Automation NGO

Why Artificial Intelligence and Content is More Than Manual Versus Machine

Why Artificial Intelligence and Content is More Than Manual Versus Machine

The way the () label is tossed around today, you would think machines are taking over the world – to both our detriment and benefit. Reality skews more to the latter. encompasses such a vast universe of applications and has become so pervasive that it is often difficult to discern its presence.

SwissCognitiveBut generally, involves machine algorithms that extract the most useful information from data in order to more efficiently, accurately and often cost-effectively perform a less exciting task traditionally handled by humans. When it comes to and the creation, personalization, and distribution of content, brands are still unnecessarily cautious. At the same time, however, many are waking up to the unquestionable advantages can bring.

More Time for More Meaningful Pursuits

Marketers’ teams spend up to 46 hours per week on manual email segmentation processes such as content selection and proofing in an attempt to personalize content, according to a recent survey we conducted with The Relevancy Group. But if they used machine and eliminated manual processes, 51 percent would instead allocate the time saved to data analysis. What’s more, if they could have the time back, 70% of marketers would reallocate those manual labor hours towards program planning, expansion and strategy. In addition, a recent Pew study found that 40% think if robots and computers did most of the jobs humans currently do, people would do their jobs more meaningful and fulfilling since machines would mostly be doing things that humans find unappealing . In this “manual versus machine” scenario, the choice seems obvious. But 92% of global senior business decision-makers responsible for data and analytics direction are worried about the reputational damage that inappropriate use of analytics could cause for their organization. Businesses want the benefits that digital and automation can deliver, but they don’t always trust the underlying analytics that power those machines .

In an world, where do we fit in?

It’s important to understand that optimizing technology does involve human interpretation and guidance. Many systems have seen major increases in accuracy when they include humans in the loop, either to help label the training data that’s fed into the machine model or helping correct inaccurate predictions once the system goes live. At its best, is bringing us closer to things we truly need and want, as it learns our behaviors and in the case of content, this is critical to personalization. […]

  1. Yana Beranek

    @SwissCognitive Cool

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