Have you ever used ChatGPT to write a social media post or ad copy? Or Adobe Firefly to generate high-quality images? Well then, my friend, you’ve witnessed the power of generative artificial intelligence (AI).
Generative AI creates content from human-sounding text and audio to detailed images and videos, using data and provided instructions. This form of AI has revolutionized many industries, with the mobile app development industry being one of the major beneficiaries.
In fact, the sector using generative AI in apps was valued at $16.87 billion last year and is predicted to grow by 37.6% annually till 2030. This growth is not only fueled by AI technology, but also the wide availability of internet services like Xfinity internet, which makes the real-time user experience possible.
In this article, we’ll take a deep dive into the potential of using generative AI in apps by exploring the aspects below:
Why is the Use of Generative AI in Apps Growing?
The use of generative AI in apps is fueled by the growing demand to deliver superior customer experiences, optimize workflows, and increase productivity and efficiency across multiple industries.
Some of these industries include self-care, finance, entertainment, gaming, and hospitality, to name a few. They look towards generative AI for task automation or personalized content generation.
Generative AI helps deliver these solutions by automating business processes like code generation, UI/UX design, and testing. The technology also helps deliver personalized customer experiences thanks to its ability to analyze user data and offer relevant content and recommendations, like Netflix does.
Netflix is now tapping even further into the power of generative AI for apps by introducing a generative AI-powered search feature as well as a TikTok-type feed. I don’t know about you, but I, for one, can’t wait to see this happen. However, Netflix is not the first major player in the game.
Back in 2023, Microsoft launched Visual ChatGPT, a tool that easily integrates visual foundation models with ChatGPT. This allows users a more intuitive user interface to interact with the AI tool. Both of these tech giants serve as examples proving that the power of generative AI for apps is not a short-term trend; it is the future of customer experiences.
Now that you have an idea of why using generative AI in apps has become crucial, let’s explore the various business functions it can be applied to.
The Business Functions Where Using Generative AI in Apps Helps
Using generative AI in apps opens up a lot of opportunities for businesses. Some of the most significant ones are:
- Automating Coding
Generative AI tools can generate code in a matter of a few minutes, sparing developers a huge amount of time and stress and helping companies improve efficiency and productivity.
These tools can analyze large codebases within seconds and generate customized code, much more efficiently than a human developer. They rely on natural language processing to generate code snippets and complete functions.
Without having to worry about coding, developers can direct their focus toward more important aspects like enhancing the user experience and improving the functionality of the app.
- Creating UI/UX Designs
A great user interface and user experience design are two of the most important considerations in app development today. Generative AI can help companies with both.
Using generative AI can help designers automatically generate parts of the user interface while focusing on user convenience, aesthetic appeal, and app functionality. Using generative AI to handle the user interface design, developers can focus on further improving the user experience through interactive features.
Most companies offer UI/UX design tools or plugins, for example, Figma’s Smart Animate feature. The feature provides designers with automatic animations for user interface components, saving them time.
- Testing Apps
Generative AI-powered tools can help greatly with app testing by simplifying and automating parts of the process using actual customer interaction data.
For example, tools like Appium’s test recorder record customer interactions and create relevant test cases to identify bugs and potential issues. This helps speed up the testing process by removing the time spent on writing test scripts.
By using generative AI tools early on in the app development process, developers can significantly minimize the chances of a poor user experience when launching the final product.
- Enhancing Personalization
Duh, no surprise there. Generative AI tools use a large amount of customer data, so it’s a walk in the park for them to identify and deliver on customer needs and preferences, creating a more personalized in-app experience.
Using generative AI in apps allows them to quickly analyze a customer’s historical data, identify their needs, preferences, and interests, and offer more relevant and tailored product or content options as well as features, and interface functionalities.
This is particularly effective in industries like streaming, where personalization can create a more engaging and immersive experience, as well as e-commerce, where personalization in the form of upsells and cross-sells can drive up sales.
- Real Time Performance Improvements
Using generative AI in apps can improve app performance by analyzing user interactions to identify where they face issues and provide actionable insights in real time. Developers can then perform the required actions accordingly
Additionally, they are also spared the time spent on manually analyzing and adjusting each crucial aspect of app performance. Generative AI can ensure the app functions normally even during increased user demand.
By quickly identifying and notifying developers of functionalities that need improvement, using generative AI in apps can add more efficiency to the performance optimization process.
Overall, using generative AI in apps can streamline and speed up each of the crucial app development processes mentioned above. These qualities have led to the technology’s widespread adoption for various purposes, and I’ll share some real-world examples of the most popular ones.
Real World Applications of Generative AI in Apps
Let’s explore some areas where the power of using generative AI in apps is making waves.
- AI-Powered Productivity Tools
ChatGPT’s rapid response time and accurate information make it a valuable productivity tool powered by generative AI. However, ChatGPT is not the only productivity tool using the technology. Tools like Otter.ai integrate with video communication tools like Zoom and use generative AI to generate transcripts of video meetings, generate and send relevant emails, and follow-ups.
- Voice to Text With AI
Generative AI can be integrated with voice-to-text apps, making the technology highly effective in customer service. It can be used to create robotic agents that manage customer concerns over phone calls or improve the performance of voice-activated apps. It can also be used vice versa to convert text into natural, humanlike audio. Google offers AI solutions like Cloud Speech to Text that allow businesses to do this.
- ChatGPT in Personal Assistants
Many apps now use the power of ChatGPT for their in-built customer service assistants. The technology can easily be integrated into apps, allowing businesses to automate, personalize, and improve their customer service quality using data. It can also be used to expand the knowledge base of both customer care chatbots and employee assistant bots. Leading cloud solutions provider, ServiceNow, uses generative AI for its virtual assistants.
- AI-Enhanced Photo Editing
Most design tools now offer image enhancement and editing features powered by generative AI. These features can be used simply to brainstorm design ideas, resize or reshape images, remove unwanted objects in images, as well as add new elements to images. They also allow the automation of time-intensive parts in the design process, helping designers push creative boundaries. Adobe Photoshop is a good example that offers these features.
- AI in Note-Taking Apps
Using generative AI in note-taking apps can help improve productivity, efficiency, and growth of a business. These tools automatically note down meeting minutes, recap meetings, and even provide actionable insights. Additionally, they allow employees to participate more in meetings without worrying about noting important points, potentially unlocking a new idea or growth strategy. Examples can include Otter.ai and Fireflies.ai.
Generative AI’s ability to automate processes, generate content, and provide actionable feedback offers businesses an edge. However, this implementation can result in certain challenges as well. The next section will explore both in detail.
The Benefits and Challenges of Using Generative AI in Apps
Like all technologies, there are two sides to the coin, and generative AI is no different. As a passionate techie, I’m going to explore the positives first.
The Benefits of Using Generative AI in Apps
- Unlocking Creative Possibilities: Generative AI can automate captivating designs, fuel creativity, and unlock new possibilities when it comes to user interfaces and app features. It provides different design variants, allowing developers to experiment and create designs that resonate better with users.
- Enhancing Efficiency and Productivity: The speed at which generative AI tools can perform tasks allows developers to focus on more important app-related aspects. Both these processes running simultaneously allows more efficiency, productivity, and a quicker final product.
- Personalized Content Generation: By analyzing customer preferences and interactions using data, generative AI can generate and offer relevant content, recommendations, and interactive features. This creates a tailored experience for users, leading to more engagement with the app.
Now, let’s take a look at the dark side of the technology.
The Challenges of Using Generative AI in Apps
- Ensuring Data Quality: Generative AI requires a lot of data to analyze user preferences and deliver personalized solutions. If the data is limited or biased, it could negatively impact the technology’s ability to deliver personalized responses, resulting in a poor user experience and a lack of trust.
- Security and Ethics: The data used by generative AI is sensitive for both businesses and their customers. To save it from cyberattacks, businesses need to consider investing in security solutions. Additionally, ethical practices and policies must be created and implemented to prevent misuse and manipulation and foster transparency and trust.
- Preventing Technical Limitations: Integrating AI into an existing framework can sometimes be challenging. Additionally, generative AI systems may also be unable to handle large apps or rapidly evolving user demands, making scalability, accuracy, and reliability difficult. Businesses must stay ahead of AI trends and use them to improve the performance of their current generative AI system.
- Ensuring Brand Compliance: Generative AI can efficiently generate content; however, the content may not always be compliant with the overall brand image, goals, and user experience requirements. Companies will have to set policies and manual intervention practices as needed to ensure the app meets brand image and user experience guidelines.
Generative AI in Apps – Automating Processes, Reshaping Experiences
The automation power, wide range of benefits, and the rapid implementation of generative AI in apps by major businesses all prove that it is not just a passing trend, but the future standard of business processes and quality app experiences.
However, it goes without saying that the challenges need to be considered and minimized. This can be done by staying one step ahead of AI trends and developments and using them to gather quality data, ethically and securely use data, ensure brand compliance, and overcome technical limitations.
These steps, paired with advancements in generative AI and the growing availability of internet services can allow businesses to deliver more creative, interactive, and personalized user experiences.