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ARTIFICIAL INTELLIGENCE DRIVES OUTCOMES IN BUSINESS PROCESSES

By: Dr. Chung-Sheng Li, Global Research Global Research Artificial Intelligence Lead, Accenture

Accenture Research Finds AI Can Potentially Boost Labor Productivity by Up to 40 Percent

In our world of rapid technological development and increasing competition, the ability of organizations to adapt to change has never been more important. Business process agility has transitioned from being a ‘nice-to-have’ to become a key pillar of long-term success.

The challenge is that traditional approaches to business process management are no longer fit-for-purpose. The myriad rules, standards and KPIs that businesses have used for decades to increase operational efficiency, cut costs and maintain service and product quality are simply too rigid for today’s markets.

What’s needed is the ability to understand clearly what’s happening, while it’s happening, and to be able to respond immediately. That’s where artificial intelligence (AI) is proving to be a game-changer.

AI – a collection of advanced technologies that allow machines to sense, comprehend, act and learn— helps organizations move away from constricting, rules-based processes to outcomes-based processes. So, instead of following a ‘cookie-cutter’ approach to business management, organizations can instead base their decisions on real-world conditions in real-time.

AI is set to transform how businesses run, compete and thrive. When implemented holistically, these technologies help improve productivity and lower costs, unlocking more creative jobs and creating new growth opportunities. With timely data and analytic methods, AI provides intelligence about an organization’s performance; such as whether a new marketing campaign has increased revenues at higher margins, for example, or whether the move toward fewer suppliers has helped to reduce manufacturing defects. In short, AI takes care of the ‘how’ questions of a business, freeing executives to concentrate on the more important ‘what’ and ‘why’ issues.

Case Studies

The attractiveness of this approach is clear, and we’re seeing its adoption gather pace across a wide range of industries and business functions. At one global consumer goods manufacturer, for example, an AI system helps compile detailed intelligence reports on suppliers by automating the search, extraction, aggregation, and synthesis of unstructured data, enhancing sourcing insights and leading to a 30 percent increase in capacity.

At a multinational technology company, an AI system that uses natural-language processing is analyzing customer emails, automatically handling simple requests and identifying which cases might require further treatment by a human agent. The result has been a faster resolution of requests and an increase of about 30 percent in capacity. Thanks to these types of applications, Accenture research has found that AI has the potential to boost labor productivity by up to 40 percent.

The imperative for organizations is clear: adopt AI-enabled business models or risk being left behind.

4 Rules to Success

Implementing AI can, however, be a challenge and business leaders will need to adopt a new mindset as well as invest in the right technologies. We believe the move to outcomes-based AI-enabled business processes demands the following from business leaders:

  • Adjust to an outcomes-driven perspective. Best practice and business expertise can be used as the basis for AI outcome-driven approaches.
  • Communicate clearly. Outline the differing needs of the various business units so IT can build the levers to collect the right data.
  • Combine knowledge-driven approaches with data-driven methods. AI isn’t a panacea. To succeed, businesses will need to mix machine learning with machine reasoning.
  • Remember the human element. The goal is to have technology adapt to people, rather than the reverse.

AI is rapidly evolving from back-end processes to become the face of a company’s digital brand. In this new world, executives must look to implement robust, outcomes-driven AI systems. Retooling business processes to become more flexible and fluid is the first step in this journey.

To read more about Accenture’s perspective on using AI to succeed in the new business process era, please visit www.accenture.com/AIbusinessprocess.

Chung Sheng Li: IAOP PULSE Outsourcing Magazine

About the Author: Dr. Chung-Sheng Li is currently the Global Research Global Research Artificial Intelligence Lead in Accenture Operations. For more than 25 years he held various roles at IBM Research Division in the areas of cognitive algorithms, next-generation cloud data center, cybersecurity, unstructured information analytics, business integrity and e-commerce. He has authored more than 100 issued patents worldwide, 160 journal and conference papers, and received the best paper award from IEEE Transactions on Multimedia. He is a Fellow of the IEEE and member of ACM. Home remodeling is one of his hobbies.



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