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Generative AI training for Chicago teams
In shortGenerative AI training teaches employees how tools like ChatGPT, Copilot, Gemini and Claude produce answers, where they fail, and how to use them safely at work. 312 IT Consulting runs it for Chicago companies before or alongside a tool decision: how the technology works, hallucination and data-leak risks, choosing a tool, a written policy and a staged rollout. Workshops typically start from about $2,500.
Last updated: November 2026 · First call free · Reply within one business day · Part of AI training for Chicago teams
Summarize this 12-page vendor contract. List the auto-renewal terms, termination notice period and anything unusual. Quote the clause numbers.
- Auto-renews yearly unless cancelled 60 days before (cl. 9.2).
- Termination: 90 days' written notice (cl. 14.1).
- Unusual: price can rise 8% a year (cl. 6.4). Check this.
We teach the habit that matters most: verify every clause the AI quotes.
What is generative AI training?
Generative AI training is instruction in the skills that carry across every AI assistant: how the models work, how to give them good input, how to check what comes back and what must stay out. It is tool-agnostic by design, so it still applies after you switch vendors or a product renames its features.
FitCompanies choosing, mixing or rolling out AI tools
- Leadership teams before a purchasewho want to understand the technology before picking a vendor
- Companies with mixed toolsCopilot in finance, ChatGPT in sales, Gemini on a few laptops
- Firms with no AI policy yetand staff already using AI anyway
- Regulated or confidential workaccounting, legal, insurance, healthcare
- Teams already on one toolsee the ChatGPT or Copilot pages for product detail
ChatGPT training and Microsoft 365 Copilot training teach one product’s plans and features. This program spends more time on concepts, risk and decisions. Practice still runs on each person’s own account: ChatGPT (any plan) by default, or Copilot, Claude or Gemini.
How does generative AI work?
A large language model predicts text. Trained on a vast amount of writing, it produces an answer one small chunk at a time, each chunk chosen because it is a likely continuation of what came before. It does not look facts up unless a tool gives it a source to read.
NIST’s Generative AI Profile puts it plainly: these models generate outputs that approximate the statistical distribution of their training data, which can be accurate or can be inaccurate and inconsistent. Fluent writing still has to be checked.
| Term | What it means | Why it matters at work |
|---|---|---|
| Model | The trained system that predicts the next piece of text (GPT, Claude, Gemini and others) | Models differ; the habits work on all of them |
| Token | The unit a model reads and writes: a word, part of a word, a number or a symbol | Limits and usage are counted in tokens, which is why very long inputs get cut or summarized |
| Context window | Everything the model can consider at once: instructions, files, the chat so far and its reply | Long chats drift; a fresh chat with focused input often beats a long one |
| Grounding | Giving the model a source (a file, an email, a web search) to answer from | The single biggest lever for accuracy: ask it to quote the line it used |
| Hallucination | A confident, false answer. NIST calls it confabulation | It reads exactly like a correct answer, so review cannot be skipped |
| Prompt injection | Instructions hidden in a web page, email or file that the model follows as if you wrote them | Matters once a tool can read your inbox, browse or take actions |
What are the risks of generative AI at work?
For small and mid-size companies, mostly two: confident wrong answers that get sent, and confidential data pasted into the wrong account. Training and a policy address both.
| Risk | What it looks like | The habit or control |
|---|---|---|
| Hallucination | Invented citations, wrong figures, a policy clause that doesn’t exist | Ground it in a source, ask for the quoted line, check names, dates and numbers before anything leaves |
| Data leakage | Client files or code pasted into a personal account with training switched on | Business accounts only, a written list of data that never goes in, the right privacy settings |
| Prompt injection | A web page or email that tells an AI tool to ignore your instructions | Limit what connected tools may read and do; a person approves anything sent or booked |
| Bias | Skewed summaries or rankings of people | No AI-driven decisions about hiring, pay or discipline without legal review and notice |
| Over-reliance | Staff stop checking because it was right the last ten times | A review checklist and a named person who signs off |
Hallucination has already cost people
In Mata v. Avianca (S.D.N.Y., June 2023), a federal judge in New York ordered two lawyers and their firm to pay a $5,000 penalty after they filed a brief citing court opinions that ChatGPT had invented. A study by Stanford researchers published in the Journal of Legal Analysis in 2024 found that the models it tested hallucinated on 58% (GPT-4) to 88% (Llama 2) of verifiable questions about federal court cases. A model can invent a source as fluently as it summarizes a real one.
Data leakage is usually an accident
In 2023 Samsung restricted staff use of generative AI on company devices after employees put sensitive code into ChatGPT. They were trying to get help with their work, which is the usual pattern; approved business accounts and clear rules work better than a ban people ignore. OWASP’s Top 10 for large language model applications lists sensitive information disclosure and prompt injection among the leading risks for any company connecting AI to its own data.
How do you choose a generative AI tool for your company?
Start from where your work already lives and what each vendor does with business data. For most small and mid-size firms the shortlist is ChatGPT, Microsoft 365 Copilot, Gemini in Google Workspace and Claude, and on their business plans all four state that customer content is not used to train their models by default.
| Tool (business plan) | Best fit | Business data and model training |
|---|---|---|
| ChatGPT Business or Enterprise | Teams that want a general assistant with shared Projects, whatever email system they use | Excluded from training by default (OpenAI) |
| Microsoft 365 Copilot | Companies whose files, mail and meetings live in Microsoft 365 | Prompts, responses and Microsoft Graph data aren’t used to train foundation models (Microsoft) |
| Gemini in Google Workspace | Companies on Gmail, Drive and Docs | Not used for model training outside your domain without permission (Google) |
| Claude Team or Enterprise | Long documents, careful writing and analysis | Not trained on by default under Anthropic’s commercial terms |
Vendor statements as published in November 2026. Consumer and personal plans of the same products have different defaults; read the current terms for the plan you buy.
Consumer versions differ. Anthropic asks consumer Claude users whether their chats may train its models and keeps that data up to five years if they agree; personal ChatGPT accounts have a similar setting, on by default. Business seats only help if staff stop using personal logins for work.
- List what people already use, including personal accounts, browser extensions and AI features inside tools you already pay for.
- Match the tool to the platform: Microsoft 365 points to Copilot, Google Workspace to Gemini; ChatGPT and Claude work beside either.
- Read the business terms for training, retention, admin controls and where data is processed.
- Pilot with three to five people on two or three real tasks before buying for everyone.
- Pick one primary tool and write it into the policy; allow others only by exception.
For a fuller comparison, read ChatGPT vs Copilot vs Gemini vs Claude for small business.
What should a generative AI policy include?
A usable policy names the approved tools and accounts, lists data that never goes in, says when a person must review output, and states who owns the policy and when it is next reviewed. Two to four pages is enough for most companies.
- Approved tools and plansbusiness accounts only for company work
- Prohibited dataclient confidential files, personal data, credentials, anything under NDA
- Required reviewwho checks what before it is sent, filed or published
- Disclosurewhen clients or customers are told AI was involved
- Employment decisionsno AI in hiring, promotion or discipline without legal review and notice
- Owner and review dateone person, and a date at least once a year
Illinois adds two rules worth knowing. The amended Illinois Human Rights Act, in force since January 1, 2026, bars employers from using AI in ways that discriminate in employment decisions and requires notice when AI is used for them; our Illinois AI employment notice kit covers it. Illinois’s biometric privacy law, BIPA, matters as soon as a tool touches voiceprints, face scans or fingerprints; see Illinois BIPA compliance for small business. Start your draft from the free AI acceptable use policy template.
General information from 312 IT Consulting, not legal advice. Confirm requirements with your employment counsel before relying on it.
How do you roll out generative AI to employees?
In stages: decide the tool and the rules first, train a pilot group, then everyone, and build a shared library of tested prompts as you go. A full rollout typically takes 1–4 weeks. Timelines are estimates and subject to change based on scope.
Discover
A free first call: which tools people use today, which three processes take most of their time, and what data you approve for practice.
Decide
One primary tool and plan, and an interim policy leadership signs before the first session.
Train
Day 1 Foundations for everyone; Day 2 Applied labs on your processes for the roles that will use it most.
Keep
The tested prompts become a shared library with owners, reviewed in a follow-up session a few weeks later.
| Part | What people learn | Tool-agnostic exercise |
|---|---|---|
| Day 1 · How AI works, tokens, context | Prediction, context limits, why answers vary | One question in three fresh chats; compare |
| Day 1 · Prompting and checking | Role, task, source, format, rules; spotting the confident error; privacy settings | Two numbers from fictional notes, both checked |
| Day 1 · Your own material, thinking partner | Answering only from a source; asking AI to argue against an idea | An action-item table with every line quoted |
| Day 2 · Reusable workflows | Saved instructions in whichever form your tool offers | Write once, run three times, fix one rule |
| Day 2 · Three labs on your processes | Your recurring work, tailored to your roles and industry, on fictional data | Review every number before saving |
| Day 2 · Multi-step and scheduled tasks | What a person must approve | A weekly reminder, plan permitting |
For programs across departments and locations, see corporate AI training in Chicago, and for a checklist, what AI training should include. 312's founder has led AI training for more than 1,200 people across four regions, and the before-and-after results live on 312 AI Training.
How much does generative AI training cost?
A 2–3 hour workshop for up to about 15 people typically starts from about $2,500. Anything longer, including policy drafting and rollout support, gets a written quote after a free first call.
Typical price, not a quote. Every engagement gets a written scope and quote before work starts. AI tool subscriptions are bought from the vendor and are not included.
Tailoring to your company is the main price driver. Benchmarks and questions to ask any provider are in what AI training costs in Chicago.
Illinois employers may recover part of the cost through ETIP, which the Chicagoland Chamber of Commerce runs for the region. It pays back up to half of eligible costs if the training is approved in advance, has two or more trainees and, for a workshop, ends in a certificate of completion; ours always does. Read Funding AI training in Illinois before you book.
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Chicago,
IL
On-site generative AI training in Chicago and the suburbs
We come to your office in Chicago (the Loop, Fulton Market, Lincoln Park) and the suburbs: Evanston, Winnetka, Northbrook, Deerfield, Schaumburg, Naperville and Oak Brook. Distributed teams join live online.
Mixed-tool groups are fine: each person brings a laptop signed in to whatever assistant they have.
FAQ
Generative AI training questions, answered.
What is generative AI training?
Training in how AI assistants such as ChatGPT, Copilot, Gemini and Claude produce answers, how to prompt them, how to check their output and what data must stay out. Ours is tool-agnostic and hands-on.
How is generative AI training different from ChatGPT training?
ChatGPT training teaches one product: its plans, settings, Projects and features. Generative AI training teaches the concepts and habits that apply to every tool, plus risk, tool choice, policy and rollout. Companies that have not chosen a tool, or use several, usually start here.
Which AI tool do you use for the exercises?
Your own: ChatGPT (any plan) by default, or Microsoft 365 Copilot, Claude or Gemini. Mixed groups work too.
What are the biggest risks of generative AI for a small business?
Confident wrong answers sent to clients, and confidential data pasted into personal accounts. Training, business accounts and a policy with a review step address both.
Why does generative AI make things up?
Because it predicts likely text instead of looking facts up. NIST describes these errors as confabulation, a natural result of how generative models are designed. Giving the model a source and asking it to quote the line it used is the most reliable fix.
Do we need an AI policy before the training?
A one-page interim policy helps, so the rules in the room match the rules on paper. If you have none, we draft one with leadership as part of a rollout.
Does Illinois regulate how employers use AI?
Yes. Since January 1, 2026 the Illinois Human Rights Act prohibits employers from using AI in ways that discriminate in employment decisions and requires notice when AI is used for decisions such as hiring, promotion or discipline. This is general information, not legal advice; confirm with your employment counsel.
How long does a generative AI rollout take?
A single workshop is 2–3 hours. A full rollout with tool decision, policy, training and a prompt library typically takes 1–4 weeks. Timelines are estimates and subject to change based on scope.
How much does generative AI training cost?
A 2–3 hour workshop for up to about 15 people typically starts from about $2,500. The 1-Day and 2-Day programs and full rollouts are quoted in writing after a free first call; tailoring to your company is the main price driver.
Can Illinois ETIP pay for generative AI training?
Possibly. ETIP, administered in Chicagoland by the Chicagoland Chamber of Commerce, reimburses eligible employers up to 50% of training costs. It requires pre-approval, at least two trainees and, for workshops, a certificate of completion, which every attendee receives.
Sources
- NIST, AI Risk Management Framework: Generative Artificial Intelligence Profile (NIST AI 600-1) (July 2024).
- OWASP GenAI Security Project, Top 10 for LLM Applications (2025), including LLM01 Prompt Injection.
- Dahl, Magesh, Suzgun and Ho, Large Legal Fictions: Profiling Legal Hallucinations in Large Language Models, Journal of Legal Analysis 16, no. 1 (2024).
- LawSites, Court imposes sanctions on lawyers who filed bogus cases after relying on ChatGPT for legal research (June 2023), on Mata v. Avianca.
- CNBC, Samsung bans use of A.I. like ChatGPT for employees after misuse of the chatbot (May 2023).
- Microsoft Learn, Data, privacy, and security for Microsoft Copilot.
- Google Workspace Help, Generative AI in Google Workspace Privacy Hub.
- Anthropic, Updates to Consumer Terms and Privacy Policy.
- OpenAI Help Center, Managing data, sharing, and privacy in ChatGPT Business.
- Chicagoland Chamber of Commerce, ETIP frequently asked questions.
Vendor data-use terms change; confirm the current terms for the plan you buy. Legal and funding details were last reviewed on November 8, 2026.
Book generative AI training for your team.
The first call is free, and we reply within one business day. Tell us which AI tools your people use today, whether you have a policy, and roughly how many people need training.
Book generative AI training (224) 382-4084