- Data Exploration: AI-guided Exploration serves as a pathfinder for insights and storytelling.
- Model Training: Meet demanding modeling expectations with explainability and transparency.
- App Development: Build decision-making Apps designed for a human-centered approach to AI.
Together, these three efforts make AI a powerful tool in not only understanding data but also creating an impactful path forward.
Elevating to AI-powered Apps
Dashboards are designed to summarize, filter, and display your data. Often they’re based on pivot tables and charts, which may show the current state of your business but fall significantly short in anything beyond that. They’re usually meant for a single user persona, limiting their usefulness to the business as a whole, and their static nature makes it difficult to see complex relationships. A dashboard can show you a problem, but it probably can’t illustrate all the drivers behind that problem or guide users toward a solution.
People who are trying to make really complex decisions demand more from their tools.
AI brings more power to your data analysis, and with that power comes understanding and evolution in data exploration. We don’t want AI to remove the human from the process, but we do want it to help us see the story our data is trying to tell. AI can assist in dashboard creation, explain the trends and relationships in data, and do all of that with a conversational interface that is helpful to many types of users.
All that being said, AI alone won’t can’t create the impact that users are looking for. What users need next is a way to derive business actions from that AI-discovered data story.
Find impact with application(s)
AI-powered applications can unlock the opportunities that organizations are missing, bringing action to places where teams only have visibility today.
For example, consider how a traditional predictive maintenance tool tells you “This part is about to fail” or “This maintenance operator is overbooked.” This provides some visibility but it’s not yet an actionable decision. You don’t know what to do about those problems, you just know that they (probably) exist.
Virtualitics has developed an AI-powered application called Integrated Resource Optimization (IRO) that not only answers the question of what is about to happen, it also guides teams on what they can do to mitigate risk and improve uptime.
I know, at first glance it looks like a dashboard. But there are decision-making tools and triggerable actions embedded within this view. With our AI-powered IRO application, decision makers can use the application to determine “How do we respond?” and then optimize maintenance schedules while accounting for resource constraints. They can even simulate the impact of crucial actions before execution, so their decisions are more comprehensively informed.
What makes a great AI-powered application?
AI is certainly prevalent in the market, but not all AI is created equally. To drive value in AI-powered applications, teams need to be looking for some key features:
- Explainable AI that offers prediction explanations and decision-making simulations
- A user interface that can be customized to serve multiple personas from analysts to executives
- Flexibility in data sources and formats that allows apps to access all the essential data
- Options for ad-hoc analysis to drill down into data and apply human expertise along with AI-discovered relationships and communities
- The ability to embed custom events for third-party API integrations so you can take action, right in the app
- A secure environment with controllable user activity and clear data & model governance
All these things are already built into the Virtualitics AI Platform for our users. Whether you’re just starting out with AI apps or you’re building AI-powered apps but need the support of a platform to help you make it to deployment, we have resources to help you get going.
What it takes to develop an AI Application
We know that the process of developing an app isn’t easy. In fact, 80% of projects fail out in the “Exploring Opportunities” phase shown below according to a recent article by Harvard Business Review. Even if you manage to identify the right opportunity and train your model, only 32% of data scientists report that their models are deployed the majority of the time according to Rexer Analytics. Not a great return on investment!
AI-powered apps are becoming more accessible through AI platforms like Virtualitics that create experiences tailored to the critical decisions businesses have to make. The decision boundary between dashboards and AI-powered Apps is shrinking and we think AI-powered apps will become a dominant form of advanced analytics.
The Virtualitics AI Platform delivers AI-powered apps along with the opportunity to develop and deploy your own tailored solutions. Sign up for a demo to learn more.
