A Double-Edged Sword: Prominent trends within AI consumer applications

Consumer apps, especially mobile ones, are fascinating to observe. They're such an integral part of our everyday lives that it’s hard not to notice certain aspects of their evolution. It's wild to think about the kinds of web and mobile apps we used in the 2000s, where even a simple game like Snake was a huge deal, and accessibility to apps was limited. Of course, it was an amazing time for technology, and using apps on mobile and web devices went through a classic cycle of early innovation. Things changed dramatically when the iPhone and App Store were released, democratizing app development and usage.

When accessibility kicks in and exclusivity goes out the window, it’s always fascinating to see how these apps monetize themselves and how they make money. Over the years, and especially now with the rise of AI, it’s clear that there has been limited pricing innovation. Many web apps still rely on subscription models, but it’s difficult to convince someone to subscribe when there are so many alternatives. There are countless similar apps and games, and they often rely on subscriptions for web-based platforms or monetize through ads on mobile, charging a premium to remove them.

The popularity of free versions for adoption is undeniable, with nearly 70% of AI apps offering some sort of freemium model. The game is still about attracting as many users as possible, getting them hooked, and then monetizing them—that’s the network effect. Even if you think about new monetization strategies or ways to be more transparent, there’s no clear answer. I can only observe and analyze because that’s my acumen. I wish I could suggest or come up with new ideas, but sometimes I just wish I were smarter.

Let's get the broad strokes in first; consumer AI apps are software applications designed for individual end-users, leveraging artificial intelligence to enhance personal experiences in areas such as entertainment, communication, and productivity. AI began integrating into consumer apps in the early 2010s with the advent of virtual assistants like Apple's Siri and Google's Assistant. Since then, AI capabilities have evolved, enabling personalized recommendations, voice recognition, and automated tasks, significantly enhancing the functionality and UX of these apps. These apps have become essential in reshaping user engagement and market dynamics. The GenAI explosion, driven by tools like ChatGPT, has led to a surge in new products across various categories, from virtual companions to productivity tools. 30^th November 2020 shifted the public perception, highlighting AI's role in enhancing productivity and co-creating value, rather than just serving as a source of entertainment or convenience. The domain has evolved, and it will keep evolving, there is hardly any doubt that. However, each one of us has a plethora of apps to choose from and there are replicas of replicas of replicas out there, making it a thrift sale (almost free) for consumers and incredibly hard for companies to make money. 

Some trends that are noticeable or perhaps not would be the following:

• Monetization is still a challenge and will likely remain one amid a nearly perfectly competitive market: Monetizing consumer AI apps is like trying to make fetch happen—it's not as easy as it sounds. Despite the boom in AI-powered tools, most of the top-used apps are generalist chat apps, with ChatGPT being a prime example. But here's the catch: ChatGPT has a gazillion look-alikes popping up faster than you can say "generative AI." It's the classic start-up conundrum: achieve virality, build a massive user base, and then figure out how to make money. But with AI still improving by leaps and bounds, users might just hop to the next shiny (and free) app instead of paying up. How long can start-ups keep playing this user acquisition game before they run out of steam or cash? Even if AI apps dazzle users with their smarts, getting them to open their wallets is a different challenge. Some of the most popular apps based on daily users have obviously raised massive amounts, but we might witness these companies becoming more capital-efficient. For example, Character.ai has close to 9 million active users, whereas ChatGPT has over 100 million, which is huge. Character.ai has raised only $193M as of now, compared to OpenAI raising over $11B, which is commendable.  

• Data commoditization and lower inference costs forcing companies to target high-volume usage consumers: The rapid evolution of AI apps is exciting, but only a few will survive the competitive market driven by declining inference and computing costs. As barriers to entry lower, the market becomes saturated, favoring only the most innovative apps. Success will depend heavily on effective monetization strategies: AI tools must enable users to create or edit content that can be monetized, providing tangible value. This means targeting users who can monetize their usage, like freelancers and small business owners, with tailored offers. The real challenge, however, lies in convincing free users to pay by clearly demonstrating how the app can help them generate income. Effectively communicating the app’s value and potential use cases is crucial, but easier said than done. Convincing users to open their wallets means showing them that the app can significantly enhance their work. It's a tough nut to crack, but the payoff could be huge if done right. Is there a possibility of targeting enterprise customers in the long run for these “consumer” apps? Who knows?

• Mobile experiences are still tough to crack, and most use cases will emerge through integrations into the existing networks and apps: Mobile apps and websites serve distinct consumer needs, with mobile apps focusing on convenience, efficiency, and user engagement, while websites remain pivotal for content creation and information dissemination. A recent survey shows a shift towards mobile apps, with 64% of users favoring them over websites for business interactions, driven by superior user experiences and personalization. However, mobile app development's complexity, including platform-specific challenges and generative AI integration, poses hurdles. Generative AI is reshaping mobile app functionalities, likely offering enhancements in productivity, health, and messaging through predictive analytics and conversational features, although adoption is still early. It’s difficult to imagine extensive use of ChatGPT or Midjourney on the phone because the mental divide is such. As mobile apps evolve, they are integrating AI to enhance their core functions, with health, education, and content editing as key areas, while websites will continue to dominate in areas requiring extensive content creation and editing. The one area in will GenAI is seeing a surgency, is voice assistance companions (talk about virtual friends!).

Who knows where it’s all headed? Sometimes I wonder if it’s as simple as a mega tech company having multiple apps, consolidating them, and offering them for free to gather data and improve their algorithms. It’s like these apps become some form of an experiment—a continuous R&D expenditure on their balance sheets. Or maybe it’s more complicated, with not many companies able to crack the right monetization strategy.

It’s hard to ignore the advancements, though. AI has transformed extremely complicated tasks into fairly simple ones, and it’s becoming more democratized. While that’s great for consumers, it raises the question: Is the trick still to make these apps as viral as possible? And if so, what happens when there’s another paradigm shift? Will even the most useful consumer apps and companies be able to stick around I’ll leave it open-ended because I can’t crack it—it’s beyond me. The hope is to keep asking relevant questions and try to understand it as much as we can. Who knows, who knows? Till then, I'll just keep fine-tuning my school assignments on ChatGPT and feeding in prompts like "suggest me a good title for my blog on consumer apps".

Sources: TechStrong AI, Bryj, LinkedIn, ForEveryScale.com, Andreessen Horowitz