Technology has been the cornerstone of economic growth around the world for hundreds of years. It has underpinned the last three industrial revolutions and is now the driving factor in today’s Fourth Industrial Revolution — marked by emerging technologies in a variety of fields.
Unsurprisingly, artificial intelligence is one of the key technologies driving this new revolution. As described in the 1950s by the father of modern computer science, Alan Turing, “What we want is a machine that can learn from experience.” His paper, “Computing Machinery and Intelligence,” is the earliest description of neural networks and how computer intelligence should be measured. While the concept of AI isn’t new, we’re only on the cusp of seeing AI drive real business value in the enterprise.
Businesses today are trying to augment and improve their customer, partner and employee experiences by leveraging AI. However, what many have yet to realize is that AI is only as good as the APIs that support it.
For example, we’re seeing the rise of conversational commerce, where consumers can interact with businesses and their services via digital voice assistants such as Alexa and Siri. Two very important things occur here. First, the voice assistant uses AI and machine learning technology — or algorithms that are trained using massive amounts of existing data — to understand voice commands. Second, the voice assistant acts on those commands by calling back-end services with APIs that do the actionable work. This can include getting product information from a database or placing an order with the order management system. APIs truly bring AI to life and, without them, the value of AI models cannot be unlocked for the enterprise.
The AI problem
Many businesses are beginning to deploy AI-based systems. According to Gartner’s recent survey of more than 3,000+ CIOs, 21 percent said they are already piloting AI initiatives or have short-term plans for them. Another 25 percent said they have medium- or long-term plans.
However, many businesses are adopting AI as a point solution to help customers with queries via a chatbot or with making recommendations via an AI and machine learning-based platform. These point solutions don’t have the ability to influence the entire customer journey. The customer journey in today’s digital world is complex, with interactions spanning many different applications, data sources and devices. It is very hard for businesses to unlock and integrate data across all the application silos in their enterprise (e.g. ERP, CRM, mainframes, databases) to create a 360-degree view of the customer.
So, how do businesses go about unlocking these information systems to make AI a reality? The answer is an API strategy. With the ability to securely share data across systems regardless of format or source, APIs become the nervous system of the enterprise. As a result of making appropriate API calls, applications that interact with AI models can now take actionable steps, based on the insights provided by the AI system — or the brain.
How APIs can bring AI to life
The key to building a successful AI-based platform is to invest in delivering consistent APIs that are easily discoverable and consumable by developers across the organization. Fortunately, with the emergence of API marketplaces, software developers don’t have to break a sweat to create everything from scratch. Instead, they can discover and reuse the work done by others internally and externally to accelerate development work.
Additionally, APIs help train the AI system by enabling access to the right information. APIs also provide the ability for AI systems to act across the entire customer journey by enabling a communication channel — the nervous system — with the broader application landscape. By calling appropriate APIs, developers can act on insights provided by the AI system. For example, Alexa or Siri cannot place an order for a customer directly in the back-end ERP system without a bridge. An API can serve as that bridge, as well as be reused for other application interactions to that ERP system down the road.
At their core, APIs are developed to play a specific role — unlocking data from legacy systems, composing data into processes or delivering an experience. By unlocking data that exists in siloed systems, businesses end up democratizing the availability of data across the enterprise. Developers can then choose information sources to train the AI models and connect the AI systems into the enterprise’s broader application network to take action.
Using AI to enhance the customer journey
As AI systems and APIs get leveraged together to build adaptive and actionable platforms, the customer journey changes dramatically. Consider this scenario: A bank offers a mobile app that targets customers looking to buy or sell a home. In the app, customers can simply point at the property they are interested in and immediately rich data comes together via APIs to provide historical information on property sales, nearby listings and market trends. Customers can then interact with an AI-powered digital assistant on the app to start the loan application process, including getting lender approval and mortgage rates. All the data captured from the mobile app can then feed the mortgage origination process to reduce errors and provide a fast and superior experience to the customer.
Businesses haven’t truly realized the full potential of AI systems at a strategic level, where they are building adaptive platforms that truly create differentiated value for their customers. Most organizations are leveraging AI to analyze large volumes of data and generate insights on customer engagement, though it’s not strategic enough. Strategic value can be realized when these AI systems are plugged into the enterprise’s wider application network to drive personalized, 1:1 customer journeys. With an API strategy in place, businesses can start to realize the full potential AI has to offer.
This article originally appeared in Tech Crunch