App development predictions for 2025 from Kochava

As we approach 2025, app development is rapidly evolving. Technological advancements, changes in user expectations, and emerging global trends are redefining what it means to build, deploy, and use mobile and web applications.

2025 app development predictions from Amro Hassan at Kochava

With groundbreaking advancements in artificial intelligence, connectivity, and privacy, app development is set to reach new heights by 2025. Here are my top predictions for app development in 2025.

1. Artificial intelligence (AI) advancement

Since the release of ChatGPT in late 2022, the number of AI-enabled applications has been growing at an accelerated rate. According to an Information Services Group (ISG) study, enterprises plan to nearly double their number of AI-enabled applications by the end of 2024 . Users will be expecting to interact with their applications using natural language and conversational interfaces, whether by text, gestures, or voice. To tend to this change in user expectations, app developers must acquire expertise in building, deploying, and integrating with Large Language Models (LLM).

Local AI

Many large enterprises are concerned about the security and privacy risks that come with the adoption of third-party generative AI services such as ChatGPT. Companies like Apple, Spotify, and Wells Fargo have banned ChatGPT to avoid leaking customer data or source code . Many companies mitigate those risks by locally deploying open-source LLMs such as Databrick’s Dolly and Meta’s Llama. According to Meta, Llama models’ downloads have increased 10X in 2024 compared to 2023 . We expect this trend to continue into 2025, which requires app developers not only to develop expertise in integration with third-party AI services, but also to be able to build and deploy LLMs locally.

Agentic AI

Agentic AI systems go beyond user interface to perform complex tasks and workflows with minimal user supervision. These systems learn from real-time and predictive analytics, leverage LLMs to orchestrate actions, and reinforcement learning to improve over time. Agentic AI will have many applications, including financial management and automated customer support. With advancements in Agentic AI, users will interact with their applications passively rather than actively. Detecting drifts in data or system state and notifying users when their input is required will be the norm. These changes will simplify user interfaces but place more emphasis on accuracy and quality.

Code generation

In addition to using generative AI to build conversational interfaces, application developers are increasingly adopting generative AI in their workflows to automate coding and increase productivity. Tools like GitHub’s Copilot enable developers to use natural language to generate code. In a study by GitHub, developers who used Copilot completed the task 55% faster than those who didn’t use GitHub Copilot . We expect the adoption of code generation tools to accelerate in 2025, increasing developer efficiency and reducing applications’ time-to-market.

2. Internet of Things (IoT) and connected devices

The past decade has seen a proliferation of internet-connected devices, including gaming consoles, televisions, and wearables. The way users interact with their devices is evolving materially.

Augmented and virtual reality (AR/VR)

In February 2024, Apple released its Vision Pro, and in September 2024, Meta unveiled Orion, its advanced AR glasses. All major online retailers are using AR to engage customers with their products. A  Deloitte Digital and Snap Inc. study found that interacting with products that include AR experiences leads to a 94% higher conversion rate . We expect an accelerated adoption of AR/VR technologies in 2025. App developers will be challenged to build immersive user experiences using an array of interfaces such as hand gestures and voice.

Cross-platform frameworks

With the proliferation of connected devices, application developers are reaching their users through many touchpoints, mediums, and platforms. These frameworks are experiencing increased adoption. Flutter, an open-source cross-platform framework created by Google, is being used by two million developers globally, according to a study conducted by Statista . We expect the increase in adoption to continue in 2025, with more developers aiming to reach users with consistent experience across the web, mobile, and other mediums.

3. Privacy, and ethical data use

The privacy landscape has evolved significantly over the past decade. Since the implementation of GDPR in 2018, a patchwork of state-wide regulations were introduced in the US. Furthermore, various regulations have been introduced to organize data-handling practices in different sectors, including the System and Organization Controls (SOC) in the financial industry and the Health Insurance Portability and Accountability Act (HIPAA) in the healthcare sector. App developers are required to implement several privacy and data-handling practices to ensure the compliance with local, global, and industry regulations.

Privacy-first design

We expect development processes to evolve and adapt with the tightening privacy landscape. Privacy-first design is a set of practices that ensure privacy is considered early in the development process. Data minimization forces developers to limit the data they collect to inputs necessary for the app to function. Furthermore, transparency and user controls are being increasingly introduced to ensure that users are informed of their data points being collected and can control whether their data is collected. Developers are increasingly considering privacy from the initial design phase of their applications to ensure privacy the default setting wherever possible.

Ethical data use

With the rise of generative AI, users and organizations are increasingly concerned about how their data is being used. Regulators are considering defining the laws that govern the training process of AI, and uses of the technology. Federated learning is a distributed machine learning approach that allows models to be trained across multiple decentralized devices or servers holding local data samples, without sharing the data itself. Federated learning will enable developers to build intelligent applications without collecting user data. Differential privacy is a technique used to protect individual privacy in datasets by adding controlled "noise" to the data, enabling insights and analysis without compromising individual identities. Differential privacy will enable developers to analyze data sets for trends, and train model without identifying their users. Adoption of these techniques will increase to build engaging user experience while maintaining the user trust.

As we stand on the brink of 2025, app development is poised to undergo a transformative shift, driven by groundbreaking advancements in AI, immersive technologies, and data privacy practices. This dynamic landscape will challenge developers to expand their technical expertise and embrace new frameworks, creating applications that not only meet evolving user expectations but also set new standards in efficiency, connectivity, and ethical responsibility. As the digital world becomes more integrated into our daily lives, developers hold a pivotal role in shaping the future—building apps that are not just tools but trusted companions in a connected, intelligent, and privacy-conscious world. The journey ahead promises innovation and opportunity, making 2025 a landmark year for those ready to lead in the next era of app development.

About Amro Hassan

Amro Hassan is the VP of Product and Engineering at Kochava, the real-time data solutions company for omnichannel attribution and measurement. He has over 15 years of experience leading product and engineering teams most recently at Amazon.