The Impact of Artificial Intelligence on Content Production

Blog | 11 Sep, 2017

Artificial intelligence is already changing the game for content marketing and companies whose primary business is content production.


Artificial intelligence (AI) is undoubtedly a hot topic, and sentiment towards this technology ranges from fear to excitement. Here at Jellyfish, we are on the excited part of the spectrum as we believe AI opens new avenues for us to create value. From both a content creation and content dissemination perspective, AI ultimately changes the set of problems companies face—as well as provides a means to solve them as it pertains to content.

AI tools, such as predictive analytics, natural language processing and generation algorithms are already changing how we work. They allow us to get smarter about content production and make it work more effectively. We expect the most impactful changes in how organizations use content for their business objectives to come precisely from such collaboration between human talent and AI.

Machine-generated content is already widely employed by blogs and news aggregators, but it only works in a very specific set of circumstances. First, it requires a structured data set and a clever, detailed template (created by a human) to automate content production. Second, the type of content this approach typically works for is limited to pieces that intend to be informative and accurate, rather than creative or empathetic. This largely depends on the subject matter and content attributes. For example, machine-generated content is often used in business, financial or sports reporting. Finally, to be efficient, the company has to regularly and frequently produce similar types of content to justify investment in AI tools and template development, and have enough data to allow the technology to find and interpret patterns.

If a company primarily creates its own content, AI tools are certainly worth exploring. Natural language generation (NLG) tools can be employed for qualifying content types, such as in the examples above. AI can also be extremely useful during the research stages if the organization is in need of producing complex, involved content. As algorithms become smarter, aggregation and analysis of relevant data during the research stage can save writers an incredible amount of time. Powerful technologies exist that enable us to understand precisely which content resonates with our target audiences, how content we published in the past performed, and provide predictive insights on the topics and placements for the future content.

For companies that heavily rely on curated or user-generated content, AI can be useful to search and evaluate the content quality, gauging audience's appetite for specific topics or understanding a sentiment around the subject.

Given the tremendous advancements in technology and machine learning, AI tools are to become even more mighty in the future. For content strategists and creators here at Jellyfish, this means automation of time-consuming tasks, better insight into user needs, improved targeting and content ROI, and ability to deliver higher quality content to scale.

We are excited about the new opportunities these technologies will open for personalization, such as using predictive analytics to promote and recommend the most relevant content and drive value to our users.

We believe in meaningful, high quality content that is produced in response to a specific business need. With that said, companies need to be careful when focusing on scale alone. Use AI tools wisely—make sure to keep the human element in the equation. No matter how advanced the technology gets, creativity, empathy, tone and interpretation are still a human prerogative.

If you have any content-related questions or inquiries, get in touch—we are always happy to chat.

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