The Complete Guide to Using AI as a Marketing Professional in Brazil in 2025

Marketing teams in Brazil can't afford to treat AI as a toy in 2025 - investments are set to top BRL 13 billion and the government's PBIA channels major funding and infrastructure (including projects like the Santos Dumont supercomputer), so strategy, compliance and skills now determine who wins customers and trust (Brazil AI legal trends and regulations - Chambers Practice Guide 2025).

New federal rules (Bill No 2,338/2023) plus LGPD and ANPD guidance mean marketers must balance powerful personalization and generative content with transparency, data-provenance and automated‑decision safeguards - while the market itself still forecasts strong growth (CAGR ~19% from 2025) for AI services (Brazil AI market outlook and growth forecast - Grand View Research).

This guide zeroes in on practical use cases, procurement and risk controls, and why short, focused reskilling (for example, Nucamp's AI Essentials for Work) is the fastest path from experimentation to compliant, revenue-driving campaigns (Register for Nucamp AI Essentials for Work bootcamp).

For marketers in Brazil, Bill No. 2,338/2023 is the must‑watch rulebook: approved by the Federal Senate in December 2024 but still pending review in the Chamber of Deputies, the proposal would impose a risk‑based regime that reaches development, deployment and use of AI across sectors and even on foreign providers operating in Brazil (territorial scope is broad), so vendor choices and campaign designs can trigger legal duties long before a model goes live; key practical takeaways include a mandatory preliminary risk classification by the developer or deployer, algorithmic impact assessments for high‑risk or systemic models, explicit transparency and human‑oversight requirements, tight data‑governance and provenance obligations aligned with LGPD, and heavy enforcement tools (warnings, suspension and fines up to R$50 million or 2% of turnover).

Marketing teams should bake these controls into procurement, documentation and A/B testing plans now - see the detailed tracker at White & Case and the practitioner summary in the Chambers Practice Guide for the latest steps to map obligations to use cases and contracts.

“a machine-based system that, with varying degrees of autonomy and for explicit or implicit objectives, infers, based on a set of input data or information it receives, how to generate outputs, in particular, predictions, content, recommendations, or decisions that may influence virtual, physical, or real environments.” - Brazil's Proposed AI Regulation (Bill No. 2,338/2023)

The Brazilian strategy for artificial intelligence is now a coordinated push to pair industrial-scale infrastructure with talent, ethics and public‑interest use: the Brazilian Artificial Intelligence Plan (PBIA 2024–2028), coordinated by MCTI and CGEE, channels R$23 billion into supercomputing, regional AI centres, workforce development and governance to favor “sovereign” Portuguese‑language models and safer public services; a vivid signal of intent is the Santos Dumont supercomputer upgrade (now a high‑performance testbed) as Brazil aims for a top‑five AI machine while building a national network of AI hubs and regulatory sandboxes to accelerate applied projects and inclusive capacity building (see the PBIA final version at LNCC and reporting on the PBIA's hardware and funding plan).

Complementing PBIA, the earlier EBIA strategy and sector programs tie defence, health and public‑sector pilots into a whole‑of‑government roadmap so marketing teams can anticipate local model development, data‑centre growth and public procurement that will shape vendor choices and campaign compliance over the next three years.

“Through technology, we want to ensure benefits to our country and our people, and this is only possible if public authorities, civil society, and the private sector work together. The AI plan is the first result of this.”

AI in Brazil is already practical marketing muscle, not just a buzzword: retailers like Magazine Luiza used AI‑driven personalization to lift customer engagement ~35% and boost conversion rates ~22% within months (Magazine Luiza AI personalization case study - BytePlus), while financial firms and fintechs pair prediction and automation to reshape customer journeys - Acordo Certo's H2O.ai models sped model development, improved repayment‑score accuracy to over 76% and helped recover millions each month (Acordo Certo repayment scoring case study - H2O.ai).

Banks are using generative assistants too: Banestes piloted Gemini in Google Workspace to accelerate credit analysis and free up analysts for higher‑value decisions (Banestes generative assistant pilot with Gemini - Google Cloud).

Across e‑commerce, media and creator economies the playbook is consistent - recommendation engines, chatbots, content generation, dynamic creative optimization and predictive segmentation - and real campaigns prove the ROI: AI can turn a generic homepage into a tailored storefront, cut manual testing cycles, and boost click‑throughs and lifetime value without sacrificing local language or cultural nuance.

For marketing teams in Brazil the imperative is clear: pilot measurable, privacy‑aware AI projects that link personalization to legal and data‑governance controls, then scale what demonstrably moves engagement and revenue.

Driverless AI is not only easy to use, but it is easy to get results. We have reduced the time to build and deploy models from about one week to a few days. This is massive for our team. We have also improved the predictive accuracy of the repayment model to over 76% Consumers and creditors alike are reaping the benefits of our unique AI debt scoring models.

Market signals for 2025 make one thing clear for marketing teams in Brazil: the AI opportunity is now measurable and multi‑speed - Grand View Research pegs the broader Brazilian AI market at roughly USD 11.09 billion in 2023 and forecasts a robust CAGR of about 19.2% from 2025–2030, meaning buyer demand and platform capabilities will scale fast (Brazil AI market outlook 2023–2030 - Grand View Research).

Generative AI is an especially hot front: analysts report rapidly rising adoption and sizable long‑term upside (IMARC projects the generative‑AI market growing from ~USD 316M in 2024 toward USD 1.35B by 2033 with mid‑to‑high double‑digit growth), a signal that content automation, localized LLMs and creative testing will move from experiments into core channel stacks (Brazil generative AI market forecast 2024–2033 - IMARC Group).

Infrastructure and fintech footprints matter too: AI data‑centre investment (estimated at ~USD 0.56B in 2025, rising toward ~USD 1.24B by 2030) and steady fintech AI growth show that hosting, latency and sectoral use cases will shape vendor choice and campaign design (Brazil AI data‑center market forecast 2025–2030 - Mordor Intelligence).

The so‑what for marketers: prioritize pilot projects with clear ROI metrics, choose vendors with on‑shore capabilities, and plan creative ops that can scale from one successful persona to thousands of hyper‑personalized experiences without violating data or procurement constraints - imagine turning a single A/B test into a library of culturally tuned storefronts overnight as the stack matures.

Marketing teams in Brazil must treat data protection as a core campaign ingredient: the LGPD applies to any processing that happens in Brazil or targets people in Brazil, so start by mapping every data flow, documenting the legal basis (consent, legitimate interest, credit protection, contract, etc.), and keeping records of processing activities as required by law - the full LGPD text and definitions are usefully searchable in the IAPP English translation (LGPD English translation - IAPP).

Practical must‑dos include deploying an affirmative cookie banner and consent capture for non‑essential tracking, proving

“free, informed and unambiguous”

consent, appointing or designating a DPO where your risk profile demands it (note ANPD guidance allows tailored approaches for small businesses/processors), carrying out DPIAs for high‑risk personalization or automated decisions, and baking privacy‑by‑design into creative ops; ANPD rules also tighten cross‑border transfer safeguards and incident reporting, with breach notifications to ANPD and affected users required when a security event is likely to cause risk (and incident records kept for years).

The so‑what: non‑compliance can trigger sanctions up to 2% of turnover or R$50M and remedial orders that can force deletion or blocking of marketing lists - in worst cases an entire email list could be shuttered - so prioritize consent management, vendor contracts with transfer guarantees, fast DSAR workflows (LGPD timelines are shorter than GDPR), and measurable DPIAs before scaling any AI personalization.

When buying AI services in Brazil, turn procurement into a compliance-first advantage: map every data flow, require a signed data processing agreement that makes the processor act only on the controller's instructions, and insist that international transfers use ANPD‑approved mechanisms - today that means embedding the full Brazilian Standard Contractual Clauses (SCCs) in both Portuguese and English where data leaves Brazil (Brazil Standard Contractual Clauses (SCCs) - JDSupra).

Contracts should specify parties, purposes, categories of personal data, retention, allowed onward transfers, and robust security measures, and they must allocate breach‑response duties (including cooperation to meet ANPD notification rules and incident records).

Make vendors warrant LGPD compliance, publish a DPO contact, supply processing records on request, and agree to assist with DPIAs and DSARs so that automated‑decision or personalization projects don't stall under regulatory scrutiny; remember ANPD and LGPD enforcement can include blocking or deletion of data and fines (up to 2% of turnover or R$50 million).

Finally, prefer vendors with on‑shore processing or clear contractual SCCs with parent/sub‑processors, require audit and remediation rights, and lock in deletion/return obligations at contract termination - a single missed clause can mean a campaign loses access to a marketing list, so build procurement checklists that protect growth and legal footing from day one (ANPD data transfer rules and SCC timeline - Securiti).

Risk management for AI-powered marketing in Brazil means turning legal uncertainty into repeatable controls: with Bill No. 2,338/2023 pushing a risk‑based regime and ANPD‑led enforcement powers (including suspension and heavy fines), teams must pair airtight data flows and contracts with active model oversight - start by mapping every feature and pipeline, run DPIAs on personalization or automated decisions, and require SCCs or on‑shore processing in vendor agreements to avoid cross‑border headaches.

Practical governance is not optional; adopt a proven structure such as the 4‑pillar approach to AI and data governance (foundational data quality, lifecycle controls, operational monitoring and ethical/compliance oversight) to make sure models are explainable, bias‑tested and monitored in production (EWSolutions AI and data governance 4-pillar framework).

Concretely, add model cards and inference logs to procurement checklists, route high‑impact decisions through human‑in‑the‑loop workflows with SLAs, instrument real‑time drift and fairness dashboards, and convene a cross‑functional ethics committee to sign off on high‑risk campaigns; otherwise a regulator order or a single misconfigured pipeline can shutter an email list or halt a campaign overnight.

For the latest procedural risks and enforcement scope, follow Brazil's evolving tracker on AI regulation (White & Case AI Watch Brazil regulatory tracker).

“a machine-based system that, with varying degrees of autonomy and for explicit or implicit objectives, infers, based on a set of input data or information it receives, how to generate outputs, in particular, predictions, content, recommendations, or decisions that may influence virtual, physical, or real environments.” - Brazil's Proposed AI Regulation (Bill No. 2,338/2023)

Sector-specific playbooks are essential because the same AI trick that boosts conversion in retail can create legal headaches in regulated areas - Brazil's AI momentum (investments set to exceed BRL 13 billion) and sector rules mean teams must treat compliance as a product requirement, not an afterthought (Chambers Practice Guides: Brazil artificial intelligence investments and trends 2025).

In retail, hyper‑personalization and features like virtual fitting rooms drive loyalty but trigger cookie/consumer‑protection duties and DPIAs; e‑commerce research warns that journey personalization and real‑time adaptation are core tech bets for the next decade (AMCIS 2025 study on the future of e-commerce in Brazil and personalization).

Finance teams must layer LGPD, banking‑secrecy rules and BACEN expectations onto credit‑scoring models and Open Finance integrations, or face operational and supervisory scrutiny.

Health‑sector AI (SaMD) carries the highest bars: ANVISA validation, sensitive‑data safeguards and explicit consent are non‑negotiable. Public sector projects demand transparency, human oversight and alignment with PBIA/ethical guidelines to keep procurement and citizen trust intact.

The bottom line: design campaigns so a single misconfigured model can't wreck a customer journey - think of compliance as the safety harness that lets AI scale, not the brake that stops it.

Final steps should be simple, measurable and urgent: map every data flow, run a DPIA for high‑risk personalization or automated decisions (follow the step‑by‑step DPIA guidance at TrustArc DPIA guide), and switch cookie banners and consent captures to explicit opt‑in so marketing experiments have a lawful basis (see Captain Compliance LGPD checklist for a practical runbook).

Lock contractual guarantees - on‑shore processing or ANPD‑aligned SCCs, breach cooperation, and deletion/return clauses - into vendor agreements before any model goes to production, and require model cards, inference logs and human‑in‑the‑loop gates for high‑impact segments so one misconfigured pipeline can't shutter an email list overnight.

Measure pilots against clear ROI metrics (engagement lift, conversion delta, LTV), scale only the winners, and treat governance as launch criteria not an afterthought; for teams that need fast, role‑focused reskilling, consider short programs like Nucamp's AI Essentials for Work to learn prompts, prompt testing and privacy‑aware deployment in 15 weeks (AI Essentials for Work syllabus - Nucamp, Register for AI Essentials for Work - Nucamp).

Start with one measurable pilot, document every decision for ANPD readiness, and iterate - compliance is the safety harness that lets AI scale, not the brake that stops it.

“free, informed and unambiguous”