Welcome to the era of machine learning, the pivotal subsection of AI that lets computers analyze and learn from data. As ML and AI technologies explode into the mainstream, they’ll continue to revolutionize industries across the board. And while the immense potential of ML is still unfolding, we predict a greater impact on some sectors than others.

Innovators, entrepreneurs, marketers, and tech leaders should keep an eye on the following industries, as they’re ideally positioned to benefit from AI and ML integration. 

1. Media & entertainment 

From music and streaming services to film and television production, machine learning's impact on the entertainment industry is undeniable. We’ve seen early adopters win big with dynamic hyper-personalization based on user viewing habits. It’s how YouTube knows to recommend that next video you just have to check out before getting back to work.

Beyond serving as recommendation engines, ML and AI will help media and entertainment brands engage and retain customers. By linking pieces of data with outcomes, such as clicked versus didn’t click, bought versus didn't buy, and watched to the end versus switched videos, algorithms learn and adjust to our personal preferences. The more complete your user profile, the better you can tailor content, features, and promotions to their specific needs.  

If your media brand has yet to integrate AI-powered features, don’t worry. With market revenue projected to surpass $99 billion by 2030, there’s plenty of opportunity to go around. 

2. Ad tech

In the same way ML algorithms can recommend songs or videos that keep users onsite longer, they can predict which ads they’re most likely to react to. ML-driven ad tech platforms meticulously gather data from our online interactions, which advertisers can then use to optimize spending and maximize returns.

Real-time data analysis opens the door for on-the-fly testing and optimization, stretching your ad dollars further. And AI-powered ad tech platforms analyze user data for better audience segmentation and ad timing. For example, you could use ML algorithms to analyze when, where, and how consumers talk about your brand on social media. Then, tailor your media buys to serve ads at times with the highest volume of users.

Best Western leveraged AI-powered ads to target consumers who were actively planning travel during peak holiday weekends. The hotel brand used this information to provide personalized tips and travel inspiration in real-time, resulting in a 48% uptick in visits to their hotel and resort locations. 

3. Online and video gaming  

PC, console, and mobile gaming companies know the winning power of data—and lucky for them, they have a lot of it. Gamers leave behind massive trails of data as they progress through fantasy worlds, interact with digital objects, and complete levels.

By ingesting that data like an insatiable Pac-Man, machine learning helps predict player behavior and preferences, leading to a more personalized gaming experience. This might include adapting gameplay to a player’s skill level and preferences, or even dynamically generating new characters and storylines.

A popular space exploration game called No Man’s Sky features over 18 quintillion planets for players to explore, each with its own distinct flora, fauna, and ecosystems. This limitless range of possible experiences has helped the game increase audience engagement by nearly 6X. And it would never have been possible without machine learning algorithms. 

See how one major gaming brand used ML-powered customer journey analytics and predictive modeling to double revenue and retention.

4. Online sports betting and gambling 

In an industry literally built upon odds and probabilities, AI and machine learning have the potential to transform online gambling in countless ways.

As with other industries, sports betting apps use AI for better CX, hyper-personalization, and audience engagement. By segmenting users based on their preferences, betting behavior, and interests, online betting platforms can deliver personalized offers, promotions, and content tailored to individual users.

In one positive advancement, ML will monitor user behavior for signs of excessive spending or increased risk-taking. By identifying problematic gambling patterns, betting platforms can intervene to protect at-risk users and promote responsible gambling practices.

We’ll also see ML algorithms put to use in detecting fraud or misuse, such as bot-driven activities or account hacking attempts. By preventing fraud, online betting platforms can maintain a secure and trustworthy environment for their users.

The future is already here   

For these and many other industries, the question is not if AI and machine learning can benefit you. It’s how, and how quickly your brand adopts these game-changing technologies. As more companies launch new ML-powered features every day, the gap will grow ever wider for the ones who struggle to embed it into their core business model. 

How is your industry using machine learning today? And what do you look forward to for tomorrow? To learn more about ML-powered decision intelligence for better CX, customer retention, and omnichannel marketing, speak with a Scuba expert today.