6 Trends and Predictions for AI in Video Streaming

On Gartner, where business trends take shape, the top search term has long been “Magic Quadrant”—the consulting company’s famous ranking system. But in January 2023, that changed, and since then, the most-searched tech trend has been “ChatGPT”. This shift underscores how crucial AI has become across all industries, including video streaming.

AI is emerging as a key driver in enhancing viewer experiences, providing new tools and capabilities that are transforming how video is streamed, consumed, and monetized. From live sports broadcasts to on-demand content, the integration of AI into video streaming platforms is no longer a futuristic concept—it’s happening now, reshaping the industry in profound ways.

Today’s viewers expect more than just seamless streaming; they want features that enhance their experience, such as real-time subtitles, personalized recommendations, and dynamic content moderation. AI is at the heart of these innovations, enabling streaming services to offer more sophisticated and user-friendly experiences.

With AI set to push early adopters ahead of the competition, we explore six AI trends that are poised to define the future of video streaming.

Trend #1: AI for Speech Recognition (AI ASR)

Automatic speech recognition, or ASR, is an AI feature that processes human speech into text format. In the world of video streaming, AI ASR can quickly transcribe words spoken within video into text. That text can be used in a variety of ways, including real-time captions, subtitles, overlays, and translation into other languages, which viewers can see in real time on the screen. AI ASR can also be used for offscreen notes, summaries, and key takeaways from live video even while it’s still streaming.

AI ASR offers end viewers three main benefits:

1. Accessibility. Non-hearing video consumers require subtitles to experience video—a task that used to be handled manually in the days of old-fashioned broadcast television. With terabytes of streaming video data created every single day, manual caption creation is no longer an option, and regardless, would be impossible to perform on streaming video. AI ASR automatically makes all video content accessible.
2. Silent scrolling. While social media platforms notoriously refuse to release the exact statistics on how many users “scroll silently,” the industry assumption (and perhaps your own anecdotal experience) is: a lot of them, most of the time. This is why the trend in social media clips has moved toward instant captions and text overlays. AI ASR helps video creators add text to video as it’s produced, keeping engagement high even without sound.
3. Global inclusivity. AI ASR can automatically add captions or transcripts to videos in other languages. This exponentially increases a video’s reach by making it understandable across the world. (Gcore, for instance, supports over 100 languages for instant transcription.)

Future prediction: Speech recognition is already well-established in the market. It will improve quickly over the next few years, giving streaming video companies access to an increasing number of user-friendly features.

Trend #2: Scalable, Real-Time Content Moderation

Content moderation is a profoundly important part of any platform that streams user-generated video, and it’s increasingly powered by AI. It’s important for the customer experience because it removes undesirable video content, but it’s also key for ensuring that streamed video complies with increasingly complicated local, regional, national, and global laws and regulations like the Digital Services Act (DSA), which was enacted in the EU in 2022.

Content moderation has historically been a major challenge for streaming live video companies and social sites that rely on user-generated content. As one Medium writer put it, “On video platforms alone, every minute translates into hundreds of hours of uploaded content, making it extremely challenging for moderators to quickly identify what’s acceptable and what’s not.”

AI makes content moderation easier and much stronger:

• It’s better than humans at identifying objectionable content.
• It’s entirely scalable, so instead of “spot checking” you can scour everything.
• When a new risk factor comes along, you can introduce new parameters.
• Human moderators no longer need to be exposed to distressing content.

The end result is a safer space for end viewers and easier compliance for brands. Considering that social media platforms like Facebook and TikTok employ tens of thousands of human moderators (and these departments or outsourced vendors often make the news for the wrong reasons), AI content moderation is also much more economical for brands, even if they design their own technology from scratch—which is entirely unnecessary, at this point. (Here’s how Gcore can perform content moderation for you.)

Future prediction: AI will become increasingly advanced in understanding context, allowing for nuanced content moderation that can distinguish between content types such as satire, news, and harmful content. Additionally, AI might predict potential legal issues or controversies before content is released.

Trend #3: Predictive Analytics to Elevate Programming

Streaming video companies and social media platforms that host user-generated video can lean into AI to better predict what users will like, dislike, and choose to engage with. By analyzing viewer data and trends, AI technology can predict in advance which types of content will be most successful.

This concept goes far beyond formulaic television, which tends to take a successful program and try to emulate it over and over. With predictive analytics, content makers can probe for more detail about what engages viewers using data and long-term trends. Predictive AI models can find patterns and details that human interpreters might miss simply because they can analyze incredible volumes of data quickly and over time.

Future prediction: As predictive analytics become more precise, video content will become more original, interesting, and innovative. Streaming video companies will be able to custom-tailor content to audience members in more precise and instant ways.

Trend #4: Enhanced Search

With the ability to analyze video content in real time, AI can simplify search by recognizing designated spoken terms, visual objects, and even actions within streaming video. For example, when it comes to educational video streams, the ability to hone in on specific subject matter or granular information is important.

With voice recognition, powered by AI ASR, users can potentially speak their search request rather than having to type it out—ideal for scenarios in which they are passively watching video without the use of a keyboard, and more comfortable for many users in general. Many streaming services already offer this functionality, but it’s still in the process of being honed to work effectively.

Future prediction: Users’ search habits will become more agile and sophisticated as AI-powered search becomes more and more precise. For streaming video companies, AI-enhanced search will mean higher user engagement with content.

Trend #5: Targeted Advertising that Goes Beyond Demographics

Targeted advertising is the economic foundation of social media and is pivotal to broadcasting as well. With AI, targeted advertising gets more accurate—and less intrusive and annoying—so users are more inclined to actually watch it.

With AI analysis of streamed video in real time, brands can deliver targeted ads relevant to what the viewer is watching at that moment. Forget about trying to group users into demographic targets and take best guesses at what will appeal to each group. AI-enabled targeted advertising delivers relevant ad content to specific individuals in the moment, seamlessly slotting them into ad spots with dynamic ad insertion for minimal viewer interruption and maximal impact.

Future prediction: The more targeted the advertising, the better ads perform. This is a definite win for streaming video companies in terms of keeping users engaged while meeting the needs of advertisers.

Trend #6: The Rise of Deepfake Video

Deepfake clips, powered by AI, can digitally recreate actors, de-age characters, or even generate from-scratch digital characters in a lifelike way. This technology is already being used for special effects in movies and series.

But not every AI innovation is entirely culture-positive, and deepfake video is a good example of an AI trend that can be ethically troubling if celebrities or politicians are made out to say and do things that never actually happened.

Future prediction: AI-generated actors may become commonplace, reducing the need for human actors in certain roles. But since this could also lead to ethical debates about the rights of digital avatars and the potential for misuse in spreading misinformation, streaming video companies must think carefully about the ethical implications of deepfakes.

The future of video streaming in an AI world

Applying AI to streaming video helps ensure decency and safety, makes streaming content more widely accessible to people all over the world, enables accurate and efficient predictive analytics about user behavior, enhances search features, and boosts targeted advertising. We’ll certainly see countless more use cases for AI in streaming video arise in the coming years.

Partnering with Gcore gives you access to some of these cutting-edge AI capabilities directly within your video streaming platform, so you don’t have to make the investment yourself. To learn more about how Gcore can support your AI strategies, read about our fully managed AI video services, including AI ASR and Content Moderation.

Get next-gen AI video streaming features today