The small but important ways AI can transform an enterprise


Artificial intelligence (AI) and machine learning (ML) are expected to usher in a glorious new era of innovation across multiple industries, including healthcare, finance, retail, manufacturing, and education.

AI will hyper-accelerate the rate of innovation as its algorithmic capabilities and computer-processing power outpace its biological equivalent,” writes Forbes Technology Council member Chad Steelberg. “The solutions to cancer, security and safety all lie within this incredible domain of technology.”

While AI already is finding its way into medical research and treatment (via IBM’s Watson, for example), the most transformative effects of AI are well down the road. But enterprises don’t have to wait for an AI Big Bang event to benefit from this technology. AI technologies are being leveraged today for routine business activities.

As contributor Mary Branscombe notes, “From coaching managers to interact more efficiently, to suggesting the right time to send email messages, to getting value out of information that might otherwise languish on whiteboards, AI-powered tools are boosting business productivity across a variety of industries.”

AI coaching apps for managers “analyze employee survey data, listen to voice cues and evaluate historic performance reports to identify the unique coaching needs of individual users, as well as offer advice and suggest training to address their shortcomings,” explains Sarah Fister Gale in Chief Learning Officer.

In addition to offering input on when to send emails, AI-based email apps can schedule appointments and follow-ups, organize inboxes into sections, customize email app layouts, and more.

AI tools also can help teams be more productive by enabling them to easily create workspaces that are well-organized, thus reducing the amount of time that team members waste searching through threads and conversations for information relevant to their jobs.

Just as enterprises can suffer “death by a thousand cuts” — that is, fail under the weight of multiple and repeatable inefficiencies — so too can they be transformed by a thousand new efficiencies. It doesn’t necessarily take a Big Bang.

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