{"id":26035,"date":"2023-09-12T10:25:12","date_gmt":"2023-09-12T14:25:12","guid":{"rendered":"https:\/\/www.3pillarglobal.com\/?p=26035"},"modified":"2024-08-15T17:24:28","modified_gmt":"2024-08-15T17:24:28","slug":"how-ai-helps-media-companies-overcome-challenges","status":"publish","type":"blog","link":"https:\/\/www.3pillarglobal.com\/insights\/blog\/how-ai-helps-media-companies-overcome-challenges\/","title":{"rendered":"How can AI help media companies overcome their biggest challenges?"},"content":{"rendered":"

Artificial intelligence, or AI,<\/a> has long been part of the cultural conversation, often as a theme for science fiction. However, AI has truly reached a tipping point recently with the accessibility and widespread adoption<\/a> of applications like ChatGPT, Bing, Bard, Midjourney, and DALL-E.<\/p>\n

As these platforms catch on with consumers, many businesses are wondering how they can leverage AI within their strategies.<\/p>\n

Of course, the promise of AI isn\u2019t necessarily new in the media industry. Technology companies have long made use of AI to build out algorithms and other tools<\/a> that can aid media companies in developing products that help grow revenue and sustain a business. What\u2019s changed is that AI has taken a leap, in terms of both overall awareness and capabilities. This creates an opportunity for media companies to apply AI within their businesses in a tangible, transformative manner.<\/p>\n

Let\u2019s dive into the different kinds of AI, and then some ways it can be applied within the wider media industry.<\/p>\n

Understanding AI<\/h2>\n

At this moment, the best way to understand AI\u2019s utility is to think about two different kinds of AI: predictive and generative.<\/p>\n

Predictive AI is a bit more established<\/a>. This is when AI processes large amounts of data to identify trends and predict future outcomes. One example that many of us encounter are the prediction algorithms that provide content recommendations for streaming services.<\/p>\n

Generative AI is when data is used to generate something completely new, whether that\u2019s images, text, audio. Whereas predictive AI needs massive amounts of input (\u201cbig data\u201d), generative AI can deliver an output based on a very simple prompt.<\/p>\n

The buzz around generative AI likely has many in the media industry fearful that it could ultimately come for their jobs. The ability to write articles or scripts gives generative AI the power to potentially upend the media industry, but we won\u2019t get deeply into that here. Instead, let\u2019s look at how AI \u2013 all forms of AI \u2013 can aid media businesses and their employees, rather than replace them.<\/p>\n

Applying AI to media\u2019s big challenges<\/h2>\n

These latest iterations of generative AI tools are incredibly user friendly, making it easy for most media companies to build plug-in products on top of those tools. While these products might be fun for a while, they\u2019re not likely to generate revenue or long-term success.<\/p>\n

The media industry currently faces a wave of challenges <\/a>amid increased competition and divided consumer attention<\/a>. When it comes to applying AI to a business, it helps to start by thinking about these challenges, and then examining if there is an AI application that can help. It helps to look at the long-term goals of a business, and then develop the tools and products that will help bring those goals to fruition.<\/p>\n