AI strategy
Synthetic view of expected objectives and allocated resources; consolidation of projects at corporate-process level; awareness of industry AI opportunities and threats.
01 — Consulting
We help executive teams and CIOs decide fast and well: which use cases, in what order, on which technical foundations and with which governance model.
Process-mapping workshops, use-case identification (pain points and the ability of AI to add value), validation of the internal and value-chain scope.
Dynamic assessment of technical complexity (make or buy, transformation issues) and of impact: hours saved, effect on the value proposition.
Technology trends and available resources taken into account, projects grouped and sequenced, a monitoring unit on solutions for the projects not selected.
Synthetic view of expected objectives and allocated resources; consolidation of projects at corporate-process level; awareness of industry AI opportunities and threats.
Design and implementation: use-case development process, AI project portfolio management, IT and business involvement in adoption.
In-house methodology for value, technical complexity and transformation complexity assessment.
Design of the shared components (agent orchestrator, LLM access portal…) that corporate IT should offer business units.
What we did : Process mapping, use-case identification and prioritisation (image and text generation), make-or-buy and impact assessment, roadmap and a solutions monitoring unit.
Context and needs : Multiple uncoordinated initiatives, fast-growing shadow IT, little visibility on priorities and stakes at executive-committee level.
What “APAIA Make or buy Agent” brought : Segmentation of the players addressing this need. Detailed view of the players in each segment. Access to detailed data on the most relevant players to inform the make-or-buy decision.
A maturity assessment across 5 criteria and 9 sub-criteria, run through guided interviews. You leave with a clear view of where to improve.