Why companies should avoid using out-of-the-box AI models
No matter what industry you’re in, nearly every organization is becoming an information technology company due to the massive amount of data being gathered about their customers and workforce.
This massive amount of data not only captures the current state of an organization, but implicitly encodes all the decisions an organization makes. Hidden in this information are critical insights that can help form a successful roadmap for the future.
For a company to take action on its organizational data, it needs to know what it has and understand the patterns that make that data valuable for different applications.
Consider this: Based on research from executives at 57 large global companies, 99 percent of respondents said their companies were “trying to move toward a data-driven culture,” but less than 33 percent of respondents felt they had actually gotten there.
Why does that chasm exist?
Some of the primary reasons include:
Lack of access to the right technology
Hesitancy to invest in a process they can’t fully defend
The latter is a crucial factor in dealing with deep learning investments. When organizations don’t own the model that has been tasked with learning from your organization’s actions, it’s difficult to protect key intellectual property and data assets.
The more prevalent AI becomes in our everyday lives, the more critical it will be to know who has access, who benefits from the insights generated, and who retains longterm ownership from your investments.
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