A decade ago, artificial intelligence seemed like a future dream. Something impossible to achieve in the next 10-15 years. But two years into the 22nd century, those visions are now a reality. Sure, we don’t have fully sentient computers yet. But, we’ve made tremendous improvements beyond what many would have predicted a few decades ago. Harnessing artificial intelligence in API management will be important for scaling and securing your business.

Of course, with the rapid growth of AI over the years, several companies are quickly incorporating its solutions into their processes. For example, Forbes reported that 83% of companies had increased their budgets for AI solutions since 2019. And of course, most of these companies are in tech-related fields (17% according to O’Reilly’s 2021 AI adoption report).

One of the main areas where you can apply AI’s limitless advantages is improving API capabilities. Interestingly, most primary AI applications you’ll come across, such as self-driving cars, automation, online video calling, and face recognition, are fundamental combinations of AI with APIs. 

But how does it work? How can you combine artificial intelligence with API management for better enterprise solutions? 

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A Little About AI and API

AI is an acronym for Artificial Intelligence, and you can pretty much deduce its definition from its name. However, people have defined AI as many things through the years. In the 80s, when the term started gaining popularity, people recognized AI as a program for developing expert resolution-based systems. 

However, AI has grown and morphed into a more complex system that works on neural networks. Today, artificial intelligence can recognize patterns, analyze them and make predictions. 

API, on the other hand, is an acronym for Application User Interface. It’s a software intermediary that enables two applications to interact. APIs are pathways or gates that allow computer programs to communicate, share information, and execute tasks. 

This definition means you’re leveraging APIs whenever you check social media on your phone, create an ecommerce marketing strategy, send an SMS, or do online video calling.

Typically, you have to input some commands to make APIs execute desired actions. But what if you can have a different program operate and input those commands with minimal effort from your end. That’s where harnessing AI in API management becomes useful.

Common API + AI Enterprise Solution Examples

Here’s a look at some common examples of how AI is changing API management. We’ll also preview what’s to come in the future for artificial intelligence in API management.

AI In API Design

AI and online deep learning techniques are revolutionizing API design processes. Modern AI can function with near-human cognitive accuracy and is much better with quantitative and numerical data analysis. 

Essentially, AI can analyze data packages that are mind-numbing for average humans. By applying this feature to the API design process, AI gives you a strong head-start.

But it doesn’t end there. AI can also help with modeling and documentation, which are fundamental to developing successful APIs. 

Essentially, AI systems take the work out of the menial aspects of API development. Plus, advanced-level AI can help developers write functions for integrating interfaces. 

AI in Augmenting API Security

APIs typically work with sensitive data. The average API is an interface developers use to factorize software modules within enterprise information systems. But, given the sensitivity of the data and the collection procedure, APIs are vulnerable to different forms of cyberattacks. 

However, you can use AI to augment the average API security system by essentially filling up the cracks. AI solutions can analyze security threats and detect malicious elements in a package. 

For example, you can develop machine learning programs to recognize dangers such as:

  • Data Exfiltration.
  • DDos API attacks.
  • Memory Injection.
  • Login DDos.
  • Advanced Persistent Threats (APT).
  • Attacks on Data Integrity.

In addition, AI-based cybersecurity measures can protect APIs through the following methods:

Authentication measures

Authentication measures validate all access to the API based on authorization. In other words, it only allows data access by license from an admin. 

Consequently, no one without due permission from a system authority will be able to use the information on the API database. AI security solutions ascertain relevant authorization using certificates, Web tokens, and Extensible Access Control Markup Language.

Static security checks

AI also detects and prevents intrusion by conducting static security checks on all incoming data and access attempts. This process examines access patterns while simultaneously scanning payloads. 

This scanning step validates all requests and scans for harmful content in API interactions. As a result, AI-based static checks can identify and prevent gateway attacks.

Throttling Capabilities

AI security tools are also applicable for curbing high-volume cyberattacks. That’s because AI systems can dynamically inspect rapidly changing data. This capability enables AI-powered security systems to identify and pick up signals that may spell unauthorized access for intruders. 

In addition, AI tools will also monitor API calls and terminate interactions that may endanger system security. By monitoring and evaluating all network interactions, they cut off the possibilities of data breaches, keeping the systems and users safe.

AI makes all these functionalities possible due to its dual-faceted applicability for blocking attacks. Firstly, artificial intelligence systems are continuously improving by integrating new information from the internet. 

Therefore, you don’t have to constantly review and update its enormous database. Instead, the system can recognize relevant information from the internet, pick it, and adapt to changing environments.

Secondly, artificial intelligence works on solid mathematical models. So, theoretically, it’ll be more efficient and accurate than rules set by humans. To put it simply, if you believe a self-driving car is safer than a human-driven car, then you shouldn’t have a problem accepting this fact about AI augmenting API security.

AI for Managing API Business Flows

The popular belief among developers is that APIs define software programs. Well, that school of thought is accurate to a degree. Most enterprise business services use APIs, so some part or the whole of a company’s operation is based on APIs. 

That’s not surprising, considering API services can span different aspects of the company’s processes. For example, you can apply APIs to creating a phone system for small businesses or running your ecommerce sales strategies. APIs are that versatile. 

Applying the capabilities of API calls and dataflows makes it simpler to cover the entire customer relationship spectrum. And you can finetune the process by leveraging AI to handle dataflows analysis. For example, AI can help you quickly categorize and evaluate customers to predict their future purchasing behavior. 

Such insights will help you develop direct to consumers marketing strategies to maximize your opportunities. Furthermore, you can apply AI to APIs to analyze supply chain events and use the data to optimize stock, reduce/eliminate delivery delays, and prevent order fulfillment issues. 

Analyzing customer behavior can also help determine possible cash flow delays or discrepancies. So you can plan for it and optimize your cash flows accordingly. With deep customer behavior analysis, enterprises can pinpoint why they’re experiencing dropped calls and build improved marketing solutions to improve results. 

Improving Scalability and Efficiency

Continuous artificial intelligence in API management will ultimately improve both systems’ efficiency. AI’s ability to learn and implement its knowledge is a telling characteristic. 

This behavior enables the AI system to predict potential issues and identify solutions before they occur. Developers commonly apply this behavior to image recognition solutions. A staple of electronic signature capture software

The average AI system begins to learn from initialization. Over time, AI systems will get familiar with interfaces and automatically monitor vital metrics to establish patterns. 

The relationship between both elements is symbiotic. But APIs benefit the most from their integration with AI systems. 

From self-correction to higher scalability, APIs will continue to grow tremendously with AI augmentations. And of course, the continued improvements will subsequently give birth to innovative solutions that maximize API capabilities.

Then again, AI can filter through and clean up API interactions and code. This way, it improves the efficiency and accuracy of API managers by preventing bugs.

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About the Author

Grace Lau – Director of Growth Content, Dialpad

This was a guest post submitted by Grace Lau, the Director of Growth Content at Dialpad. If you’re interested in submitting your own guest post, then contact [email protected]. We’re looking forward to your submissions!

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