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How does your team address ethical risks in AI projects within short delivery cycles?

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Stelian ROMAN Project Manager| MicroSafety Carlingford, New South Wales, Australia

Like Agile, Artificial Intelligence (AI) is no longer seen as a concept limited to software development. Artificial Intelligence has become a defining force in product innovation across industries. As Agile delivery cycles accelerate the introduction of AI-powered features, organizations face a critical question: Can Agile teams govern AI risks effectively within short delivery cycles? The challenges are complex, touching on bias, explainability, accountability, and human oversight. As this debate takes centre stage in many professional forums, references such as the PMI Code of Ethics and Professional Conduct, the Agile Practice Guide, ISO 31000, and the PMBOK provide valuable perspectives on delivering responsible AI products.

This blog post aims to spark thoughtful discussion and practical action on one of today’s most critical technology challenges.

ProjectManagement.com - Challenges of AI and Ethical Product Delivery

on ProjectManagement.com - The Agile Enterprise

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Lissette Indhira Pimentel Sosa
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Program Manager| HARPER SRL Santo Domingo / Distrito Nacional, Dominican Republic
I think ethical risks need to be part of the work from the beginning rather than something reviewed at the end of a delivery cycle. For AI projects, that can mean identifying concerns around data, bias, transparency, and human oversight early and including the necessary checks as part of the acceptance criteria.
Short cycles shouldn’t mean postponing those conversations. Some risks need to be addressed before the feature moves forward, even if that affects the timeline.
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1 reply by Stelian ROMAN
Sep 24, 2026 10:59 PM
Stelian ROMAN
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I agree. They should be part of the scope with agreed-upon acceptance criteria. The challenge is that in Scrum, a product backlog item may not capture the ethics dimension.
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Stelian ROMAN Project Manager| MicroSafety Carlingford, New South Wales, Australia
Sep 24, 2026 8:22 AM
Replying to Lissette Indhira Pimentel Sosa
...
I think ethical risks need to be part of the work from the beginning rather than something reviewed at the end of a delivery cycle. For AI projects, that can mean identifying concerns around data, bias, transparency, and human oversight early and including the necessary checks as part of the acceptance criteria.
Short cycles shouldn’t mean postponing those conversations. Some risks need to be addressed before the feature moves forward, even if that affects the timeline.
I agree. They should be part of the scope with agreed-upon acceptance criteria. The challenge is that in Scrum, a product backlog item may not capture the ethics dimension.

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