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tecnovy AI Suite

AI for Product Managers

You review individual AI summaries one draft at a time; errors in user-facing AI features can reach many people at once. Their answers can differ for the same input, cost money each time they run, and need quality standards of their own before they ship. In this training you decide which feature gets AI, for whom and at what risk, and you capture that in a business case, a specification and a measurement plan.
Attendance certificate4.8/5 on ProvenExpert

What this module delivers.

In tecnovy's AI for Product Managers training you decide whether an AI feature belongs in your product, based on a business case with cost per use, measurable quality criteria and a rollout plan your team tracks with metrics.

How the training runs

Method
Case studies and your own product idea with an AI feature
Basis
tecnovy curriculum for product management with AI features
Outcome
tecnovy certificate of participation at 80% attendance, no examination

Dates & booking

Choose a date that fits

No public dates are scheduled yet.

New dates are published regularly. Join the waitlist or plan an in-house course for your team.

Request in-house training

Fit

Who this module is designed for

Typical roles

  • As a product manager or head of product you decide what goes into a product and why.
  • In a business unit, you are responsible for a product that is due to get an AI feature.
  • You have to make the case for a planned AI feature to the people who decide on the budget.

Prerequisites

No prerequisites

You can start right away. What you need: experience in product management. Helpful: a product idea that could use an AI feature.

Consider instead AI for Product Owners For Product Owners in a Scrum Team: AI for discovery, user stories, ordering the Product Backlog and stakeholder updates.

Curriculum

AI for Product Managers Course in Detail

Four parts follow an AI feature through its product life: from the value to customers through the business case and specification to rollout and measurement. The fifth part makes AI a tool for your own product work. Case studies and your product idea run through every part.

01Spotting opportunities

This part works out where AI creates real value for customers in your product.

  • User groups and their problems as the starting point
  • Customer value as the yardstick for an AI feature
  • Choosing an AI feature for your product idea
02Business case

Here you work out whether an AI feature pays its way in your product.

  • Value for users and for the organisation
  • Cost per use: the cost incurred again with every request to the AI
  • Build vs. buy: developing it yourself or buying a ready-made solution
03Specifying AI features

This part turns an AI feature into requirements your development team can plan with.

  • Quality criteria for the AI's answers
  • Evaluation: checking the answers against test cases set in advance
  • Error tolerance: which mistakes the feature can afford
  • Risks and regulatory requirements in the specification
04Rolling out and measuring

Here you plan how an AI feature reaches users and what your team measures it by.

  • A rollout plan for the launch
  • Collecting and analysing user feedback
  • Setting metrics for the AI feature
05AI in day-to-day product management

In the fifth part AI turns from subject to tool: you use it in your own work as a product manager.

  • Discovery with AI: finding out what users need
  • Analysing market and user information with AI
  • Preparing stakeholder communication with AI

Outcome

What you will be able to do afterwards

  1. 01

    You assess where in your product an AI feature would benefit which users.

  2. 02

    You work out the business case for an AI feature from its expected value and its cost per use.

  3. 03

    You weigh up whether your organisation builds an AI feature itself or buys a ready-made solution.

  4. 04

    You set quality criteria for an AI feature's answers and describe how they are checked.

  5. 05

    You define an AI feature's error tolerance: which mistakes it can afford and which it cannot.

  6. 06

    You write risks and regulatory obligations into the specification as requirements.

  7. 07

    You plan the rollout of an AI feature and set its metrics and the channels for user feedback.

  8. 08

    You use AI for discovery, analysis and communication in your own product work.

Offer scope

What is included

Included

  • Business case template for AI featuresYou use it in the training to build the business case for your product idea.

Why tecnovy

What you get on top with us

01

No Slideshow, Hands-On!

Promised: no PowerPoint marathon. We work in groups, tie theory to practice, and you get real project examples from our experienced trainers plus the exchange with like-minded people.

02

Certificate Showroom

Get your certificate of participation and, if you have one, add your exam certificate from E-Learning. Fully automated, beautifully designed. Just for you, only at tecnovy.

03

Flexible Date Change

If you are not able to attend the course, you can rebook your training free of charge up to one week before the start of the training.

04

Attend Twice, Pay Once

You are welcome to attend the training online again within a year as a refresher.

05

Learn from Experts

We always guarantee you the use of didactically and methodically first-class qualified trainers who draw their knowledge from training experience as well as professional practical and project experience.

FAQs

Frequently asked questions

01How do AI features differ from classic features?
An AI feature can give different answers to the same input, and every call incurs a running cost. In the tecnovy AI for Product Managers training you therefore set quality criteria, error tolerance and cost per use before an AI feature is built.
02What goes into the business case for an AI feature?
The business case for an AI feature covers its expected value, its cost per use (the cost incurred again with every request to the AI) and the build vs. buy decision between developing it yourself and buying it in. In the tecnovy AI for Product Managers training you put these parts together for your own product idea.
03Do I need to code for AI for Product Managers?
The business case and specification work in tecnovy's AI for Product Managers training requires product management experience, not coding.
04Do I work on my own product in AI for Product Managers?
Yes, the tecnovy AI for Product Managers training combines case studies with work on your own product idea with an AI feature. Whether you may use real customer or user data in it is decided by your company's rules and the GDPR (General Data Protection Regulation).
05How does AI for Product Managers differ from AI for Product Owners?
The tecnovy AI for Product Managers training takes an AI feature from business case through specification to rollout and measurement. If you are a Product Owner in a Scrum Team, accountable for a Product Backlog and writing its user stories with AI, AI for Product Owners is the better fit.
06How does AI for Product Managers differ from AI for Executives and AI Strategy & Transformation?
The tecnovy AI for Product Managers training stays with one product: which feature gets AI, what it costs and which metrics your team measures it by. AI for Executives and the AI Strategy & Transformation workshop, by contrast, prioritise AI initiatives for the whole organisation.
07Where do I go after AI for Product Managers?
If you want to take the quality measurement of AI applications further on the technical side, continue with the tecnovy AI Evaluation & Observability training. It expects Python skills and experience with applications built on large language models (LLMs).
08What do I receive at the end of AI for Product Managers?
tecnovy confirms your participation in AI for Product Managers with a certificate of participation once you have attended at least 80 percent of the training time. The training ends without an examination and leads to no certification.

What does your training at tecnovy look like?

AI for Product Managers

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