Don’t Panic! 6 Technical AI Terms That Sound Intimidating (But Every PM Can Master)

Authored By Sara Gallagher

If you’ve sat through a vendor demo or AI roundtable lately, you’ve probably heard AI jargon tossed around like confetti:

• “We’re piloting an agentic workflow.”
• “This solution uses embeddings and RAG.”
• “Of course, we fine-tuned the model.”

And if you nodded along while quietly Googling later, you’re not alone.

The truth is, most project managers are stuck between two extremes:

• The tips and tricks crowd (“use this prompt to write better emails”)
• The futurist crowd (“AI agents will eliminate middle management by 2030!”)

What’s missing is a practical middle ground: the key technical terms you need to understand, explained in plain language so that you can lead projects confidently in an AI-shaped world.

So let’s demystify the buzz. These six terms are your quick-start glossary for navigating AI with credibility, whether you’re guiding your team, evolving your PMO, vetting vendors, or developing your career.

Buzzword #1: Agentic AI

Simple Definition: Agentic AI refers to AI systems that don’t just respond to prompts; they can take autonomous steps toward a goal, plan, make decisions, and sometimes even execute tasks on your behalf.

A PM Example: You’re running a rollout with many dependencies. An agent can pull status from JIRA/DevOps, draft a portfolio update, and nudge owners whose tasks are slipping without you clicking around.

Why It Matters for PMs and PMOs: The AI most people use today is like a calculator: you ask, it answers. Agents behave more like a junior teammate who can run with a checklist. For PMs and PMOs, the upside is time back for stakeholder strategy and risk thinking. The caution: you’ll still need to set boundaries on what it can touch, when to notify, and what requires human review.

Buzzword #2: Retrieval-Augmented Generation (RAG)

Simple Definition: A method for AI to “look things up” in your own sources (SharePoint, Confluence, tickets) before drafting an answer, ensuring outputs are grounded in your actual content, not just the model’s general knowledge.

A PM Example: Preparing a Quarterly Business Review (QBR)? RAG retrieves relevant docs (past decisions, risks, metrics), summarizes them, and drafts the slide narrative that you can verify.

Why It Matters for PMs and PMOs: Without RAG, an AI tool is like a new hire with no access to systems. It can give you general answers, but without access to your data, they won’t be particularly useful. With RAG, it references your organization’s data, raising accuracy and relevance.

If you’re evaluating a vendor solution that uses RAG, here are the types of questions you should be asking:

• What sources can you retrieve from?
• How do you show citations?
• What access controls are enforced?
• Who approves sources?
• How fresh must the data be?
• What happens when sources contradict each other?

Buzzword #3: Vibe Coding

Simple Definition: Building apps or workflows by describing what you want in plain language. The AI generates the code/logic, so you move from idea to prototype quickly.

A PM Example: You describe: “Create a form for pilot feedback, store responses in a table, and send a weekly summary to the team.” The tool scaffolds the working prototype; IT later hardens it if it goes enterprise-wide.

Why It Matters for PMs and PMOs: This lowers the barrier between “we should try X” and “we tested X.” PMs can prototype simple tools and automations without waiting in long queues. The guardrails: security, scaling, integrations, and governance still need engineering/IT when moving from prototype to production.

Buzzword #4: Custom GPTs

Simple Definition: A tailored version of ChatGPT that you can configure for a specific purpose, with your instructions, tone, and reference materials, requiring no coding.

A PM Example: Imagine you create a Custom GPT that acts like a risk analyzer. You can chat with it to uncover new risks, assess the ones you’ve already logged, update your register, and keep the language consistent across entries. Unlike writing prompts from scratch each time, it remembers your format, asks the right questions, and draws from a standing library of documents (like your charter) so it carries context from chat to chat.

Why It Matters for PMs and PMOs: Custom GPTs don’t replace the PM’s judgment. They strengthen it. Think of them as assistants who help you apply your own playbook more consistently and quickly. For PMs, that means less time stuck on formatting or repetition, and more time thinking critically about risk impact and mitigation. For PMOs, it’s a way to share standards across teams without the need for endless one-off coaching or review cycles.

Buzzword #5: Embeddings

Simple Definition: Embeddings transform words and ideas into coordinates on a map, allowing the AI to determine which concepts are close together and which are far apart. That’s how it can connect “schedule slip” with “late deliverables,” even if the wording is different. You can think of it like neurons in a brain forming connections so the right ideas “fire” together at the right time.

Embeddings are the backbone of many AI capabilities: search, recommendations, classification, and summarization.

A PM Example: Imagine your PMO has a pile of lessons-learned documents. Normally, keyword search is hit-or-miss; you’d only find results that literally match your wording. With embeddings, the AI stores those documents on a “map of meaning.” When you ask, “What risks came up in past ERP projects?” your question is also mapped, and the system retrieves passages about “schedule delays” or “vendor bottlenecks,” even if the exact phrase “ERP risk” never appears.

Why It Matters for PMs and PMOs:

• As a user of AI tools, You’ll understand why search results may feel “fuzzy” but also more insightful than keyword matching. You’ll know the AI can spot conceptual connections, but may also miss nuance or context.
• As a PM implementing AI: You’ll be able to ask sharper vendor questions: What data sources are embedded? How often are they refreshed? How accurate and fair are the retrievals? These choices affect cost, accuracy, and governance.

Buzzword #6: Hallucination

Simple Definition:
When AI produces something that sounds right but is factually incorrect or fabricated.

Real-Life Example:
You ask for a contract summary; the AI confidently invents obligations that aren’t there. Or it cites a study that doesn’t exist.

Why It Matters for PMs and PMOs:
Hallucinations are a significant risk, particularly in stakeholder communications, contracts, and decision-making support. RAG and embeddings reduce risk but don’t eliminate it. Make “verify against source” a habit, require citation as part of your prompt, and make sure to validate all outputs against your own expertise or research. Practical guardrail: define which outputs can be “AI-drafted and shipped after review” (e.g., meeting notes) versus “AI-assisted but must be checked line-by-line” (e.g., contract language).

Why Learn This Now?

Let’s be real: AI isn’t slowing down, and project managers are right in the blast zone. If you don’t know the basics, you’ll struggle to follow vendor pitches, keep up in PMO strategy meetings, or even understand what your own team is trying to pilot.

But here’s the flip side: If you can work your way to intermediate fluency, being able to describe technical terms in business language, you’ll be able to:

• Track the conversation with confidence (no quiet Googling under the table)
• Ask better questions that show you understand how AI really works
• Position yourself as someone execs can trust to help shape smart adoption

Start small: Pick one term this week, use the Prompt Pack to try it in the context of your own project, and bring one insight to your next team meeting. That’s how you build fluency step by step until you’re the person others look to for guidance.

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Want to go deeper? You can download these “try-it-yourself” prompts to help you practice these concepts in a way that’s relevant to your real projects, industry, and experience.

https://thepersimmongroup.com/gain-ai-fluency-practice-pack-for-project-managers/ 

Contributor Bio

Sara Gallagher is President of The Persimmon Group, an award-winning consulting firm that helps PMOs, leaders, and teams execute with speed and discipline. She’s partnered with organizations from Fortune 500s to fast-moving startups to untangle the bottlenecks that derail execution; whether that’s siloed teams, unclear priorities, misaligned governance, or a PMO that’s lost its purpose.

Her experience spans industries including energy, financial services, and manufacturing, and she’s worked with IT PMOs, EPMOs, and even HR PMOs to help them deliver real business value. She also writes Big Dumb Questions, a weekly LinkedIn newsletter exploring the messy, overlooked realities of how work really gets done.

Connect on LinkedIn: Sara Gallagher