The availability of AI screenplay coverage services has the potential to reshape how production companies handle script submissions. These services, which use machine learning to analyze screenplays, are able to provide coverage reports in a fraction of the time a human reader would take. While this is a clear benefit, and would enable teams to process significantly higher volumes of screenplays, there are several factors that teams should consider.

Speed & efficiency

AI’s strength in summarizing text makes it highly effective for generating synopses and loglines from uploaded screenplay PDFs. This can significantly streamline the initial stages of script analysis, providing quick, concise story overviews. A logline or synopsis can often be enough for an executive to decide whether they will pick up a screenplay to read. 

Human oversight

Despite AI’s growing capabilities, we believe humans will always need to be involved in the process of screening submissions. While large language models that power AI screenplay coverage services are trained on extensive datasets, they often struggle with understanding the nuances and subtleties that are crucial in scripts. An original concept or narrative structure in a screenplay may be marked down because it does not fit with the types of screenplays that the models have been trained on.

Story relevance & cultural awareness

Screenplay readers bring a crucial awareness of the cultural zeitgeist and collective consciousness to their role, enabling them to identify stories that need to be told. Beyond seeking catharsis, audiences are drawn to narratives that reflect current societal trends and speak to pressing issues. This requires readers to not only engage with the emotional depth of a screenplay but also to discern its relevance and potential impact within the broader cultural context. Their ability to pinpoint stories that resonate with the times and ignite discussions is key.

Voice of the writer

As readers of screenplays, we engage with the world portrayed through the unique voice of the writer. This is an aspect that AI, in its current state, finds challenging to fully comprehend and appreciate – but is essential to spotting talented new voices.

Company fit

Production companies need to identify stories that align with their creative and business objectives. This discernment is another area where the human touch is indispensable, as it involves understanding the market, audience preferences, and the unique brand of the company. 

Training data & bias

The effectiveness of any AI model in screenplay coverage is dependent on the quality of data it’s trained on. If the training data is limited or biased, the model’s analysis will also be constrained. Companies looking at AI coverage services should examine what films have been used to train the underlying models and how this might affect the coverage they receive – for example if the training data contains mostly mainstream movies, or only movies which reached the US market.

While AI’s role in screenplay coverage is growing, it’s still in a nascent stage compared to its use in other areas. The tech is evolving, with several AI coverage services already emerging in the market, including Greenlight Essentials, Prescene AI, Rivet AI, Avail, and Scriptreader AI. While these services offer standalone coverage reports on screenplays, Ovassa’s AI screenplay coverage is embedded into workflows within our platform. You can effortlessly keep track of your incoming screenplay subs, automatically create coverage reports and store all documents securely within our platform. 

The space is evolving fast – as are the models that power these services – so it’s worth keeping tabs on these services and evaluating whether they can help you process your submissions pile more efficiently, in combination with human readers