Start with one real business task and build reusable AI methods, Skills, and a lightweight personal workspace.
不公開未核實財務、贊助金額、企業個資、未批准方向或成果保證。
Designed for business owners, managers, and core operating teams, this hands-on programme moves from task definition and source preparation to Prompt, Context, Skill, output checking, and workplace adoption.
These images record the August 2026 Guangzhou Nansha class. They illustrate the teaching method and are not a fixed itinerary for every enterprise programme.
View the complete Enterprise AI Training programme on EmpowerWithAI ↗
If the problem sounds familiar, start with a short diagnostic call before choosing a package.
Book an enterprise AI training diagnosisEach stage is designed to leave a decision trail: what was confirmed, why it matters, and how it can be reused by the team after handover.
Confirm participant roles, business goals, and the tasks that should be improved first.
We confirm approvers, existing assets, target markets, and risk boundaries so the work does not begin from taste alone.
Choose a real exercise and confirm available information, privacy boundaries, and review responsibilities.
The research turns references into comparable market position, language gaps, audience signals, and practical opportunities.
Demonstrate, execute, check, and revise a complete task during the class.
Each revision keeps the decision logic visible for internal review, vendor handover, and future content extension.
Review the output, reusable method, limitations, and acceptance standard.
Visual, verbal, website, and social assets are connected by one operating rule instead of drifting separately.
Define the next test and improvement cycle; an optional 90-day practice programme can be scoped separately.
Handover separates ready-to-use files, items requiring human confirmation, and structured versions for backend or AI retrieval.
Content, events, website pages, and social assets are scattered, making it hard to explain the value internally.
A searchable, citable, and handover-ready brand asset system that can extend into pages, reports, events, and business matching.
Every project starts from scratch, with proposals, FAQs, cases, and reports rebuilt manually.
Core messages are turned into an editable content spine that supports backend updates, external communication, and human follow-up.
The team only sees one campaign or one event, without long-term content and decision evidence.
A staged route with deliverables and directional proof that can be reviewed and improved over time.
Each output is designed as a business asset: clear enough for the team, usable by vendors, and structured for website, content and reporting workflows.
Prioritised business tasks based on value, available information, risk, and review requirements.
Clear inputs, instructions, outputs, risks, and checking method for one real task.
A tested method that can be used and improved after the class.
The one-day option builds a working prototype; the two-day option extends it into a role-specific personal AI workspace.
We keep case studies focused on challenge, route and reusable assets, without exposing private client information.
Some institutional or cross-border work cannot be shown publicly. We can prepare relevant anonymized references during the consultation.
We clarify market, audience, language route, approval flow, and existing assets before recommending a service mix.
Pages, FAQ, proposals, reports, case references, and content assets are structured for future updates and internal presentation.
Starbay connects content, events, business matching, and institutional communications across Hong Kong, the GBA, Mainland China, and global Chinese markets.
A fixed package can look simple but often misses the real business context. Pricing depends on scope, urgency, assets, approval flow and confidentiality needs.
For confirming direction, auditing current assets, and deciding what should move first. Fees are provided in writing after scope confirmation.
For defined deliverables such as brand foundation, content engine, event communications, landing pages, or matching projects, with scope confirmed in a proposal.
For teams that need ongoing content, events, social media, SEO/GEO, and cross-border execution, scoped around quarterly goals and operating rhythm.
The programme starts with the team's real work, not a generic tool list. Choose one-day onsite training or a two-day Nansha intensive route, subject to diagnosis and written confirmation.
Outcomes can include an AI opportunity list, one defined task and acceptance standard, a reusable Prompt, Context, or Skill, a lightweight workflow prototype, and a practical next-step plan.
The programme does not promise a complete enterprise automation system in one or two days.
No. Participants work on real role-related tasks and must prepare information, define requirements, run the task, check the result, and document a reusable method.
The one-day option builds a shared method and a lightweight workflow prototype. The two-day option includes that foundation and extends into a role-specific personal AI workspace.
A cohort of 15 to 30 participants is recommended. The final arrangement depends on the venue, exercise design, and facilitator configuration.
No such promise is made. The programme creates testable, reviewable, and improvable working outcomes. Enterprise systems require a separate integration and governance assessment.
Send a short brief through the contact page. We will review the context and suggest a practical next step.
