AI Glossary
The AI terms that matter for business — defined.
Plain-language, one-sentence definitions of the AI certification, integration, and automation concepts behind everything we build.
- AI certification
- An AI certification is a credential that confirms a person can apply artificial intelligence to real work, typically earned by completing coursework and passing an exam.Stronger AI certifications are assessed (not just attended) and verifiable, so an employer can confirm the holder actually earned them.Related: Verifiable credential, AI operator certification
- Verifiable credential
- A verifiable credential is a digital credential whose authenticity anyone can confirm independently — usually via a public page that checks a unique serial and cryptographic signature.Open Badges 3.0 and W3C Verifiable Credentials are common standards; DNAi certificates are verifiable at digitalnetworks.ai/verify with no login.Related: AI certification
- AI operator certification
- An AI operator certification proves a professional can decide where AI belongs in a workflow and deploy it, rather than build models from scratch.It targets operators and career-movers — the people who run the work — instead of ML researchers.Related: AI certification
- AI integration
- AI integration is the work of connecting AI models and tools into a company's existing systems — CRM, ERP, data warehouse — over real APIs so they operate in production.Done well, it augments existing workflows with monitoring and rollback rather than replacing systems wholesale.Related: AI automation, Agentic AI, Retrieval-Augmented Generation (RAG)
- AI automation
- AI automation uses AI to complete repetitive, rules-light tasks end to end — such as triaging tickets, processing documents, or following up with leads — with humans kept on high-stakes decisions.Related: AI integration, Human-in-the-loop
- Agentic AI
- Agentic AI refers to AI systems that can plan and take multi-step actions toward a goal — calling tools, querying data, and making decisions — instead of only answering a single prompt.Related: AI automation, AI integration
- Retrieval-Augmented Generation (RAG)
- RAG is a technique that grounds a language model's answers in your own documents by retrieving relevant passages at query time and feeding them to the model.It reduces hallucination and lets AI cite internal knowledge without retraining the model.Related: AI integration, Large Language Model (LLM)
- Large Language Model (LLM)
- A large language model is an AI model trained on vast text data to understand and generate human language, powering tools like chat assistants, copilots, and agents.Related: Agentic AI, Retrieval-Augmented Generation (RAG)
- Human-in-the-loop
- Human-in-the-loop is a design pattern where AI handles routine work but routes high-stakes or ambiguous cases to a person for judgment and approval.Related: AI automation
- Vendor-neutral AI consulting
- Vendor-neutral AI consulting is advisory work whose recommendations carry no commissions or kickbacks from AI vendors, so the shortlist is chosen only on client fit, security, and total cost.Related: AI integration
From terms to skills
Turn the vocabulary into a credential.
DNAi certifications teach you to apply these concepts — and prove it with a verifiable credential.