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What structural barriers slow down AI adoption in your workplace?

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Fabian Crosa
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PMO Leader | Speaker & Mentor | Content Leader – PMOGA Latin America Hub| Catholic University of Uruguay Montevideo, Montevideo, Uruguay

Research shows that technology is rarely the main obstacle—governance, decision rights, and operating models often hold back progress. This question encourages readers to identify the hidden organizational factors.

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Luis Branco CEO| Business Insight, Consultores de Gestão, Ldª Carcavelos, Lisboa, Portugal
Fabian, I would make one distinction between structural barriers and legitimate structural constraints. Not everything that slows AI adoption should necessarily be removed.

Unclear decision rights, unnecessary approval layers, fragmented workflows or operating models designed around assumptions that AI has changed may genuinely constrain value creation.
But some friction may serve an important purpose.
Human review, segregation of duties, risk controls, escalation paths or limits on delegated authority may slow execution while being necessary to preserve accountability, meaningful oversight and the ability to intervene when consequences become material.

So, for me, the objective should not be to maximize the speed or extent of AI adoption.
It should be to redesign the organization so that human and AI capabilities can be combined where they create value, while preserving the governance needed to ensure appropriate authority, accountability, oversight and intervention when consequences become material.

Perhaps the deeper question is not simply what is slowing AI adoption, but which structural constraints are preventing useful adaptation, which should be redesigned, and which remain necessary because of what they protect.
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Sergio Luis Conte Helping to create solutions for everyone| Worldwide based Organizations Buenos Aires, Argentina
It is simple. 1-do not use generative AI as a synonim of AI. 2-understand that generative AI works in probabilistic environments.

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