Paper Type

Complete

Paper Number

1477

Description

Small and medium-sized businesses (SMBs) face unique challenges in developing AI- enabled products and services, with traditional innovation processes proving too resource-intensive and poorly adapted to AI's complexities. Following design science research methodology, this paper introduces Innovation Process for AI-enabled Products and Services (IPAPS), a framework specifically designed for SMBs developing AI-enabled solutions. Built on a semi-formal ontology that synthesizes literature on innovation processes, technology development frameworks, and AI-specific challenges, IPAPS guides organizations through five structured phases from use case identification to market launch. The framework integrates established innovation principles with AI- specific requirements while emphasizing iterative development through agile, lean startup, and design thinking approaches. Through polar theoretical sampling, we conducted ex-post analysis of two contrasting cases. Analysis revealed that the successful case naturally aligned with IPAPS principles, while the unsuccessful case showed significant deviations, providing preliminary evidence supporting IPAPS as a potentially valid innovation process for resource-constrained organizations.

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Jul 6th, 12:00 AM

Innovation Process for AI-enabled Products and Services (IPAPS)

Small and medium-sized businesses (SMBs) face unique challenges in developing AI- enabled products and services, with traditional innovation processes proving too resource-intensive and poorly adapted to AI's complexities. Following design science research methodology, this paper introduces Innovation Process for AI-enabled Products and Services (IPAPS), a framework specifically designed for SMBs developing AI-enabled solutions. Built on a semi-formal ontology that synthesizes literature on innovation processes, technology development frameworks, and AI-specific challenges, IPAPS guides organizations through five structured phases from use case identification to market launch. The framework integrates established innovation principles with AI- specific requirements while emphasizing iterative development through agile, lean startup, and design thinking approaches. Through polar theoretical sampling, we conducted ex-post analysis of two contrasting cases. Analysis revealed that the successful case naturally aligned with IPAPS principles, while the unsuccessful case showed significant deviations, providing preliminary evidence supporting IPAPS as a potentially valid innovation process for resource-constrained organizations.