Top growth areas for developers in 2025
Monday, January 13, 2025
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Freeman Lightner |
Dr. Marlene Wolfgruber of ABBYY highlights the top growth areas for developers in 2025, including explainable AI, ethical AI design, and multimodal AI. Mastering tools like SHAP and CLIP will help developers meet transparency needs, ethical standards, and data innovation goals.
There are many ways artificial intelligence can assist developers today, from helping to streamline the development process by instantly detecting and fixing errors to summarizing code and generating documentation. A recent survey corroborated that 76% of developers are using or planning to use AI coding tools. Respondents cited several benefits for using AI such as increasing productivity (81%), speeding up learning (62%), improving efficiency (58%), and improving accuracy in coding (30%).
Top growth areas for developers in 2025
However, in 2025, developers will need to be fluent in new capabilities. More advanced uses for AI within product development will be needed that foster transparency, incorporate ethical standards and advance skills.
One growth area is explainability and interpretability in AI via explainable AI (XAI) frameworks. Familiarity with tools like LIME, SHAP, and Explainable Boosted Machines (EBMs) will help developers build models that offer transparency for end-users, regulators, and stakeholders. Regulations and compliance standards for AI are continuously emerging globally. Explainability will be a critical skill as industries increasingly require interpretable AI solutions for compliance and trust-building.
Ethical AI design will become more of a priority as 66% of survey respondents claim a distrust of the output of AI tools. To overcome this, developers should study ethical principles and best practices, as they will be expected to consider factors like fairness, transparency, and bias mitigation from the ground up in the AI development lifecycle.
Another focus in 2025 is advancing their skills in multimodal AI. When working with multimodal datasets, devs need to understand how to handle, process, and train AI models on multimodal data. This includes the ability to combine text, image, and audio to open new possibilities in fields like healthcare, customer service, and manufacturing. In healthcare specifically, diagnosing and treating a patient requires a holistic approach consisting of listening to the patient, reviewing their health records, examining medical images, and analyzing lab test results. Becoming more familiar with transformer-based architectures for multimodal models will be necessary to understand relationships between different data types.
Much of the data in healthcare includes media imaging, electrophysiological data, and sensory data from medical devices. Developers should familiarize themselves with fusion techniques and multimodal frameworks to create new solutions that generate a unified representation of the input data to provide comprehensive information that results in more valuable outcomes for users.
Working with large language models like RoBERTa and GPTs are evolving to support multimodal inputs. Studying transformer variations that support multimodal data (e.g., CLIP, FLAVA) will prepare developers to build robust, context-aware applications.
Upskilling in ethical and human-centered AI design is becoming an essential competency for developers. Staying current on AI ethics and responsibility frameworks is crucial for designing systems that support human decision-making, promote positive user experiences, and comply with emerging guidelines and regulations. By proactively adopting best practices in ethical AI, developers can help create applications that are not only trustworthy and collaborative but also sustainable and future-proof.
About Dr. Marlene Wolfgruber
Dr. Marlene Wolfgruber leads Product Marketing for AI at ABBYY, bringing over 10 years of leadership experience in product management and marketing. She has deep knowledge in a wide range of topics within the intelligent automation industry, and regularly shares her expertise as an expert in AI and language technologies. In her previous roles, Wolfgruber led efforts to revolutionize AI-powered spend management and empowered businesses to build autonomous assistants with generative AI. Wolfgruber holds a Ph.D. in computational linguistics from Ludwig Maximilian University of Munich, and enjoys reading, exercising, cooking, and spending time with her two children.

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