January 5, 2021 By Dinesh Nirmal 5 min read

This is the first in a series outlining a new approach to automation.

As digital transformation accelerates across the globe in nearly every industry — fueled, in part, by the challenges posed by COVID-19 — companies are increasingly faced with managing the critical IT systems and complex applications that span the hybrid cloud landscape. It is no surprise, therefore, that when I talk with clients, the one topic that is increasingly top of mind is something that has been with us since the dawn of the industrial age — automation.

An inflection point for automation

So why the growing interest in automation now? Today, we are at an inflection point shaped by several technology trends. First, there’s the explosion of digital business, as companies scramble to remain competitive by digitizing and automating their business processes and IT operations. Another driver is recent advances in artificial intelligence (AI), resulting from the convergence of visual recognition, natural language processing and machine learning. These technologies have opened the door to new possibilities for a more intelligent form of automation that taps into the ability to process and synthesize vast amounts of data in record time.

Putting it all together creates a new approach — one we call “AI-powered automation” — and it has enormous potential to enable companies to digitally transform and improve how IT and businesses operate with unprecedented speed, at scale. Adding AI to the automation toolkit helps organizations discover and decide where to best apply automation digital transformation — arming employees with the knowledge they need to accelerate innovation and make more informed decisions to improve outcomes — allowing them to, essentially, work smarter.

Companies can apply AI-powered automation to manage complex technology environments and simplify workflows and tasks, all of which reduce costs and give back time so that people can focus on what is most strategic. We believe AI-powered automation will make all information-centric jobs more productive. Automatic incident detection, for example, can help avoid digital outage. And digital employees can help automate business operations.

Four key elements to AI-powered automation

To realize these productivity gains, we have an approach to AI-powered automation we describe as having four key elements: Discover, Decide, Act and Optimize. Without AI, data discovery associated with automation is mostly limited to structured processes and structured data. But AI tools like machine learning and the natural language functions found in the Reading Comprehension feature of Watson Discovery have advanced to the point where they can understand unstructured data and processes, allowing organizations to discover patterns and opportunities in noisy data and helping to lessen the burden of manually reading and analyzing data. 

Making actionable decisions on that data then becomes a function of a well-defined methodology, and AI-infused tools like IBM Operational Decision Manager can execute decisions within business and IT operations at a speed and scale well beyond traditional automation. Acting on those decisions falls largely into the realm of the tried-and-true technology known as robotic process automation (RPA), but with a much greater reach thanks to AI.

RPA is no longer about automating simple, single tasks, but rather about digitizing complete systems and workflows. To achieve the full combined benefits of the discover, decide and act facets of AI-powered automation, optimizations must be continually applied, using tools like Watson AIOps to capitalize on new insights to autonomously enhance business and IT operations, moving beyond reactive to predictive and proactive. 

Client use cases

Using this “Discover, Decide, Act and Optimize” approach allows us to understand where clients are in their automation journey and unlock to faster paths to business value, as the following examples illustrate:

  • ENN Group, Ltd, a green energy company in China, implemented a virtual assistant solution at the start of the COVID-19 pandemic to respond to employees, now suddenly working remotely, with their IT service desk requests. Within a half a day of setup, the virtual assistant helped enable thousands of employees with the technology they needed to work remotely — an effort that would previously have taken days or weeks.  ENN has also implemented an automated financial assistant, based on IBM RPA technology, to handle back-office tasks, reducing processing time by 60% and generating millions of dollars in savings.
  • Turkcell, a mobile phone operator in Turkey, used the AI-powered IBM Datacap OCR (Optical Character Recognition) solution to process 15 million customer contracts in six months, saving labor costs, decreasing compliance risk and improving client responsiveness — as the old process would have taken their staff of 20 well over two years to complete.
  • The Administrative Office of the Courts in a southeastern U.S. state used AI-powered automation to accelerate their claims processing by 77%, allowing them to keep up with growing caseloads that include 135,000 claims per year.

Stories like these reinforce that AI-powered automation can generate tangible value. In fact, the IBM Institute for Business value estimates that automation supported by AI will generate billions of dollars in labor value in 2022. And 80% of AI and automation early adopters expect to significantly outperform their competitors, because the ultimate benefit automation delivers, supported by AI, is a smarter way to work that results in scalable revenue growth.

IBM automation solutions

That’s why over this past year IBM has invested in building out an integrated suite of IT and business automation software supported by our IBM Cloud® Paks, which are designed to help companies drive innovation across their expanding environments and accelerate their digital transformation.

The core of these automated AI offerings is Watson AIOps, built on Red Hat OpenShift. Watson AIOps is designed to help enterprises proactively self-detect, diagnose and respond to IT issues in real time. IBM’s recent acquisition of Instana, an application performance management and observability company, will enhance this IT automation portfolio, giving clients the most complete AI-powered automation platform in the industry.

IBM also continues to make significant investments in expanding our business process automation offerings. These include our acquisition of WDG Automation to provide clients with broader access to intelligent automation through software robots; our expanded partnership with ServiceNow to develop a joint solution to help companies reduce operational risk and lower costs by applying AI to automate IT operations; the IBM Cloud for Telecommunications —  an open, hybrid cloud architecture designed to help telecommunications providers address the specific challenges of the highly-regulated industry; and continued updates to our IBM Cloud Paks to help companies drive innovation across their expanding environments and accelerate their digital transformation.

These investments reflect our conviction that automation, powered by AI, is the next major innovation in hybrid cloud software and is the key to improving business performance — today and over the next decade. We look forward to continuing to partner with our clients to accelerate innovation and improve efficiency, helping companies find smarter ways to work and giving back the gift of time, so the focus can be squarely on finding new ways to drive growth, compete and win.  

The next feature in this series will focus on the important steps involved in implementing an enterprise automation strategy.

For a deeper technical dive, please see “AI-powered Automation is Enterprise 2.0” by Jerry Cuomo, IBM Fellow, VP and CTO, IBM Automation.  

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