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The Power of Two
Generative AI and low-code technologies complement each other, amplifying the pace of innovation beyond conventional methods. Proper integration considering data integrity and security is essential for their meaningful collaboration.
The Growing Demand
Surveyed innovation officers and IT professionals emphasize the value of increased AI and automation embedded in low-code platforms. This integration enables systems to manage tasks, reducing human effort and unlocking a wide range of capabilities.
Closing the Development Gap: AI and Low-Code Convergence
The convergence of AI and low code bridges the development gap. Low-code software enhances accessibility, empowering citizen developers, while generative AI improves organizational efficiency and congruence, leading to faster innovation.
Querying Language Models
Language models in generative AI platforms will revolutionize low-code development. Instead of visual design, users will interact with models through queries, specifying requirements like building an e-commerce shop. Although not fully realized yet, this approach holds promise.
Balancing Governance and Innovation in AI-Powered Low-Code
Successful implementation requires a responsible and ethical AI framework. Transparency, bias testing, and human involvement are critical. Protecting against biases and prioritizing customer empathy ensure fair and relevant outcomes for end users.
Proprietary Data and Closed-Loop Models
Closed-loop models trained with proprietary data present the next wave of generative AI. Transparency remains crucial, but the ability to securely leverage proprietary data can revolutionize generative AI across industries, boosting innovation speed.
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