Industries are focusing more on choosing Artificial Intelligence thanks in part to its exponential benefits. With expectations on the return of new products, a significant competitive advantage, or increased customer segmentation and proximity, it’s no wonder AI is exploding, and so too is its wingman, APIs.
AI and API connection
Artificial Intelligence and your APIs may be living separate lives. It’s extremely common for AI to be the focus of a given group, but often the charter is to explore business problems in a mostly non-real time situation in a lab. For insights from AI to be realized, however, they require action and that’s where APIs come in.
Why do you need to unleash it?
The reason you would want to unleash AI with APIs is that if all the investments in AI and data science stay in the lab, then the investment is lost. This brings about a huge detriment to the business.
By unleashing an agile API-first program and leveraging your AI findings and algorithms, you can bring to life new customer experiences like voice-assisted systems and richer applications that are more personalized and yield greater customer interaction and hence loyalty. Think Siri, Alexa, Tesla’s entire in-car experience, and even today’s shopping experience that replaces an out of stock item with a comparable one to make customer’s happy, this is the value and experience customers expect.
Benefits for your enterprise
With a strong investment in AI, many benefits can be monetized in forms of new products, new services, data services and even enhanced customer service. AI can be utilized in retooling the business to eliminate processes and platforms that slow down decision making. Read how APIs and AI can be complementary.
Furthermore, APIs that unlock your AI, can be utilized to sequence or choreograph the interaction of your platforms and engagement with customers while providing a more comprehensive solution that saves time, money and creates better value for the company.
Making it happen
To get things in motion, the best approach is to intentionally combine or connect teams that sit in an incubation or innovation group with the application development and API teams. Press these teams to explore how and where AI can be mapped into existing apps, products and experiences as well as to new services being imagined.
Remember, AI and Machine Learning can be encapsulated to work within your product, so don’t constrain your ideas to only cloud-native AI that always requires a backend connection.
One example of introducing APIs to AI through trial and error is in the insurance business. It’s extremely common for firms to evaluate their actuarial content over long periods to harden the data set in support of making high probability recommendations. AI can help shorten this window of time, but if this research is leveraging AI and machine learning buried deep in an Excel macro, how does it actively help the business? This is where introducing APIs can enhance the process and platform, becoming a bridge to enable real-time decision-making scenarios that involve pricing engines and identifying new customer patterns that can be driven by AI learning and executed by APIs. Read how API Design and ecosystems drive the insurance industry.
The reality is that APIs are building momentum. A simple failure to connect the dots is where companies will go off-kilter. By linking these concepts and teams, companies will get ahead of the curve.
Are you still skeptical about AI and machine learning? It’s time to believe.