AI Strategy & Implementation
AI training for employees that turns paid licenses into daily habits
NextGen Code's AI training for employees teaches your team to use AI on their actual work, in the tools you already pay for or are about to buy: ChatGPT Business or Enterprise, Claude, Microsoft 365 Copilot, and Gemini in Google Workspace. It's built for small and mid-sized businesses that want everyone, from the owner to the front desk, using AI productively and safely, not just a few enthusiasts.
This is for you if…
- You pay for ChatGPT, Claude, Copilot, or Gemini seats, and only a handful of people use them more than once a week.
- Some employees use personal AI accounts for work, and you don't know what customer or company data they've shared.
- Your team is anxious about what AI means for their jobs, and nobody has talked about it openly.
- Leadership wants more AI use, but nobody has shown each role what that looks like in their day-to-day work.
- You're rolling out Microsoft 365 Copilot or Gemini and need permissions, policy, and training in place first.
- You don't have a written AI usage policy, or the one you have hasn't been read.
Overview
Leadership briefings, hands-on workshops, playbooks, and a usage policy, so your team uses AI well and safely.
Generic webinars rarely change habits. We start with your roles and workflows, run hands-on workshops where people complete real tasks, and leave behind role-based playbooks, a shared prompt library, and an AI usage policy that says clearly what's allowed. Then we measure adoption and keep reinforcing until the new way of working sticks.
We also take the fear factor seriously. People worry about their jobs, about AI getting things wrong, and about privacy, and those concerns are reasonable. AI can sound confident and still be wrong, so every workshop practices checking its output, and the usage policy spells out which data never goes in. We answer job questions honestly and show where human judgment stays essential.
What you get
Deliverables, not decks.
- 01
Leadership briefing
A 90-minute session for owners and managers on what AI can and can't do today, where it fits your business, which risks to manage, and the decisions only leadership can make.
- 02
Hands-on team workshops
Role-based sessions, on-site in Texas or remote, where each person completes real tasks from their job, such as drafting replies, summarizing documents, analyzing spreadsheets, and checking AI output for errors.
- 03
Role-based playbooks and prompt library
Step-by-step guides for each role's most common tasks, plus a shared library of tested prompts and reusable assistants, such as custom GPTs, Claude Projects, or Gemini Gems.
- 04
AI usage policy
A plain-English policy covering approved tools, what data can and can't go into them, when a person must review output, when to disclose AI use, and who to ask, written for your industry's rules.
- 05
Tool rollout and configuration
Setup of ChatGPT Business or Enterprise, Claude Team or Enterprise, Microsoft 365 Copilot, or Gemini in Google Workspace, including admin settings, data controls, single sign-on where your plan supports it, and a permissions review before licenses go out.
- 06
AI champions program and adoption tracking
A small group of trained internal champions who answer questions and share what works, plus a monthly view of usage by team so you can see where adoption stalls.
How it works
A clear process, start to finish.
- 01Week 1
Discover
Short interviews and a survey to learn each role's work, current AI use, skill level, and concerns, plus a review of your tools, data, and file permissions.
- 02Week 2
Set the guardrails
We draft the AI usage policy, configure tools and data controls, and fix oversharing (files shared more widely than they should be) before anyone gets a new license.
- 03Weeks 2–4
Train
A leadership briefing first, then hands-on workshops by role, each built around real tasks and followed by the matching playbooks and prompt library.
- 04Weeks 4–12
Reinforce and measure
Champions meet regularly, office hours handle questions, and we track usage and time saved, then run follow-up sessions wherever adoption lags.
What we measure
The numbers this moves.
We baseline these before we start and report against them after launch.
Weekly active users
The share of licensed employees using approved AI tools each week, taken from your plan's admin reports. Paid seats that nobody opens are the first thing we target.
Time saved on target tasks
Before-and-after timing on tasks each team chose in its workshop, such as drafting proposals or summarizing calls. Example: 30 minutes a day × 20 people is 10 hours a day returned.
Policy coverage
The share of employees who have read and acknowledged the AI usage policy, and the shift from personal AI accounts to approved, business-grade tools.
Output quality
Spot checks of AI-assisted work for accuracy and tone, so speed doesn't come at the cost of mistakes that reach customers.
Workflows in routine use
The number of playbook workflows teams use every week, plus the automation ideas champions bring to leadership.
In practice
What this looks like in a real business.
Microsoft 365 Copilot rollout
Example: a 60-person firm on Microsoft 365 buys Copilot. Because Copilot can surface any file a user can already open, we review SharePoint, OneDrive, and Teams permissions before licenses go out, then train each department on Copilot in Outlook, Teams, Word, and Excel.
ChatGPT Business for a sales team
Example: a distributor's sales reps learn to prepare for calls, draft quotes and follow-ups, and summarize account history, using shared custom GPTs loaded with product sheets and pricing rules.
Front-desk staff at a medical or dental practice
Example: front-desk staff learn to draft patient messages and summarize insurance policies without putting protected health information into any tool that isn't covered by a HIPAA business associate agreement.
Leadership AI briefing
Example: a family-owned manufacturer's leadership team spends a morning on what AI means for its operations, sees live demos on its own documents, and leaves with three priorities and an owner for each.
AI champions program
Example: a property management company names one champion per office. Champions meet every 2 weeks, share prompts that work, and bring automation ideas to leadership, so adoption keeps growing after the workshops end.
Gemini for an agency on Google Workspace
Example: a marketing agency learns Gemini in Gmail, Docs, and Sheets, plus NotebookLM for research, with clear rules on client confidentiality and on disclosing AI-assisted work.
Tools & platforms we work with
- ChatGPT Business
- ChatGPT Enterprise
- Claude
- Microsoft 365 Copilot
- Microsoft 365 Copilot Chat
- Gemini in Google Workspace
- NotebookLM
- Custom GPTs
- Claude Projects
- Gemini Gems
- Microsoft Copilot Studio
- Microsoft Purview
We're vendor-neutral: we recommend what fits your stack, budget and risk profile — not what pays us a referral fee.
Next step
Let's talk about AI Training.
Bring a problem or a goal. In 30 minutes we'll tell you what's realistic, what it would take, and where AI fits — even if the answer is to start smaller.
FAQ
AI Training: common questions
Still have a question? Ask us directly.
How much does AI training for employees cost?
It depends on format and depth. The main cost drivers are the number of people and roles, how many sessions you need, on-site versus remote delivery, how much custom material we build, such as playbooks, prompt libraries, and a usage policy, whether tool setup is included, and how long we support adoption afterward. A single leadership briefing is a small engagement; a company-wide rollout with champions and measurement is a larger one.
How long does AI training take?
A leadership briefing takes about 90 minutes, and hands-on workshops typically run 2–3 hours per role group. A full program, from discovery and policy through workshops and follow-up, usually spans 4–12 weeks, because new habits need repetition. One-off sessions tend to fade; the follow-up sessions, office hours, and champions are what make the change stick.
Which AI tool should our team use: ChatGPT, Claude, Copilot, or Gemini?
Usually the one that fits the software you already run. If your company lives in Outlook, Teams, and SharePoint, Microsoft 365 Copilot works inside those apps; if you're on Google Workspace, Gemini is built into Gmail, Docs, and Sheets. ChatGPT Business and Claude are strong general-purpose assistants for writing, analysis, and research on any stack. We test the options on your real tasks before you buy, and some teams do best with one primary tool plus a specialist.
Will AI replace our employees?
We're honest about this: AI changes tasks, and some roles will change with them. In a well-run rollout, people spend less time on first drafts, data entry, and searching, and more on customers and judgment calls. Training is how employees stay valuable as tools change. That's why we involve them early, show where human review remains essential, and encourage leaders to say plainly how the time saved will be used.
Is it safe to put company data into ChatGPT or other AI tools?
It depends on the account. Business plans such as ChatGPT Business and Enterprise, Claude Team and Enterprise, Microsoft 365 Copilot, and Gemini in Google Workspace don't use your company data to train models by default, and they give admins control. Free personal accounts may, depending on settings. That's why the usage policy names approved tools and the data that never goes in, such as patient records or passwords. Check each vendor's current terms; this isn't legal advice.
How do you measure whether AI training worked?
With usage data and before-and-after task times, not just a satisfaction survey. Most business AI plans include admin reports that show active users by team. We also time the tasks each group chose to improve, spot-check output quality, and track how many playbook workflows are in routine use. When a team's numbers stall, we run a targeted follow-up session for that team.
What should a company AI usage policy cover?
At minimum: which tools are approved, what data can and can't be entered, when a person must review AI output, when to disclose AI use to customers, how to report a problem, and who owns the policy. Regulated businesses add their own rules, such as HIPAA for patient data, GLBA for financial institutions, and state laws like the Texas Responsible Artificial Intelligence Governance Act, in effect since January 2026. Our free AI policy template is a good starting point; this isn't legal advice.
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