As with any complex technology, implementing an AI system requires at least some appetite for risk. Research by GartnerIDC and MIT Sloan Management Review/Boston Consulting Group all find that businesses struggle to generate ROI from their AI projects.

Is this an indication that these projects are fool’s errands? Quite the opposite. Companies are struggling to generate ROI from their AI projects because they have not invested nearly enough in sophisticated AI deployments. This is the assertion made by IPsoft CEO and Founder Chetan Dube in an op-ed for TechSpective. In the post, Chetan urges companies to look beyond single use cases in favor of automated processes for far-reaching business goals.

“Companies are struggling with AI because they are taking half measures, only implementing them in small use cases or in environments where the data is insufficient to power its success,” he writes. “That’s causing their businesses to flounder.”

Chetan references Telefónica, the multinational telecom, and its deployment of digital voice assistants (using Amelia) as call center whisper agents as a prime example of how to use AI to solve a large-scale issue. Telefónica’s intelligent voice assistant fields 4.5 million mobile calls per month, day or night.

“By identifying customer call abandonment as a key issue and tackling the problem with a cognitive AI solution, Telefónica was able to use AI at scale, saving money and improving customer experience in the process,” Chetan writes.

Read the post in its entirety to learn about Chetan’s vision for cognitive AI, intelligent automation and more.

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