How machine learning and AI are transforming the workplace

artificial intelligence machine learning in the enterprise CSC Blogs

Enterprise success in the digital economy requires levels of speed and flexibility that legacy IT systems simply can’t provide. Fortunately, the emergence of big data analytics, artificial intelligence and automation gives enterprises powerful new tools to improve efficiency and decision-making.

Over at Information Management, contributor Mark Feldner makes the case that “big data and artificial intelligence (AI) stand to become the driving force behind innovation in the workplace.”

“By automating previously manual processes, we have more capabilities to identify patterns in real-time and make predictions that can streamline how we run our businesses,” Feldner says.

He goes on to cite three specific areas where machine learning can make workplaces more efficient, accurate and productive:

  • Customer service and retention
  • Business operations
  • Cybersecurity

The key to making customers happy is to understand and meet their needs. AI in the form of bots that can process natural language are invaluable in obtaining information from customers that can be leveraged to increase customer satisfaction and loyalty.

While automation by itself can improve business processes and workflows, combining it with embedded AI creates a perpetual feedback loop that enables enterprises to make continuous improvements to how the business operates.

Machine learning and AI can rapidly detect patterns in vast amounts of data that could indicate threat attempts and even security breaches. As mobile devices and the Internet of Things continue to invade the enterprise, it is critical that IT is able to monitor and respond to security threats in near real-time.

As with any technologies, machine learning, AI and data analytics should be deployed within the framework of a business strategy or enterprises risk short-changing their return on investment.

Research firm McKinsey writes, “Without strategy as a starting point, machine learning risks becoming a tool buried inside a company’s routine operations: it will provide a useful service, but its long-term value will probably be limited to an endless repetition of ‘cookie cutter’ applications such as models for acquiring, stimulating, and retaining customers.”

Is your enterprise using AI, machine learning and data analytics? And does it have a strategy framework in place?


How to build (and execute) a real data strategy

Creating a virtual service desk agent – a DevOps experiment

Will a robot take my job? Not if I’m creative!



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