires in California complete required training during the onboarding process.” The system would then interpret the command and translate that into an executable workflow. The HR director in this example doesn’t necessarily need any in-depth coding or automation training to add a new step to the onboarding process. This ease-of-access allows new specific automations to be created/edited efficiently and with limited overhead.

While much of the excitement about AI in the enterprise space is rightly centered on its potential to improve productivity, the real sea change in generating ROI will begin manifest when AI begins to design itself in part through Intelligent Automation.

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