Why AI and machine learning need to be part of your digital transformation plans
- by 7wData
AI and machine learning promise to not only improve the customer experience, but also change the way companies operate. For this reason, enterprises should consider integrating these technologies into Digital Transformation plans to stay competitive.
By 2019, 40 percent of all digital transformation initiatives will be supported by cognitive/AI capabilities, according to IDC.
"The time for AI has now finally come, because of the technique of deep reasoning connected with the amazing amounts of computer power and data," said Sanjay Srivastava, chief digital officer of Genpact. "We're seeing the impact of that in our personal lives already. The opportunity now is to apply those technologies in the business context."
For example, we can now use AI for account management and customer service systems across industries. "The benefit isn't just the fact that you get productivity, but the fact that you can scale very quickly," Srivastava said.
Gartner predicted that by 2018, 20 percent of business content (such as shareholder reports, legal documents, and press releases) will be authored by machines. And IDC expects that at least 20 percent of all workers will use automated assistance technologies by that year.
Tools like IBM Watson "introduce machine learning to understand what human beings have a hard time seeing in the context of their work," said Brian Solis, principal analyst at Altimeter. "Machine learning will allow companies to see things they wouldn't otherwise, because of the cognitive bias that exists in the relationship between humans and the data they collect."
These tools can help companies learn in ways that accelerate innovation, Solis said. "AI and machine learning will be really helpful tools in companies getting closer to customers and objectives," he said. If you better understand the context of the customer's world, you can better help them accomplish their goals, and base digital transformation efforts on that information. "Use those insights to reverse-engineer new ways to apply AI to create value," Solis said.
Companies can also use AI internally to study productivity and employee engagement. "Employee experience is the next customer experience," Solis said. "A lot of that is gaining insight into ways to introduce operational models they couldn't see before."
While some studies predict that nearly half of today's jobs could be replaced by a robot within 20 years, automation can ultimately aid productivity and digital efforts, according to Marc Cecere, vice president and principal analyst on Forrester's CIO role team.
"Nearly all processes within an IT org will experience some automation," Cecere said. Some of these will be replaced entirely, he said. Tasks such as backups, job scheduling, password resets are all in the process of being automated.
"More insulated from automation are processes like agile development, which requires a high level of creativity, but even higher levels of social interaction and intelligence, as business and IT people need to interact closely to create something new," Cecere said.
AI and machine learning can also help determine which business practices can be automated, Cecere said. "Machine learning, in particular, can be used to rapidly create scenarios of many practices and match them with the data to see which combinations of practices are optimal," he added.
Increased automation is beneficial when it helps the most creative people in a company be more productive, said Andrew Moore, dean of the school of computer science at Carnegie Mellon University.
For example, AI and machine learning could be useful in his job as a dean of a college because he could ask a platform, "Are faculty course evaluations getting better or worse in the past few years?" and have a machine pull that data up automatically.
"It would be nice to get quick insights from your data," Moore said. "It's the same as installing digitization software.
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