Main image of article How Will Apple's New A.I. Efforts Impact You?

Apple is reportedly pouring $1 billion per year into generative A.I. research, according to reports. What’s that mean for tech professionals in the iOS and macOS ecosystem?

Apple has built a large language model (LLM) dubbed “Ajax” and a chatbot, according to CNBC, quoting Bloomberg. So far, the company has deployed its A.I. advancements to enhance existing features, including photographs and text messaging. That’s in sharp contrast to rivals Google and Microsoft, which are busily baking A.I. into a variety of user-facing platforms, from productivity software to search.

For a company of Apple’s size, with a market capitalization of $2.7 trillion (give or take a few billion, depending on the day), $1 billion isn’t a lot—but the company could easily increase that spending if it sees progress in its A.I. initiatives. It’s also very possible that Apple’s A.I. work could trickle down to the sea of third-party developers who build apps and services for iOS and macOS.

The nature of those theoretical A.I. services is an open question. Could a platform like Xcode, Apple’s integrated development environment (IDE), adopt auto-debugging or even code generation? Could a chatbot in SwiftUI help novice coders navigate their way through building their first app?

Whether or not you work within Apple’s ecosystem, A.I. could change coding in significant ways over the next decade and beyond. A new report from consulting firm McKinsey, Technology Trends Outlook 2023, suggests A.I. and machine learning will power your workflow in some of the following ways:
 

  • Low- and no-code platforms: Microsoft Power Apps and other platforms could make it simpler for all employees to build limited-function applications.
     
  • Infrastructure-as-Code: In the consulting firm’s words: “This is the process of configuring infrastructure, such as a data center, with machine readable code, which enables rapid reconfiguration and version control. The cloud, for example, is infrastructure that is fully abstracted as code.”
     
  • A.I.-generated code and A.I.-based testing: Chatbots such as ChatGPT and Code Llama can already generate and debug code; these platforms will only become more sophisticated over the next several years.
     
  • Microservices and APIs: Microservices and APIs will likewise continue to evolve, especially given how software engineers and developers use them as the building blocks for complex services.
     
  • Automated code review: A.I. will assist human users in code review.

As companies like Microsoft, Google and Apple invest more in A.I. tools, we’ll likely see the pace of automation increase. How that will impact your workflows—and your job—remains to be seen.