Ai add-on

As explained in The Art of AI Product Development

An AI add-on is an artificial-intelligence capability added to an established product rather than serving as its primary foundation.

An AI add-on adds artificial-intelligence capability to an established product, extending an existing foundation and user base instead of making AI the product’s primary foundation. This brownfield pattern can deliver a quick win, but legacy data, integration, governance, and infrastructure constraints can determine whether it creates value. section 2.1.4

Treat an AI add-on as a product and organizational change, not merely a model integration:

• Target high-impact opportunities where AI amplifies the company’s existing domain competence and competitive advantage. section 2.1.4
• Plan for scattered databases, incompatible formats, data cleanup, governance work, and possible infrastructure updates. section 2.1.4
• Build confidence through differentiated design, development, resource allocation, risk management, and stakeholder decisions. section 2.1.4

Established analytics products

A financial analytics platform adds AI while retaining its established foundation. Comparable applications include adding sustainability reporting to a corporate reporting tool or integrating AI into a data analytics platform with substantial governance needs. section 2.1.4

Figure 2.6 Three scenarios for AI integration

Compare the AI add-on with other integration scenarios before choosing design, delivery, and resource-allocation approaches. section 2.1.4

How The Art of AI Product Development covers it

How deep it goes

Explains the brownfield rationale, trade-offs, and planning concerns, but stops short of detailed implementation procedures.

Examples

Uses financial analytics, corporate reporting with sustainability functionality, and data analytics platforms as examples.

What it assumes

Builds on an established product, user base, organizational domain competence, and tolerance for legacy data and integration constraints.

What you can do after

Apply it by identifying high-impact opportunities and planning integration, governance, infrastructure, resources, and risks.

How it connects

Connects AI integration with brownfield development, data integration, governance, infrastructure, and domain competence.

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Related concepts

• brownfield environmentequivalent to · A brownfield environment is an established technology landscape whose systems, infrastructure, data, processes, or dependencies must be retained, integrated, modernized, or changed.

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.