Training involves goal definitions, historical data, outcome feedback, and supervised fine-tuning with domain-specific knowledge. NiCE Agentic AI uses structured training processes to ensure accurate, safe, and effective autonomous operations.
What are the key steps in training?
Define clear goals: Establish business objectives and measurable outcomes
Leverage historical data: Use past interactions and workflows to inform model learning
Incorporate feedback loops: Continuously refine decisions based on real-world outcomes
Apply supervised fine-tuning: Involve subject-matter experts to guide model improvements
Embed domain knowledge: Tailor AI for industry-specific regulations and workflows
Why is ongoing training important?
AI must adapt to evolving business needs, market conditions, and customer behavior. Regular updates prevent performance degradation and keep automation relevant.
How does NiCE simplify AI training?
NiCE Agentic AI provides tools for easy data integration, human-in-the-loop supervision, and continuous optimization to reduce complexity for enterprises.
How does this create a NiCE world?
In a NiCE world, Agentic AI continuously learns and adapts, ensuring smarter automation that evolves alongside your business.
Create an adaptive world, where AI learns from your goals and delivers better results.
