X
GO
 

The New Narrative 

Want to know what makes us different? This is a great place to start. See how we’re innovating and experimenting, constantly. And get our take on the ideas of the moment— and where we think tomorrow will take us—across the industry and around the world. 

 

The New AI: Why Automated Integration is Key to Artificial Intelligence

As organizations across the globe continue to invest heavily in AI solutions to automate their activities, there is one key piece of the puzzle that cannot be overlooked: automated integration. First, let’s define what “automated integration” actually means. The integration of an AI solution simply means that the API endpoint is leveraged to perform the tasks formerly executed by humans lives within a product or a workflow, meaning that it is accessible to those who need it. Automated integration refers to the idea that this entire process is executed with no intervention from humans.

When companies tap into AI-driven SaaS platforms, there is often not a specific integration methodology provided. Instead, the organization receives an API endpoint they can leverage to execute the new automated processes they have paid for and it is up to their teams to integrate it in the best way possible.

This is how Narrative Science works with organizations to facilitate the automation of writing of reports across the enterprise. A common pitfall that businesses who work with Narrative Science, and other AI SaaS startups, are susceptible to is not automating the end-to-end process where they are trying to leverage AI. Here are three reasons why this is so crucial to success:

  1. Engagement with the new integration is at risk when the process is not automated. End-to-end automation contributes greatly to the overall efficiency of the end user, which makes it more likely that they would look to adopt this new tool, platform, solution, etc. However, if the end user feels that their time and skill is still heavily required, especially at multiple touchpoints in the workflow, they may not see any incentive to engage despite the ease of adoption.
  2. The ability to scale a new AI-driven solution is only feasible if the integration is totally automated. If each report or process that an organization is trying to replace with AI still requires some level of human interaction, then they can only scale at a speed achievable by humans, versus the speed of a machine.
  3. Automated integration lets organizations take full advantage of the cost- and time-related benefits inherent to AI. Typically, this is important to organizations that leverage these types of technologies, since they are looking to save money, increase operational efficiencies, and allow their teams to focus on higher-value tasks. If an automated integration is overlooked, these benefits can not be fully maximized, as human interaction is still required.

Read our white paper and learn more about Intelligent Automation >>

Print

Privacy Policy | Cookies Policy | © 2018 Narrative Science