The impact of AI on APIs

The last few years have introduced us to the union of AI and APIs. Both technologies continue to grow and enrich each other in exciting ways. This includes new use cases with the potential to revolutionize how organizations develop, access, and share APIs.

But with these opportunities come new security risks that highlight the need for a robust API management platform that leaves no API unmonitored and unsecured.

APIs enriched with AI

Let’s look first at some of the AI-powered APIs available that bring new automation and efficiency benefits to various industries and use cases.

These APIs leverage AI technologies like computer vision, natural language processing, speech recognition, and more to enhance the functionality and value of applications and services—from predictive maintenance in manufacturing to dynamic pricing for e-commerce and smart document processing for finance.

APIs also leverage AI in many other applications and services that assist businesses and their customers. For example:

• Chatbots: Many businesses use AI-powered chatbots to provide automated customer support and assistance. These chatbots use AI algorithms to understand and respond to user queries, providing quick and accurate information.
• Personalized experiences: AI algorithms can analyze user data and behavior to provide personalized recommendations and experiences. This can be seen in e-commerce platforms that use AI to suggest products based on user preferences and browsing history.
• Data analysis and insights: AI-powered services can analyze large volumes of data and extract valuable insights. This can help businesses make data-driven decisions, identify patterns and trends, and optimize their operations.
• Voice assistants: Voice assistants like Siri, Google Assistant, and Amazon Alexa use AI and natural language processing to understand and respond to voice commands. They can perform tasks, answer questions, and provide information to users.

See also LAM vs LLM: Could LAMs break the API wave?

Smarter, faster API development

In addition, AI can greatly improve the API development process. Traditionally, developing APIs involves manual coding and testing, which can be time-consuming and prone to errors.

AI-powered tools can automate various aspects of API development, such as generating code snippets, detecting errors, and suggesting improvements. These tools can analyze existing codebases, identify patterns, and generate code templates, significantly reducing the time and effort required for API development.

Additionally, AI can assist in API documentation, automatically generating clear and comprehensive documentation based on the API code.

AI can also enhance the usability of APIs. AI algorithms can analyze user behavior, preferences, and feedback to provide personalized API recommendations.

By understanding the specific needs of developers, AI can suggest the most effective APIs for their projects, saving time and effort in searching for the right API.

Furthermore, AI can speed and simplify API development and adoption by using human language rather than complex programming syntax.

Vincent explores several of these AI use cases in more detail in his blog series on the Art of the Possible.

APIs, AI, and security: a double-edged sword

Whether or not you actively pursue these benefits of AI, your API strategy is going to be affected. Generative AI tools like ChatGPT and Gemini are now widely used within and outside businesses to find and combine public information.

It’s only a matter of time before AI is used for criminal purposes with less constrained software engines trained to attack and intrude on other systems.

When it comes to API security, think of AI as a double-edged sword. On one hand, AI is a powerful new weapon in the hands of bad actors. They are using it to plan new kinds of cyberattacks and exploit vulnerabilities in API-driven systems.

On the other hand, businesses are now leveraging API to counter these same threats and add new layers of protection to their APIs and larger digital environments.

Recent examples of AI used in cyberattacks

T-Mobile Data Breach (2023): In this incident, hackers compromised the data of millions of T-Mobile customers.

While the exact cause of the breach is still under investigation, some reports suggest the attackers might have used an AI-powered API that helped them gain unauthorized access.

The AI in the API might have been used to automate tasks like identifying vulnerable points or optimizing attack attempts.

Social media account hijacking: Social media platforms like Instagram have faced issues where attackers potentially used AI to automate large-scale attacks.

The AI could be used to scan for accounts with weak passwords or identify users susceptible to social engineering tactics.

These automated attacks could then be used to hijack accounts and potentially steal user data or spread misinformation.

Strengthening security with AI

While it can be a source of risk, AI can also help identify and mitigate security vulnerabilities in APIs by analyzing patterns and detecting anomalies in API traffic.

AI algorithms can monitor API requests and responses in real-time, identifying any suspicious activities or deviations from normal behavior. This proactive approach enables companies to detect and respond to potential security threats before they cause any harm.

Additionally, AI can automate the process of authentication and access control, ensuring that only authorized users and applications can access the APIs.

AI-powered tools can analyze the sensitivity of API data and automatically apply appropriate security measures, such as data encryption and tokenization, before sharing the APIs with external parties.

Additionally, AI can help monitor and enforce compliance with data privacy regulations, such as the General Data Protection Regulation (GDPR), by automatically identifying and redacting any personally identifiable information (PII) from the API responses.

Dive deeper into API security tools and best practices

Strategies to mitigate AI-related risks

At Axway, we help our customers identify new opportunities that leverage AI, along with the tools and strategies they need to mitigate security risks.

Here are a few recommendations we can offer:

• Discover and map your API landscape to understand your exposure
• Focus on controlled access and exposure to minimize risk
• Plan and perform security audits for AI-generated code
• Train generative AI models on secure data
• Stay informed about new opportunities and security threats

While AI can enhance API security, it’s crucial to have the right platform to keep AI and API systems properly configured, monitored, and maintained to mitigate security risks.

With Axway, you can lean on expert guidance and rely on our Amplify Platform to leverage the full benefits of AI while keeping your APIs secure.

Govern, secure, and monitor APIs on-premises and in multiple clouds from a central location while giving development teams the freedom to use the tools that work best for them without worrying about using unsanctioned solutions.