liveBook · Manning

Onboarding

As explained in The Art of AI Product Development

Onboarding is the initial process of introducing users to a product’s capabilities, benefits, limitations, and basic operation.

An AI product can impress a new user and still lose their trust if its behavior does not match what they expected. Onboarding establishes a useful first mental model: what the product helps with, where it falls short, and how to begin using it. Focus on what matters to early interactions rather than explaining every technical detail. section 10.2.2

A practical first-use message answers five questions:

Set expectations before the first report

An AI assistant for sustainability reporting can analyze company data and draft report text. Its onboarding should also say that it cannot produce visuals, charts, or tables and that users will need to edit much of the text. When an output has low confidence, users can add information or corrections. That gives them a concrete way to work with the system without mistaking a draft for a finished report. section 10.2.2

Choose a format that fits the users and the effort needed to get started. In-app tutorials can guide first steps; tailored guides and hands-on workshops can address a team’s workflow. Onboarding need not carry every lesson: webinars, knowledge hubs, tooltips, and contextual help can support learning after initial use. section 12.3.4

For a consumer product, quick-start guides, in-app tips, and short videos can keep entry simple. In a business rollout, decision makers and daily users may need different explanations: strategic value for one group, effects on everyday tasks for the other. Workshops and a pilot can help both groups see the product in use and provide feedback before a wider rollout. section 12.3.6

Table 12.3 Communication with users and customers in B2B vs. B2C

Aspect

B2B

B2C

Target audience

Customers and users

Users

Onboarding and education

Tailored onboarding for customers and users; ongoing education (everboarding)

Quick-start tutorials, FAQs, in-app tips, and videos; minimal effort required

Communication channels

Demos, workshops, ROI-focused webinars, user training materials

Low-touch; in-app tutorials, automated support, discords, and community building

Adoption approach

Phased rollouts, starting with pilots to show early wins and gather feedback

Beta launches with early adopters; feedback-driven refinement before broader release

Compare B2B and B2C choices for onboarding, communication channels, and adoption before selecting a rollout approach. section 12.3.6

How The Art of AI Product Development covers it

How deep it goes
Provides a five-part messaging framework and concrete education formats, but defers more detailed learning beyond initial use.
Examples
Uses a sustainability-reporting assistant, in-app tutorials, workshops, quick-start guides, and a business pilot.
What it assumes
Assumes an AI product with identifiable capabilities and users; teaches a first-use messaging structure without requiring model mathematics.
What you can do after
Practice/perform onboarding that states benefits and limits, teaches first steps, and fits the audience and rollout.
How it connects
Connects mental models and calibrated expectations with user education, feedback, and phased adoption.

Also explained in

Compare how 3 books explain onboarding →

Related concepts

This explainer was generated by Manning's knowledge graph from the text of The Art of AI Product Development. The section links point to the parts of the book it draws on.