Work that Machine

‘Taking the robot out of the human’ is a powerful first step in applying automation to work processes. But what if we bring machine intelligence into the equation? Cognitive systems can mimic human behavior; this is visible in their mastery of natural language and their understanding of audio, video and images. Deep learning enable these systems to observe processes and their broader context, detecting complex patterns that humans might not be able to see or absorb. They then continuously learn from applying these patterns to daily practice, augmenting the workplace with ever increasing, automated intelligence. Such a symbiotic relationship between man and machine changes the way we work, get ourselves organized, and do business.

What:

  • Cognitive systems can master the typical human ways of communicating and analyzing through, for example, natural language processing and the ability to recognize images or analyze video footage. These capabilities can enhance existing processes, either by augmenting human work or by replacing parts of it.
  • AI has utilized (unsupervised) deep learning to win games—such as Go—just by observing how it is played and won, without even knowing the rules. The same technology can be applied to processes by learning from the way humans do their work and then providing them with automated, highly intelligent support.

 

Use:

  • A European mobile communications retailer leveraged cognitive technology to radically improve back office processes, leading to a 70% reduction in operating costs and up to 80% improvement in operational efficiency.
  • A trade finance organization digitized and categorized unstructured documentation and extracted relevant data with thousands of complex daily transactions managed by cognitive software and bots.
  • Capgemini Business Services works with Celaton leveraged its inSTREAM AI software to automatically handle incoming structured and unstructured correspondence through a variety of digital channels.

 

Impact:

  • Boosting work productivity and effectiveness through automated decision-making and the availability of real-time predictive insights
  • Improved customer experience by adding human-like, cognitive capabilities to end-to-end processes
  • Mitigating the risks of an aging workforce and dependencies on specialized or scarce knowledge
  • Enable new, previously unthinkable processes to very complex, data- and event-intensive contexts

 

Tech:

Associated experts