Saturday, November 26, 2022

Why Enterprises Need to Add Automation in Integration

By Prangya Pandab - June 03, 2022 3 mins read

Automation enables more scalable, effective, and agile control of a wide range of integration use cases, resulting in more valuable insights and efficient operations. As companies modernize their processes, they get improved visibility and more stable and secure innovation, even in the face of pandemic disruptions and other headwinds.

Organizations are dealing with an influx of data and processes in this era of digital transformation. IT teams can manage the surge with hyper-automation without adding more resources.

Automation is becoming more prevalent, and investments are increasing. In a 2020 Deloitte survey of executives worldwide, “Automation with Intelligence,” 73 percent stated their companies were on the road to intelligent automation.

Companies can develop end-to-end business operations that are more reliable, efficient, and scalable by automating tasks. According to Gartner’s IT Automation Trends for 2022, businesses will be able to conduct 25% more processes autonomously by 2023.

AI-powered automation takes a fresh approach to integration, speeding up and cutting the cost of integration projects. Here are the top four reasons why businesses should automate integrations:

Accelerating Integration Development 

Traditional integrations are expensive and time-consuming because they require systems integrators to connect disparate platforms. Real-time communication is needed by manufacturing systems, customer care portals, and project management apps. However, connecting them with custom-coded point-to-point connections can be a maintenance nightmare. Businesses risk breaking all the links if they change or upgrade one system.

Extended teams can implement integrations faster using automation. Low-code/no-code integration tooling can leverage AI and built-in Natural Language Processing (NLP) to provide smarter mapping outcomes. Robotic Process Automation (RPA) makes integration with legacy applications easier. The latest tools also include a shareable asset library that allows easy asset reuse, speeding up integrations.

Also Read: Natural Language Processing Can Boost Enterprise Capabilities

Improving the Quality of Integration

Many companies emphasize automation system speed, but speed isn’t everything. An API designed rapidly or without sufficient testing can result in a lot of rework, which costs time and money while also affecting application performance and reputation.

Integration quality is improved via automation. Robust automation technologies use Artificial Intelligence (AI) to analyze real-world operational data to provide continuous feedback for optimizations tailored to the business. The embedded AI can provide recommendations for workflow and field mapping, develop smarter API test cases, and help find inefficiencies in the current environment.

Cost-Cutting and Increased Efficiency

Companies have a combination of cloud-native apps, legacy systems, and everything in between. The reality of today’s surroundings and budget limits do not allow for a one-size-fits-all approach to integration.

The latest automation tools are prepared for the hybrid IT world, including multiple stakeholders and integration methods. Continuous backend availability for updates via business-critical messaging and the ability to create app integration flows and expose the work for reuse via an API are all important capabilities. This avoids the several licensing fees and complications associated with other methods.

Ensuring Availability, Security, and Governance

Integration projects can put businesses and their security at risk. End users are more likely to make mistakes when more human intervention is necessary. The demand for strong security and compliance support also grows due to cloud integration.

Organizations can update systems of record with integrity and scale through automated integration. The latest tools incorporate data security at rest and in transit. Backend systems can manage workloads without expensive and disruptive modifications thanks to resiliency auto-scaling functionality. Organizations can also detect operations, deployment, and security issues as they occur, providing data for AI to use in future asset protection and best practices.

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AUTHOR

Prangya Pandab

Prangya Pandab is an Associate Editor with OnDot Media. She is a seasoned journalist with almost seven years of experience in the business news sector. Before joining ODM, she was a journalist with CNBC-TV18 for four years. She also had a brief stint with an infrastructure finance company working for their communications and branding vertical.

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