What does AI consulting include?
AI consulting maps business processes, ranks use cases, checks data readiness and defines the first practical pilot.
AI consulting
Get a clear AI roadmap before you build.
AI consulting should end with decisions, not a slide deck. We identify where AI can create value, what should stay manual, and which first workflow deserves a pilot.
2 weeks
typical diagnostic sprint
1 roadmap
use cases, risks and order
Fixed scope
clear next build decision
Quick answers
What to know before you start
Who is it for?
It is for leaders who know AI matters but need a grounded way to choose what to build first.
What is the output?
The output is a ranked roadmap, pilot scope, risk list, adoption plan and clear owner for the next step.
Practical scope
How AI consulting becomes a working system
We start with one workflow, not a platform decision. The first candidate is usually use-case confusion, tool-first thinking or adoption risk. Before any tool is connected, we define the input, owner, approval point and measurable business result.
AI consulting can involve CRM data, inboxes, documents, spreadsheets, n8n or Make automations, ChatGPT workflows and internal AI agents. For each implementation, we document what AI may decide, what it may only draft and where a person must approve the action before it affects a client or system.
The proof base comes from Artelity's AI adoption work: 1000+ trained specialists, 50+ workshops and projects with Eesti Koolituskeskus, VOCO, Töötukassa and the Estonian Ministry of Education. The first result should be operational: ai opportunity map, pilot scope and a clear decision on what to scale next.
Integrations
We map data sources, CRM fields, document types, owner roles and the places where information currently moves by hand.
Measurement
We define the baseline: time spent, error rate, response speed, pipeline leakage or training adoption signal.
Safeguards
Sensitive outputs start with human approval, logs and a clear rule for when AI should escalate instead of answering.
Focus
What consulting clarifies
Use-case confusion
Too many ideas, no order, no measured business case.
Tool-first thinking
Teams choose software before agreeing how work should change.
Adoption risk
AI fails when people do not know when and how to use it.
Result
Consulting outputs
AI opportunity map
Processes ranked by impact, complexity, risk and readiness.
Pilot scope
One first workflow with data inputs, users, success metric and constraints.
Adoption plan
Training, SOPs, owner model and rollout order.
Consulting sprint
01
Discovery
We review processes, tools, team habits and existing data.
02
Prioritisation
We score use cases by value, readiness and risk.
03
Decision workshop
You leave with the first pilot and what to avoid.
FAQ
Common questions
Do you also build after consulting?
Yes, if the pilot is worth building. The consulting output is useful even if you build internally.
Can this include tool selection?
Yes, but tools come after process, data and ownership decisions.
The next step is a short working call.
We review your current situation and decide whether the first move should be an audit, CRM setup, dashboard, automation or training.