What’s the difference
AI First, Native AI, and Enterprise AI
AI (Artificial Intelligence) can mean different technologies to different people.
You will find Native-AI, AI-First, and AI Software. Let us describe the differences, which are more serious than most people think.
1) AI-First
AI-First indicates that a software solution was designed with AI as a design priority in mind. However, AI-First solutions are still developed using conventional software that is coded in a linear, step-by-step process and only uses prompts to an AI LLM, when needed.
Today, AI-first makes little difference, as almost every technology created today starts with AI. Conventional solutions, even when plastered with additional agents, remain conventional software because of their core architecture.
2) Native AI
Native-AI describes a solution that is written in Natural Language, so that intelligence, autonomous actions, decision-making processes, learning, and reasoning are completely controlled and managed by intelligence. The application communicates directly with an AI model without software code in between.
AI agents that are written in Python, a 35-year-old programming language, are NOT native AI. Also, conventional software like ERP, CRM, SCM, etc., are NOT native AI, no matter what is attached to them.
When leveraging the power of agentic AI to its fullest extent in truly intelligent workflows, unpredictable event responses, non-linear processes, uncleansed data management, and adaptive human interactions, Native-AI is a necessity.
Obviously, accessing APIs, databases, and other external systems and devices requires code. That layer, however, is the lowest layer – like the machine room in a ship. Each and every access to those functions is controlled intelligently by unique Promts.
The Intelligence-over-Code Method was the breaktrough for a first Native-AI system.
- Intelligence First Hierarchy
- Superior Process Measurability
- Intelligent Process Capabilities
- Application Scalability
- Rapid Application Design
- Easy Application Maintenance
- Rapid Agent Development
- Fast Agent-to-Agent communication and data exchange
- Future AI readiness
Additional Technological Benefits for developers:
- Standardized Agent-to-Agent Protocols
- Synaptic Agent Connectivity
- Agents builds Agents Methodology
- Agentic Spine navigation
- Transparent Memory Management
Learn more about Intelligence-over-Code here.
3) Enterprise AI
Enterprise AI is profoundly more scalable than any of the today’s tools like Chatbots, Co-Pilots, and Agents. It’s a Native-AI based technology and a Worflow Intelligence Powered approach.
Enterprise AI applications run on top of AI model provider and are either focused on specific verticals or aim as a full scope of enterprose workflow intelligence.
Unlike the general AI tools where everybody can build their own solutions, Enterprise AI provides solutions for hundreds of thousand of users, collaborating in special projects or work across departments and silos. The entire intelligence management is structured and designed to run in an enterprise. Workflows in Sales, Marketing, Product Management, R&D, Innovation, Logistics, Administration, Finance, can seemless interact and exchange based on the corporate specific rulings. You can learn more about Enterprise AI here.
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