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AI strategy and value

AI that shows up in the results, not just in the slide deck

AI strategy and value means deciding where AI pays off, what it costs and how to change the way people work to capture that return. Your scattered initiatives become integrated, measurable operations, connected to the same context.

You start with the process and the number it needs to move. The technology comes after.

Find where to start →

Executive analyzing business indicators in the office

What is it?

It is the plan that connects AI to business goals: which processes to change, in what order, with what investment and with what expected return.

Why does it matter?

Without a strategy, AI becomes a collection of pilots that never reach operations and never show up in the company’s results.

How does it work?

We assess how operations work today, design how they could work with AI, prioritize by return and follow the change through to results.

What changes?

Higher productivity, lower costs and real-time indicators showing the value of each initiative.

An example: what should we do with AI this year?

The same question from the board, with and without a strategy.

Today

  1. Lots of ideas
  2. Pilots in every department
  3. No criteria for choosing
  4. Results that never show up

After

  1. Processes mapped
  2. Use cases prioritized by return
  3. Business case approved
  4. Results measured

Each initiative has a business indicator and an owner from day one.

Where this fits: this solution is part of the Data and AI front and is usually the first step for companies that don’t yet know where to start. The 1-minute assessment gives a first answer.

Signs you need this

  • “The company has several AI pilots and none in production.”

  • “No one can say what results AI has delivered.”

  • “Processes are disconnected and depend on manual effort.”

  • “People resist the changes AI requires.”

What we offer

From strategy in the boardroom to change in teams’ daily work.

  • AI strategy and roadmap

    Where AI creates value, what to tackle first and how to move toward increasingly autonomous operations.

    Also known as: Strategic Consulting (C-level) · roadmap to autonomous operations

  • Business case

    The expected return of each initiative, with investment, timeline and a success indicator.

    Also known as: Business Case · ROI

  • Redesigned processes

    How each process works today and how it could work with AI, from end to end.

    Also known as: As-Is assessment · AI-Driven design

  • Change management

    Preparing people to work with AI, through communication, training and follow-up.

    Also known as: Change Management

  • Data strategy

    The plan for data to support AI priorities, with governance and costs under control.

    Also known as: Data & AI Strategy, Governance & FinOps

By the numbers

  • 6%

    of companies see a significant impact from AI on operating results

    Source: McKinsey, State of AI 2025

  • 61%

    of companies do not yet report any impact of AI on operating results

    Source: HBR Analytic Services

  • 95%

    of organizations face integration challenges

    Source: Connectivity Benchmark 2026

Where AI comes in

We also use AI in the assessment itself: to map processes from system records, estimate gains and simulate scenarios before investing.

Where to start

Assessment and business case

We map current operations, identify where AI creates the most value and deliver a prioritized roadmap with the business case.

Request the assessment →

How we do it, step by step

Four steps, from assessment to continuous evolution.

  1. 01

    Assess the current situation

    How operations work today: processes, systems, data and where the bottlenecks are.

  2. 02

    Design with AI

    How each process could work with AI and agents, with people deciding where it matters.

  3. 03

    Prioritize and plan the roadmap

    What to do first, by return and risk, with a business case for each stage.

  4. 04

    Governance and continuous evolution

    Tracking indicators, adjusting course and preparing teams for the change.

How do we do it? See the technical detail →Hide the technical detail

Professional layer

As-Is assessment and process mining · AI-driven and agentified process design · prioritization by value and risk · business case and ROI model · committee and governance of AI initiatives · change management · roadmap to autonomous operations.

We call this Business Consulting: strategy, processes and change for the AI era.

Frequently asked questions

Common questions about AI strategy

Where should a company start with AI?

With a process that happens often, follows known rules, has data available and does not cause serious harm if it goes wrong. The assessment points to that process and its expected return before any investment.

How do you measure the return on AI?

With a business indicator defined before the project — service time, cost per transaction, revenue — and tracked afterward. Without that number, AI stays a matter of perception.

Why do so many AI pilots never reach production?

Because they start with the technology, not the process. They lack prepared data, integration with systems, governance rules and people ready for the change. A strategy solves this before the pilot.

Will AI replace people?

AI takes over repetitive and lookup tasks; people keep what requires judgment and relationships. Change management prepares teams for this new division of work.

The Enterprise AI Company

Connected to your operation

This service is part of a single operating model, with AI agents and specialists on the Semantix AI Suite. Decisions made here feed your company’s shared context and make the other operations smarter.

  1. 01Service DeskField Services · Asset management · ITSM
  2. 02AMS · ApplicationsSupport · Modernization · Quality
  3. 03AMS SAPImplementation · Support · SAP Business AI
  4. 04NOC · Infrastructure and cloudCloudOps · FinOps · Observability
  5. 05SOC · Security24×7 monitoring · Identities · XDR and MDR
  6. 06DOC · Data and AIData platform · Analytics · AI governance
  7. 07Agentified business processesFinance · Customer service · Procurement and supply · People and HR · Legal and contracts · Risk and compliance

Agents on the volumeSpecialists on judgmentFrom platform to operations

One context for your companyEvery operation feeds the same context and runs on the same foundation: the Semantix AI Suite and Brazilian governance.Explore Semantix AI Suite →

Connect · Operate · Learn · Orchestrate

Not sure what a term means? That’s fine

Nobody should have to speak technology to understand a transformation.

Enterprise AI Company
A company that brings AI into the operations of large enterprises: it delivers the platform, builds with the client’s team or runs the processes with AI agents and specialists.
Hybrid workforce
AI agents handle the volume; specialists decide the exceptions and the risky cases.
Operation that learns
Every human decision becomes knowledge, so the next similar case is faster and cheaper.
Outcome-based contract
You pay for what is delivered and measured, such as tickets resolved or cost per transaction.
Context
Your company’s knowledge (data, processes, rules and decisions) that lets AI act safely.
AI
Computers able to perform tasks that would normally require human intelligence.
Agent
An AI system that can carry out tasks using tools.
Workflow
The path a piece of work travels inside a company.
API
A way of letting systems talk to each other.
Cloud
Computing and storage reached over the internet.
Data Platform
An environment that organizes and serves the company’s data.
Agentic AI
AI that can understand goals and carry out tasks within defined limits.
AI Harness
The structure that supplies the context, tools, rules and controls an agent needs to act safely.