Infographic Capture the Power of AI-Enabled Apps at Your Organization
By Insight Editor / 31 Jan 2024 , Updated on 28 Apr 2025 / Topics: Data and AI Modern infrastructure
Learn about AI-enabled apps and what components you need to capture the power of this technology at your organization.
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The power of AI-enabled apps
What are AI-enabled apps?
Applications where a user can interface with AI are AI-enabled apps. Traditionally when we talk about AI, we are referring to static models or technology that is coordinated and interacted with by data scientists. AI-enabled apps bring AI to the fingertips of non-expert end users for a myriad of use cases.
AI-enabled apps are the latest game changer for organizations looking to serve customers better, improve operations and/or capture competitive advantage. This framework can transform the operations of businesses from improving patient care by healthcare organizations to faster, safer production from a manufacturer.
Enabling your app landscape
To build successful AI-enabled applications, there are three major considerations: modern application, the data estate, and the AI stack architecture. When these components work in harmony, organizations can deploy powerful AI-enabled applications.
The considerations for modern applications
Development frameworks: Which development framework makes sense for the goals of this app?
Application architecture approach: Which infrastructure is needed for this application to be set up for success?
Platform architecture: How can we ensure the platform is suited for this use case?
Ops: How will applications be managed and optimized after initial deployment?
Considerations for data estate
Data storage: What storage is suitable for the type and volume of data?
Governance and Ops: How will the data be managed, maintained, and secured?
Data services: How can we make the data more available and resilient?
Business intelligence, AI, ML: How can we leverage the data for powerful insights?
Components of AI stack architecture
- Compute
- Cloud
- AI architecture
- AI platforms, frameworks and algorithms
- Foundational models and fine-tuning
- Gen AIOps
- AI services
- UX
- Security
AI-enabled apps in the real world
Imagine a healthcare company develops a data model for patients with a particular condition and an AI-enabled application for providers to use. A doctor could enter a patient’s symptoms and previous health data and then receive recommendations for their treatment plan. Patients would receive more personalized care and improved experience.
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