Artificial intelligence (AI) is not a new topic, but last year it saw an explosion of new use cases and capabilities.
In a somewhat simplified definition, AI is intelligence exhibited by software or machines, and—through machine learning—has the capability to improve itself over time. AI functions in different ways depending on the specific application of the technology, but in general it has some form of sensory input (like a neural net, or even just data mining large data sets) and provides some self-improving output based on that sensory input.
Understanding Intelligent Apps
The underlying components that make up AI today: machine learning, natural language processing (NLP) and deep learning—have existed in an evolving form for many years. Over the past year or so, software application vendors started experimenting with embedding AI into business software applications. This approach of embedding AI capabilities into the workflow of the applications (better referred to as “intelligent applications”) will continue to grow in 2017 and beyond.
Intelligent applications are developing along two distinct functional use cases:
Automating simple routine tasks that take time away from more value add activities.
Provide relevant data to the application user (person or team) that needs it, at the appropriate time and with the proper context.
Both of these approaches take advantage of the rapidly growing mass of structured and unstructured data that can be accessed and used by companies to make better business decisions. These use cases open up opportunities to improve productivity and decision accuracy, as well as employee and customer experience.
The first function, automating simple, routine tasks, is straightforward and relieves users from tasks that distract and consume time, allowing them to focus on higher-value tasks. An example would include virtual assistants that manage schedules, providing the capability to coordinate meetings without user intervention. An AI agent could also perform tasks that require coordination of available data into an output, like a project plan, a resupply order or even a bill of materials.
The second use case, providing decision support to users that need to evaluate large data sets, has many applications across a business operation. Perhaps the simplest example is in medical diagnosis. An intelligent app doesn’t make the diagnosis, but it can sort through massive data sets to look for patterns, potential diseases and treatments. It can manage electronic health records, test data, patient and family history, and genetic information: ordering and contextualizing relevant data to make the physician’s job more manageable.
Real-World Intelligent Application Uses
For sales personnel, intelligent apps could evaluate leads and opportunities, prioritize them, and even apply behavioral models that would predict which opportunities were most likely to close and provide the largest return. An app could also predict what a customer might need next or be more inclined to purchase. Customer service intelligent apps could offer service employees potential solutions based on knowledge of historical data.
Chatbots that interact with people looking for assistance, and mimic the experience of a live chat agent, could free agent time up for more critical issues. The same app could also provide solution recommendations directly to customers in a network or community.
These examples offer some idea of the potential of intelligent applications and the potential for many other use case examples across every business area.
Intelligent apps offer significant business benefits; combined with some of the other key trends, they open up even broader business improvements and potentially a high return on investment. Applying AI to security (intelligent security), internet of things (IoT), and new user interface models—such as augmented reality, virtual reality and conversational systems—in the context of intelligent apps, could provide new and more effective business security models, increase the automation of many activities, and make the apps more user friendly and productive.
Intelligent apps, the next generation of many business systems, are just starting to become widely available. Access and breadth of use of embedded AI should accelerate over the next few years. The potential for removing distracting tasks from workers is compelling. Using intelligent apps to improve interactions with customers could help many businesses, leading to better experiences and potentially increased revenue.
Once employees start experiencing the substantial benefits from intelligent systems using AI, they will drive accelerated development, deployment and adoption, which will in turn push software vendors to find creative new intelligent apps.
Ready to learn more about intelligent applications? Discover how fit into the biggest digital trends of 2018.
Michael is an experienced technology executive with a diverse software background that includes experience as a software company executive and leading a premier marketing research team. Michael is a published author, blogger, photographer, and accomplished public speaker on emerging trends in business software, digital transformation, and customer experience strategies.