The drifting changes

The television industry is known as a medium that thrives on storytelling and audience engagement. Emerging technologies such as AI or big data have brought up critical opinions that AI will hurt human creativity and negatively impact the business world leaving creators without jobs. Additionally, some argue that the reliance on AI algorithms and data-driven decision-making could lead to predictable content production, stifling innovation and diminishing the unique human touch. For example, the opposing opinions regarding AI's impact on the television industry peaked in a strike in America. The Writers Guild of America initiated the strike due to concerns from film and TV writers, asking the government to regulate the use of content generated by AI. This strike underscored the growing divide within the industry, with some advocating for strengthening regulations to safeguard against the perceived threat of AI-driven content diluting artistic integrity.

Despite these and similar concerns, several research suggests that AI and Big data, in fact, can improve creativity by providing invaluable insights and tools to content creators within the television industry. For example, one of the ways AI is improving creativity in television is through recommendation systems. According to a study conducted by Tianshi Hao and Xuanyi Chen (2024), Artificial Intelligence Recommender Systems boost user engagement and present creators with fresh possibilities which include simplifying content creation, providing insights for content optimisation, and enabling targeted distribution strategies. Moreover, these systems allow AI to analyse extensive viewer data, including viewing habits, preferences, and feedback. By understanding the patterns in this data, AI can accurately reveal new trends and what audiences like. By using this knowledge, content creators within the television industry can gain a deeper understanding of their audience, allowing them to create content that resonates more effectively. This approach not only increases viewer satisfaction but also creates a stronger connection between the television broadcaster (or the content creator) and their audience.

Research suggests that the way to use AI within the creative industries, including television, is when the human-centric approach is enhanced by technology rather than overruled. For instance, AI-driven content generation tools can assist writers and producers in various ways, from brainstorming ideas to generating scripts. By analyzing extensive datasets and identifying patterns within viewer preferences and trends, AI can suggest potential storylines and themes likely to resonate with audiences. This not only saves time but also provides creators with valuable insights into what content is most likely to capture viewers' interest. It also allows creators to focus on more innovative aspects of content creation, such as concentrating on exploring new narrative techniques or experimenting with different storytelling formats. Furthermore, AI-generated insights can spark inspiration and introduce fresh perspectives that creators might not have considered otherwise. By analysing vast amounts of data, AI can present not-so-obvious connections or trends that can inspire new storylines or themes. This enriches the creative process and enables content creators to explore new storytelling ways and push television's creativity boundaries. As a result, content creators can explore new storytelling avenues and push the boundaries of creativity in television.

Similarly to AI, Big Data analytics has emerged as a powerful tool for understanding audience behaviour and preferences in the television industry. By collecting and analyzing data from various sources, such as social media, streaming platforms, and viewer demographics, television networks can gain valuable insights into their audience's viewing habits and preferences.

Contrary to the argument that Big Data will limit creative expression, research suggests that it can foster greater audience engagement and enable more personalised content experiences. For instance, Big Data analytics empowers content creators within the television industry to tune their programming to meet the specific preferences of distinct audience segments, which results in more precise and relevant content delivery. By using data-driven insights, content creation strategies are improved by a deep understanding of viewer behaviour and preferences. It enables content creators to explore innovative formats, genres, and storytelling techniques that resonate strongly with their audience. This data-driven approach not only enhances audience engagement but also facilitates experimentation and adaptation to evolving viewer tastes, ensuring that television content remains compelling and impactful in an ever-changing media landscape.

Several case studies illustrate how AI and Big Data have facilitated innovation within the television industry. For example, Netflix, a leading streaming platform, has leveraged AI algorithms to recommend personalised content to its subscribers, leading to higher viewer engagement and retention rates. Similarly, Big Data analytics enables TV networks like HBO to analyse vast amounts of data, identifying niche audience segments with unique preferences and behaviours. HBO then tailors targeted marketing campaigns to these segments, delivering personalized messages through various channels to increase viewership and engagement for their shows. This approach enhances viewer satisfaction and loyalty while maximizing the effectiveness of promotional efforts.