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How AI Can Augment Thought Leadership | Stephanie Grayson | 503

Episode 503 of the Leveraging Thought Leadership podcast, hosted by Thought Leadership Leverage, titled "How AI Can Augment Thought Leadership | Stephanie Grayson | 503" was published on July 16, 2023 and runs 31 minutes.

July 16, 2023 ·31m · Leveraging Thought Leadership

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AI is a powerful tool that is growing at an astonishing rate, but can thought leaders trust the technology? 
Or should a human be keeping an eye on the process - and importantly, the output?

Our guest today is Stephanie Grayson, a Content Marketing Leader and Thought Leadership Advisor with experience in the worlds of agency marketing, large consulting houses, and enterprise scale software.  She is also an AI enthusiast with a creative view on how to best use this remarkable new technology.

We start the conversation by defining the difference between thought leadership and content marketing. Stephanie helps us understand how content marketing focuses on the now, while thought leadership focuses on the future.

Stephanie explains how the current limitations of AI make it unlikely to generate truly new ideas that could be considered genuine thought leadership.  In addition, since AI can only learn from what we give it we have to be careful about introducing bias and be sure to fact check any results it gives to ensure it isn't a very convincing AI hallucination.

So if AI isn't completely trustworthy, how can we best use it?  Stephanie shares AI would be capable of sorting through huge datasets that might be too cost and time prohibitive for people to go through.  From these datasets, the AI could deliver valuable stats and even pose answers to various hypotheses allowing the thought leader to spend more time asking smart questions.


Three Key Takeaways:

*  AI cannot (yet) accomplish the level of thought leadership that gets executive response. Collation is not creation!

*   Great thought leadership should stop you in your tracks for a moment and make you say, "Now that is a unique and interesting #idea."

*   There is a need for more than one set of eyes on large company-level data-backed thought leadership - be it human or AI.  Check your facts, your sources and make sure everything is correct.
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