DLG AI Discovery
Clarify where AI can create value, what is feasible, what must be governed and what should happen next.
What the engagement can cover
Stakeholder and objective alignment
Defined in relation to the organisation, selected workflow and evidence available.
Use-case discovery workshops
Defined in relation to the organisation, selected workflow and evidence available.
Process and pain-point mapping
Defined in relation to the organisation, selected workflow and evidence available.
Data and system readiness review
Defined in relation to the organisation, selected workflow and evidence available.
Governance and risk baseline
Defined in relation to the organisation, selected workflow and evidence available.
Prioritised opportunity portfolio
Defined in relation to the organisation, selected workflow and evidence available.
Typical outputs
How decisions are made
Agree objective and constraints.
Gather the minimum evidence required.
Develop the proposed approach.
Test against quality, value and risk.
Stop, adapt, deploy or scale.
What DataLgorithmics does not assume
Scope, duration, technology choices, commercial terms and expected benefits are not fixed in advance. They depend on the organisation, selected use case, data, integration requirements, risk, delivery model and evidence gathered during the engagement.
Connect learning with delivery
Engagements can be combined with Academy pathways so executives, business teams, engineers and governance functions build the capability needed to operate the resulting systems.
Explore Academy pathwaysDiscuss DLG AI Discovery
Share the organisation, current challenge, intended outcome and timeframe.
Request a scoping conversation