AI in corporate communication: scale, efficiency, and data-driven creativity.

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AI-generated summary:

Artificial intelligence is transforming content production and communication in companies, bringing scale, agility, and personalization to previously manual and fragmented processes. From using GenAI for automatic text and report generation to translation and the creation of multilingual videos, applications are already generating real impact on efficiency and reach. Case studies from companies like Salesforce, Lionbridge, and Happy Scribe demonstrate tangible gains in speed and consistency, while projects by BlueMetrics with a large e-commerce company and one of the largest TV networks in Brazil show how generative AI can unite technology and purpose to deliver value in every interaction.

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The new frontier of content production.

In the age of real-time information, companies face the challenge of maintaining effective, relevant, and coherent communication aligned with their business strategies. In this context, the combination of data, machine learning, and generative artificial intelligence (GenAI) opens unprecedented avenues for creating, distributing, and personalizing content for both external and internal audiences.

When applied correctly, AI ceases to be merely an automation tool and becomes an engine for efficiency, scale, and precision. It frees up communication and marketing teams for more strategic activities, connected to brand positioning and organizational objectives.

Among the main areas of use, four stand out:

• Content generation at scale : using generative AI to produce articles, posts, newsletters, and reports consistently and quickly.

• Translation and accessibility : eliminating language barriers and promoting inclusion in multilingual markets.

• Automated multimedia : transforming text into video, audio, or hybrid formats, expanding the reach and variety of communication.

• Financial narratives and reporting : automating the creation of data-driven reports, presentations, and executive communications.

  
  

Each of these areas is redefining the role of corporate communication — previously seen as an essentially creative function, and now also driven by data and intelligent automation.

Content generation at scale

Producing repetitive or adapted content for multiple channels usually requires time and large teams. With generative AI, this cycle accelerates. Linguistic models trained with internal data and brand guidelines can generate consistent and localized versions for campaigns, reports, and institutional communications.

Automating the most operational steps frees up time for strategic planning, editorial curation, and impact measurement. The result is more continuous and responsive communication, without loss of identity.

Translation and accessibility

AI-powered translation and automatic interpretation is making global communication more fluid. Tools based on deep learning translate texts, subtitle videos, and adjust for cultural nuances almost instantly.

In addition to eliminating language barriers, these solutions broaden accessibility. Automatic transcriptions, simplified reading versions, and dubbing in multiple languages make content more inclusive, aligning technological innovation with social responsibility.

Automated multimedia

Corporate content goes far beyond text. Videos, podcasts, webinars, and interactive presentations are part of the daily routine for companies. AI allows for the automation of part of this workflow: script creation, video editing, soundtrack selection, subtitle generation, and format adaptation for different platforms.

This expands production capacity and ensures consistency between messages, styles, and audiences. By integrating engagement and behavioral data, AI also helps to understand which formats resonate most with each audience.

Financial narratives and reports

Annual reports, earnings releases, and executive presentations are fundamental pieces of corporate communication. AI is already being used to summarize data, generate introductory slides, create automated visualizations, and produce versions tailored for different audiences: analysts, investors, or employees.

As a result, the communications and finance teams reduce production time, improve consistency, and focus their efforts on the strategic interpretation of results.

Best practices and challenges in the adoption of AI in communication.

Despite the possibilities, adopting AI in content production requires planning and governance. Generative technologies operate based on data, and the quality of that data determines the value of the deliverable.

Companies that excel in this field follow three fundamental principles:

1. Governance and content curation

All AI-generated material needs to undergo human review. The editor's role transforms: instead of simply writing, they become a curator, adjusting tone, narrative, and accuracy. Editorial control remains essential to maintain brand credibility and consistency.

2. Ethics and transparency

Corporate communication should be clear about the use of AI, especially in public materials. Transparency strengthens trust and prevents reputational risks. Furthermore, internal policies should define ethical boundaries for automation and content publication.

3. Data culture and capacity building

The integration between AI and communication depends on the company's analytical maturity. It's necessary to structure data, train teams, and create continuous validation workflows. AI-driven communication is not a replacement for talent, but an expansion of human capabilities.

The combination of technology and data culture creates a new production ecosystem where creativity and efficiency coexist.

Next, we will look at some real-world case studies in this segment.

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Practical applications: real-world cases of AI in communication

Case 1: Generating content at scale with GenAI

In 2023, Salesforce launched Einstein GPT, a product that incorporates generative artificial intelligence into its CRM platform for various functions, including the automatic generation of emails, knowledge base articles, and personalized marketing campaigns. The goal was to scale content production while maintaining brand consistency and relevance for different user profiles.

The results point to a significant acceleration in the production cycle: actions that previously required several hours and multiple validations are now generated in minutes. Furthermore, personalization has been expanded: content adapts to specific segments with customized language and approach. This type of project shows how automated text generation, when combined with good data practices and curation, can free up teams to focus more on strategy, creativity, and impact measurement.

Case 2: translation and multilingual accessibility

Lionbridge Technologies implemented AI solutions on its Language Cloud™ platform for a large global retailer. The challenge was to quickly localize advertising campaigns, web pages, and internal communications for multiple language regions, ensuring brand consistency and cultural sensitivity.

With AI, the localization process was substantially accelerated: translations that previously took days were now delivered in hours, at a lower cost and with greater stylistic uniformity. Furthermore, the solution allowed the company to expand its global presence more quickly and offer accessible versions of its content in different languages, promoting inclusion and engagement in diverse markets. This case reinforces that automated translation is a strategic vector for global communication for companies operating in multiple languages and cultures.

Case 3: automated multimedia and intelligent captioning

A study by Happy Scribe highlighted how companies are using AI to subtitle, transcribe, and adapt corporate videos, training materials, or webinars for different languages and platforms. Automation has drastically reduced subtitling times, which used to take weeks, and expanded the international reach of content.

As a result, organizations were able to generate versions of their training videos in multiple languages, increase accessibility (through subtitles and transcripts), and adapt formats for social media or mobile devices more quickly. Furthermore, post-publication engagement analysis helped identify the most effective formats for each audience, closing the loop between automated production and results measurement. This case demonstrates that multimedia production is no longer a bottleneck, but an agile and scalable component of the communication strategy.

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BlueMetrics Case Study: How one of Brazil's largest TV networks automated the transcription of its content with GenAI.

Context

One of Brazil's largest television networks, with a national presence and a strong presence in investigative journalism and crime reporting, sought to increase its operational efficiency and accelerate the multiplatform distribution of content. In an increasingly competitive and digital market, the broadcaster faced the challenge of rapidly transforming its vast audiovisual archive into standardized, accessible, and impartial textual information.

The growing demand for structured digital content and the accelerated pace of newsrooms have made evident the need for a technological solution capable of automating tasks that were previously manual, while maintaining the rigor and neutrality required by professional journalism.

Problem

The process of transcribing and summarizing news reports was entirely manual, requiring time and dedication from specialized professionals. This workflow generated high operational costs, delays in making the reports available in different formats, and inconsistencies in the summaries produced by different editors.

The absence of a structured textual database also prevented the full utilization of the journalistic archive, limiting the reuse of materials and hindering integration with other digital platforms. The challenge was to find a solution capable of automating the processing of large volumes of audiovisual content, while maintaining the accuracy, impartiality, and agility necessary for the newsroom environment.

Solution

BlueMetrics has developed an automated transcription and summarization solution based on Generative AI and AWS cloud services, combining AWS Transcribe for audio-to-text conversion and AWS Bedrock for generating unbiased summaries.

The project included the creation of a complete processing pipeline, integrating components such as:

• Automated audio-to-text transcription system;

• Summary generation engine with neutrality control and fact-checking;

• Structured database for storage and querying;

• Scalable serverless architecture with native integration into the client's existing infrastructure.

  
  

According to Diórgenes Eugênio, Head of GenAI at BlueMetrics, “the biggest challenge was ensuring that the summaries did not express any kind of bias or opinion. The combination of Transcribe, Bedrock, and our customized validation layer was essential to delivering a pipeline aligned with the broadcaster's editorial standards.”

This approach allowed not only the automation of processes, but also the incorporation of linguistic validations specific to crime journalism, ensuring terminological accuracy and editorial consistency.

Results

The solution transformed the journalism team's workflow. Transcription and summarization time was reduced from hours to minutes, freeing up journalists and editors for higher-value activities such as investigation and story curation.

The broadcaster began making its content available in a more agile and standardized way across multiple digital channels, increasing its coverage capacity and the ability to reuse its historical archive. In addition to operational efficiency, the project brought significant editorial gains, with consistent, neutral summaries that comply with the impartiality standards required by investigative journalism.

Among the main results achieved are:

• Complete automation of the transcription and summarization process;

• Significant reduction in content processing time;

• Standardization and neutrality in the generated texts;

• Organization and structuring of the journalistic archive;

• Better use of content across multiple platforms.

  
  

The adoption of Generative AI not only optimized costs, but also raised the standard of quality and productivity in the processing of audiovisual content, positioning the broadcaster as a benchmark for innovation within the Brazilian television sector.

Conclusion

Intelligent automation and the strategic use of generative AI are redefining how companies manage their processes and resources. In the case of the broadcaster, BlueMetrics demonstrated how solid data engineering, combined with GenAI applied with technical and ethical rigor, can transform an operational challenge into a competitive advantage.

This expertise is what sets BlueMetrics apart in the market. The company combines deep mastery of data engineering, analytics, and machine learning with a practical, results-oriented approach, ensuring that every solution delivered generates measurable value.

With over 200 AI and data projects completed for more than 90 clients in Brazil, the United States, and throughout Latin America, BlueMetrics continues to help organizations across various sectors reduce costs, optimize resources, and operate more intelligently and efficiently.

In a world where efficiency is synonymous with competitiveness, we develop data and AI solutions that deliver measurable, short-term results. Does your company need to reduce costs and optimize resources? Let's talk about it!

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