Give the opportunity to royal adoption of artificial intelligence.
The DOMVS iT framework structures the AI strategy to transform scattered opportunities into a clear path for adoption and execution.
Business outcome-driven AI strategy
We map where artificial intelligence can generate real value and structure the path to transform these opportunities into viable initiatives for the company.
DOMVS iT oversees the strategy from development through implementation, creating the conditions for adoption to proceed with consistency and governance.
What changes for the business
More clarity to decide where AI should advance first.
Clear priorities
Find out which AI initiatives to invest in first and why.
Actionable roadmap
Transform the defined priorities into a clear adoption plan.
Secure adoption
Structure AI adoption with the necessary controls from the start.
From pilot to scale
Take initiatives from proof of concept to operation with greater predictability.
Solution components
Each workstream is structured according to the adoption stage and business objectives.
AI Maturity Assessment
We identified the company's current stage and what needs to evolve to sustain AI adoption.
Opportunity map
We prioritize use cases with the highest potential to generate business value.
Adoption roadmap
We organized the initiatives into an adoption plan compatible with the actual execution capacity.
Governance and responsible use
We have structured the guidelines that guide the responsible use of artificial intelligence in the company.
Security and compliance
We incorporate security and privacy requirements into the AI adoption strategy.
Implementation support
We support teams from the execution of the first initiatives through to operation.
Frequently asked questions
An artificial intelligence strategy defines how the company intends to adopt AI in alignment with its business priorities. It guides where to advance and what conditions must exist to transform initiatives into real capability.
The starting point is to understand the organization's current scenario and identify where artificial intelligence can generate relevant impact. From there, it is possible to prioritize initiatives and structure a viable adoption plan.
It is an assessment of the company's current stage to understand its capability to adopt and scale artificial intelligence. The diagnostic helps identify gaps that may limit the progress of initiatives.
It is the plan that organizes the evolution of AI initiatives over time and guides which fronts should advance first, according to the company's reality.
The transition requires the use case to be prepared to operate in the company's real environment. The strategy must consider from the beginning what will be necessary to sustain the initiative in production.
This type of action makes sense when the company needs to organize AI initiatives, prioritize investments, or transform isolated pilots into a structured adoption agenda.
Yes. The work can go beyond strategy definition and monitor initiatives during the transition to implementation, helping to turn planning into execution.