7. Transforming B2B Sales in Latin America with Generative AI
Discover how to automate, scale, and humanize your sales process with 10 key use cases.
A Region with Talent, but Sales Slowed by Bureaucracy
Across Latin America, thousands of B2B companies face long sales cycles, multiple decision-makers, and low differentiation. Despite having strong commercial talent and relationships, most sales teams spend over 60% of their time on repetitive or administrative tasks¹. This leads to loss of focus, team frustration, and missed opportunities.
Sales reps feel overwhelmed by low-value tasks and lack of curated information.
Sales managers have limited visibility of the sales pipeline.
Marketing generates leads that are underutilized.
B2B clients receive slow and impersonal interactions.
Generative AI can unlock this human value. According to IBM’s 2024 report, 42% of companies are already actively using AI, while another 40% are still exploring it². McKinsey reports that Gen AI adoption in sales and marketing has doubled between 2023 and 2024³, delivering real improvements in efficiency and customer experience.
Use Cases Organized by Impact
Based on the experience of "Industrias Latinas," a fictional company inspired by real business scenarios in Latin America, we explore 10 key Gen AI applications. Each addresses a real pain point, eliminates a bottleneck, and delivers measurable impact.
1. Automatic Summarization of Calls and Meetings
Each salesperson at Industrias Latinas spent up to 40 minutes daily taking manual notes. These were later (sometimes) entered into the CRM. Key insights often got lost in emails or personal files and weren’t shared across teams.
Without a single source of truth, marketing, pre-sales, and sales worked with incomplete information. New reps had no access to relationship history, causing rework and errors.
Generative AI automates transcription, highlights key agreements and tasks, and connects instantly to the CRM. This improves data quality and creates institutional memory.
Impact: ~15% time saved on repetitive tasks².
2. Follow-ups and Post-Meeting Emails
After client meetings, sellers often struggle to write precise, personalized follow-ups that drive action. At Industrias Latinas, follow-ups were often templated or vague, disconnecting from the meeting and losing opportunities.
Junior sellers also lacked the confidence to write strong messages. Gen AI drafts custom emails based on meeting context and tone, speeding up communication and improving professionalism.
Impact: 18–25% increase in early responses.
3. Opportunity Prioritization in CRM
The sales team handled massive CRM lists filled with outdated or duplicated data, making it hard to know which deals mattered. Managers had trouble identifying which opportunities deserved attention.
Gen AI with predictive models can analyze historical data, find closing patterns, and suggest actions—turning the CRM into a strategic assistant.
Impact: Up to 30% improvement in efficiency and speed.
4. Personalized Commercial Proposals
Creating customized proposals took too much time and involved coordination across teams. Most proposals used generic templates or outdated documents, affecting credibility.
Gen AI builds dynamic proposals using updated data, pricing, customer needs, and success stories. Key success depends on the documents and data used to train the model—this requires ongoing effort to clean and curate information.
Impact: ~60% reduction in time to generate proposals.
5. Automated Response to RFPs
RFPs were exhausting. Teams searched through folders, rewrote texts, and coordinated with technical experts. This led to delays, errors, or abandoned opportunities.
Gen AI parses RFPs, extracts key points, and drafts structured responses. We’ve seen this firsthand: what took a week can now take minutes, providing focused summaries and key requirements.
Impact: 35% increase in response capacity.
6. Objection Handling
Poorly managed objections often lost deals. Sellers at Industrias Latinas improvised when facing legal or technical concerns, undermining trust. There was no structured objection-response database.
Gen AI can map objections, match them with successful answers, and suggest real-time responses, helping reps gain confidence and close more deals.
Impact: 15–20% increase in win rate.
7. Real-Time Training for New Sales Reps
New seller onboarding took weeks. Manuals were outdated, support depended on senior team availability, and knowledge transfer was informal.
With Gen AI, companies can create virtual assistants trained with updated content, FAQs, and best practices, giving reps instant access to key knowledge.
Impact: 40% faster ramp-up time.
8. Automatic Lead Qualification
Marketing handed off large volumes of leads, but many were misqualified or neglected. Some high-value leads were ignored, while reps wasted time on cold contacts.
Gen AI with data enrichment models spots patterns, fills in missing fields, and ranks leads accurately, improving allocation and sales conversion.
Impact: Up to 20% increase in conversion rate.
9. Contract Analysis
Contract review was tedious and error-prone. Key clauses were scattered, multiple versions existed, and legal teams were overstretched.
Gen AI analyzes contracts, flags inconsistencies, compares versions, and highlights risks, improving speed and reliability.
Impact: 40% time savings in contract review.
10. Commercial Content Creation
Sales teams needed tailored brochures, decks, and pitches but depended on marketing for every request. This slowed down response time and flexibility.
Gen AI empowers reps to create client-specific content in minutes using accurate data and clear language.
Impact: Higher professionalism and relevance.
Summary Table: From Pain Points to Generated Value
Conclusion
Adopting Generative AI is not just a technological bet, it’s a deep transformation of the commercial model. In the Latin American context, where resilience and ingenuity are natural strengths, these technologies enable scalable productivity without dehumanizing the sales process.
Each use case presented reflects real, everyday challenges faced by sales teams, and shows that the path to a more agile, personalized, and efficient operation is possible today, not tomorrow. The challenge lies in acting with intention, starting where the pain is greatest, and scaling gradually with open, trustworthy, and integrated solutions.
The solution may lie in AI assistants or agents that accelerate the sales process while keeping human intent in the loop. Growing sales and strengthening customer relationships is the core of these use cases—but we must not lose the human touch that fosters empathy and trust.
Organizations that understand this will not only sell more, but will build stronger and more lasting relationships with their clients—enhancing their competitiveness and purpose in an increasingly demanding market.
In my upcoming articles, I will dive deeper into three specific use cases currently emerging in the region, which I’ve had the opportunity to observe closely with IBM clients.
References
IBM Institute for Business Value, Global AI Adoption Index 2024
IBM Newsroom, Data Suggests Growth in Enterprise Adoption of AI, January 2024
McKinsey, The State of AI in Early 2024, May 2024
Business Insider, Salesforce sellers are using AI…, May 2025
Salesforce/IBM data shows 38% improvement in lead-to-opportunity
McKinsey, Gen AI casts a wider net, July 2024
McKinsey, Economic potential of generative AI, 2023
McKinsey B2B Pulse Survey, September 2024