NexTech Academy – Workplace AI Class

Overview

Centered on enterprise AI use and data-driven decisions, the course builds an AI application mindset and transformation framework from market insight and product innovation to marketing and operations. Case analysis, AI tools and planning methods help companies spot where to adopt AI, refine decision flows and organization, and build sustainable competitive advantage and smart operations.

Syllabus

L1 Market trend research and consumer behavior analysis; L2 Turning ideas into products with AI; L3 Automating marketing and sales; L4 A new view of process automation: documents and systems working together; L5 A visual revolution in decisions: real-time AI insight into operations through BI; L6 From data to strategy: how AI guides a company to blue-ocean markets; L7 Smart recruiting: automated candidate screening; L8 Data integration and better decisions: seeing the whole picture of company information; L9 AI-driven organization in practice.

Instructor

鄒昆廷, associate director of digital transformation at 朋昶數位, focuses on digital transformation, AI applications and process-automation analysis; has long helped companies adopt AI and plan transformation, using practical tools and cases to raise operating efficiency and competitiveness.

Who it is for

SME owners; mid- and senior managers and core staff; companies that want to adopt AI tools and refine processes but do not know where to start or keep hitting obstacles.

The adoption problem it addresses

The workplace AI class is for owners of small and medium-sized companies, senior and middle managers, and core staff. It targets a specific predicament: a company wants to bring in AI tools and improve its processes, but does not know where to begin, or has tried and met obstacles. The course starts from the view that AI projects often fail not because the tool is weak, but because the wrong use case was chosen first.

It therefore breaks company work into use cases. Market research, product development, marketing and sales, document and system processes, decision analysis, recruitment and data integration each get a session, so participants can examine which part of their own business deserves attention first.

How the nine sessions are arranged

Session 1 begins with market trends and consumer behaviour, and Session 2 shows how AI can turn an idea into a product. Both look outwards and towards innovation. Session 3 covers marketing and sales automation, and Session 4 covers process automation across documents and systems, which means handing repetitive work to software.

Session 5 uses business intelligence to explain visual decision-making, Session 6 moves from data to strategy and uncontested markets, Session 7 covers smart recruitment, Session 8 deals with data integration across systems, and Session 9 closes with practical sharing on AI-driven organisations. The later sessions shift from single tools to the organisation: whether data is joined up and decisions have evidence.

The nine sessions do not require programming skills. The emphasis is on spotting opportunities and managing adoption, not on building models. Each session uses cases to show how a task changes with AI and automation, and discusses roles and risks before and after, so managers can make informed investment decisions.

What participants should prepare

The class meets once a month from 13:00 to 16:00 at the Soaring Humanities Hall in Zhongzheng District, Taipei, taught by Tsou Kun-ting. Each session lasts about three hours. Participants should choose one concrete task they want AI to handle, such as replying to quotations, answering customer queries or compiling a monthly report, so that cases can be compared directly.

If the company already holds data in an ERP, a CRM or spreadsheets, check the fields and access rights beforehand. Data about customers or staff should have internal approval and be anonymised before it is used in class exercises.

With one session a month, participants have time between classes to test a tool. A small trial is best, such as one department or one process, with time spent and results recorded. Bringing the results to the next session allows a fair comparison and shows the real benefit of a tool.

What participants take away

The course lists four outcomes: an AI adoption strategy and application blueprint, market insight and growth decisions supported by data, gains in product innovation, marketing and operating efficiency, and an AI-literate culture with governance thinking. In practice a company should leave with a prioritised list of AI use cases and a workable path to put them in place.

The instructor, Tsou Kun-ting, is Digital Transformation Associate Director at Pengchang Digital (朋昶數位). He focuses on digital transformation, AI applications and process-automation analysis, and has long helped companies adopt AI and plan transformation strategy, using practical tools and cases.

Link to TINAI resources

The Taiwan Industrial Network of Alliances for Investment (TINAI) was initiated by the National Innovation and Entrepreneurship Association, R.O.C. Once a company has clarified its AI use cases, it can look at the digital alliance page for solution or integration partners, and state the use case, the data position and the expected result on the opportunities page.

The N-Generation series also includes Northern Classes A and B and the Tainan, Kaohsiung and central classes. The workplace AI class concentrates on AI applications and does not cover organisational systems or a full transformation blueprint. A company that needs overall planning may combine it with other classes.