How to design AI into your applications

AI is in nearly every application nowadays. A frequently cited IDC statistic has 75% of commercial enterprise apps using AI by 2021. And as AI has become more prevalent, the C-suite has taken a bigger role in AI strategies and implementations. In recent industry survey, 71% of respondents said that their company’s AI projects are “owned” by C-level executives.

Yet, even with C-level involvement, many organizations’ efforts with AI are falling short. Leaders often view AI as a plug-and-play technology with immediate returns, and they struggle to take a more holistic approach. For instance, they may focus on discrete business problems, such as improved customer segmentation, rather than big business challenges, like optimizing the entire customer journey.

As developers integrating AI into applications, how can you reconcile the need for immediate returns with bigger picture goals? To design for an AI-infused future, you’ll need to think more broadly than you may have in the past.  

To start, consider a few truths about AI that should shape the way you approach AI design.

You need to think beyond just automation metrics to bring intelligence to products in a way that is truly conscious. We call this approach Conscious Experience Design—a design discipline tailored for a world shaped by artificial intelligence. Conscious Experience Design helps us answer questions for our clients such as:

There are three main principles of “conscious experience design” that will help you integrate AI into your applications in ways that can evolve as user experiences and AI change. I’ll discuss these three principles and steps for implementing them below.

When designing apps with AI, it’s natural to think about what data is needed to increase the machine’s or system’s intelligence. But this focus on data overlooks a fundamental step—understanding and empowering human intelligence. AI is an enabling technology meant to empower and enhance human capability and potential. If we only train the machine and misalign it with the core human needs it becomes a wasted endeavor unlikely to deliver real value. 

The way around this is to begin with people from a research and insight perspective. Before you begin integrating AI into business applications, first seek to understand the expectations and key problems that need to be solved. Explore where and when people could benefit from offloading tasks to automation and how much control and awareness they desire to achieve an effective human-machine collaboration. 

AI is about living systems that are ultimately going to be smart enough to know when, where, and how to engage us. Designing for immersion means that experiences should feel natural. People should be empowered by AI and automation. People should be less hindered, and their interactions should feel frictionless.

To get to this level of immersion, technology on the back end needs to be able to learn from people to become a system that ultimately intuits what people need. And on the front end, designers need to create similarly frictionless interaction. Allow people to speak rather than grab a mouse. Consider immersive experiences that can anticipate and engage in ways that require less effort. 

At the same time, when you engage the senses, you want the system to feel “living” and ”real,” not clinical and machine-like. Think about the “EQ” or emotional intelligence of the system, and the human emotions it will impact and interact with. For instance, voice technologies may have a hard time intuiting emotions that could be gleaned from facial expressions. It is incredibly nuanced to understand what people are thinking and how they are feeling. Many tech leaders understand the concept of multi-modal interaction—the same applies here. Make the system come to the people. Don’t make people have to come to the system.

It’s easy to focus on just a product or a touch point.