Start with the decisions that cross boundaries.

From AI ambition to governed action

A large enterprise has engaged i5 to turn AI interest into evidence-based priorities. The work brings discovery, readiness assessment, bounded action and opportunity definition together, with governance running throughout. Its objective is to clarify where AI could create value, what must be ready, and who should decide what happens next. Target outcomes remain distinct from achieved results.

Read the anonymous program brief.

These scenarios show possible starting points for complex enterprises. They are illustrations, not customer engagements, deployments, or achieved results. The suggested roles are examples; each enterprise must establish its own decision rights.

Illustrative customer archetype. An enterprise has AI experiments across functions, but no shared way to compare opportunities or decide which are ready for wider use. A transformation executive could sponsor the evaluation, with business decision owners, the CIO or data lead, and governance owners accountable for their respective boundaries.

Teams already use enterprise applications and hold process documentation, sample outputs and access-controlled data. The recurring coordination problem is reconciling local enthusiasm with dependencies, ownership and control requirements. A plausible first evaluation would compare a small set of opportunities using available evidence, map prerequisites and decision rights, and test one bounded assumption with approved data. Any next step would require an explicit owner and review.

Illustrative customer archetype. An enterprise operates across several sites. Local teams respond to disruptions, but a change in one location can affect capacity, commitments and priorities elsewhere. An operations executive could sponsor a bounded evaluation, with site decision owners, systems and data leads, and governance owners defining who may approve a change.

Existing planning and operational systems remain authoritative. A first evaluation would need usable historical or read-only records, agreed definitions and evidence of the constraints that matter across sites. The team could reconstruct one recurring exception, compare possible responses and document approval boundaries. The purpose would be to test whether shared context improves the decision process before considering controlled actions.

Illustrative customer archetype. An enterprise coordinates commitments across suppliers, logistics providers and internal functions. Each participant has its own systems and authority; an exception can trigger conflicting updates and repeated negotiation. A supply-chain or operations executive could sponsor an evaluation, with procurement, logistics and customer-facing decision owners, supported by data and governance leads.

The starting point would be a narrow set of commitments and approved historical, synthetic or read-only data. Participants would need to agree which evidence can be shared and who controls each decision. A plausible evaluation would trace one exception, compare alternatives and identify the approvals required. It would test coordination assumptions without granting access to partner systems or committing participants to live execution.

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