AI development is the process of creating an intelligent system that can learn from data and improve over time. This type of learning is facilitated by machine learning algorithms, which are the building blocks of most AI applications. There are a few key types of machine learning algorithms. Supervised learning teaches an algorithm to make predictions or take action based on input-output pairs. It’s similar to teaching a child with examples, and it allows AI systems to develop insights, predict outcomes, or take steps autonomously without the need for step-by-step human instruction.
Generative AI creates new content — text, images, or code — in response to a prompt, like “what time do you close?” Generative AI is becoming essential to professional tools in fields such as marketing, education, customer service, and data analysis. It also automates repetitive tasks, freeing human capital to work on higher impact projects.
The World Economic Forum estimates that AI will create 97 million jobs worldwide by 2025.3 Many of these new roles will be filled by AI developers, who are responsible for integrating machine learning models and developing AI-powered applications for business and consumer needs.
While AI is revolutionizing countless industries, it’s still early days for the technology. There are some concerns about AI bias, cybersecurity risk, and unintended consequences. AI developers must incorporate transparency and explainability into their systems to mitigate these issues and foster public trust in this powerful technology. There are a variety of tools and platforms available that make it easier for developers to build, integrate, and deploy AI into their apps. For example, IBM Watson, Google Cloud AI, and Microsoft Cognitive Services offer ready-made AI capabilities that can be seamlessly integrated into apps.