AI adoption is growing, but many enterprises still struggle to turn AI into scalable business applications. The whitepaper highlights that 73% of enterprises implemented AI, machine learning, or deep learning in 2022, up from 67% in 2021, while 78% of organizations find it difficult to fill AI data scientist roles. This guide shows how low-code can help businesses build smart apps faster by embedding machine learning models, connecting enterprise systems, reusing AI components, and aligning AI initiatives with business outcomes.
What’s Inside
- The Value of Smart Apps: Why embedded AI and machine learning can create more business value than simple API-based AI services.
- AI Use Cases in the Enterprise: How AI supports service operations, product development, marketing, sales, risk management, forecasting, and automation.
- Smart Apps vs. AI Service Apps: The difference between apps that call external AI services and apps with embedded proprietary machine learning models.
- Challenges of Delivering Smart Apps: Key barriers including AI talent shortages, software engineering gaps, high costs, integration complexity, and governance.
- AI + Low-Code: How low-code helps teams build, integrate, deploy, and reuse machine learning models faster.
- Mendix ML Toolkit: How Mendix supports ML model deployment into low-code applications for practical smart app development.
- Conclusion: Why low-code gives businesses a faster path to real AI value through scalable, business-ready smart applications.
Kyanon Digital is a solution partner with Mendix – a leading low-code development platform in the world. As a Mendix solution partner, Kyanon Digital works hard to ensure this partnership has the goal of accelerating digital transformation for our clients by providing excellent low-code solutions from Mendix. We’re also keen to dramatically boost the development of new apps, enhance the power of pre-built and customized low-code solutions, and expand the business ecosystem.
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