Enterprise generative AI: Transforming operations and unlocking new possibilities

Generative AI (GenAI) is changing how enterprises work. What started as an emerging technology is now a powerful tool for scaling operations, speeding up content creation, and delivering more personalized experiences.

But unlocking these benefits takes more than just plugging in a tool. Enterprises need a clear, strategic approach to GenAI — yet only 1% of leaders say their organization is “mature” enough to scale it across workflows. Without that foundation, teams risk falling behind with manual processes and disconnected systems.

In this article, we’ll explore how GenAI helps enterprises streamline operations, navigate key challenges, and build smarter, more scalable workflows to generate more business value from their content and customer data.

How enterprises benefit from GenAI

Generative artificial intelligence, or GenAI, is technology that creates, modifies, or transforms content, such as text, images, audio, or video. It works by using machine learning models — especially large language models (LLMs) — trained on large datasets. These AI models recognize patterns in existing data and then generate new outputs that closely resemble human-created content.

Unlike traditional AI, which analyzes past data to predict outcomes, GenAI models produce entirely new outputs, from content and code to insights and design. For example, predictive AI might estimate next quarter’s sales based on historical data and other contextual inputs. GenAI, however, learns patterns, structures, and relationships in the training data and uses that knowledge to write concise summaries, craft personalized emails, translate content, or create visuals tailored to specific audiences.

Many enterprises like Docusign (see below) are increasingly using GenAI for tasks such as automating content creation, translating, personalizing experiences, and producing content variations quickly and consistently. By taking on these tasks, GenAI helps teams streamline their workflows and operate more efficiently at scale.

Case Study

Docusign: Streamlined workflows enable faster handoffs and publishing

Contentful Personalization and AI Actions are speeding up Docusign’s production times and localization initiative for key webpages, helping it to scale to new markets.

Workflow automation for greater efficiency

Repetitive tasks — like writing basic copy, tagging digital assets, adding image alt texts, generating an outline, or formatting content — often slow enterprise teams down. These manual processes take valuable time away from strategic projects. They also introduce errors and inconsistencies, especially across large or remote teams. This makes collaboration harder and maintaining brand standards more challenging.

GenAI models help by automating repetitive tasks. Instead of manually reformatting assets or rewriting similar copy, teams can use AI-generated content. This approach saves significant time, reduces mistakes, and keeps content consistently on-brand.

For enterprises managing global content across multiple teams and regions, automation leads directly to efficiency. Teams can scale their operations quickly, respond faster to market changes, and focus more resources on high-value work, like bulk translations or SEO metadata optimization that would otherwise require heavy manual effort.

Accelerated content creation at scale

Enterprise content teams handle large amounts of content for different markets, channels, and customer groups. Creating, translating, and optimizing each piece of content manually is time-consuming and difficult to scale. It can also lead to inconsistent messaging and missed SEO opportunities if global or regional teams aren't aligned.

GenAI helps teams simplify content creation by automatically generating multiple content variations quickly and accurately. Instead of starting each piece from scratch, teams can create high-quality, brand-aligned content at scale — complete with optimized headlines, meta descriptions, and region-specific language. This saves significant production time and helps enterprises maintain consistent messaging everywhere they operate.

By streamlining content creation, enterprises can respond faster and more effectively to customer needs and market opportunities.

Personalized customer experiences

Today’s customers expect content tailored to their interests, behaviors, and preferences. For enterprise teams, delivering that level of personalization across regions, audiences, and touchpoints is a massive undertaking. Imagine operating in 30 different markets with 20 primary audience segments — suddenly, you’re managing 600 versions of every asset. Gathering data and producing unique messaging at that scale is time-consuming, error-prone, and nearly impossible to do manually.

GenAI simplifies this process by automatically generating personalized content based on customer insights. Teams can quickly deliver tailored product recommendations, relevant messaging, and localized visuals that feel timely and meaningful.

This level of personalization helps brands connect more deeply with their audiences. It increases engagement, builds loyalty, and drives conversions — without overwhelming content teams.

Challenges of adopting enterprise GenAI

While the potential of enterprise GenAI is clear, adoption doesn’t come without hurdles. Companies need a clear, strategic approach to adopt responsible AI practices and make sure AI delivers long-term value. Understanding the challenges is the first step toward addressing them effectively.

Protecting data security and privacy

Enterprises work with massive amounts of customer and proprietary data. That data is often spread across teams, tools, and regions — and much of it falls under strict privacy laws and industry regulations. Feeding this information into GenAI systems, especially third-party models, raises real concerns around data handling, compliance, and intellectual property protection.

Without clear policies, teams risk exposing sensitive information or violating legal requirements. Strong data governance is essential. Enterprises need clear rules on what data can be used, how it’s processed, and where it’s stored. Working with secure, enterprise-ready platforms helps ensure responsible AI practices and supports broader risk management goals.

Ensuring quality and ethical use

GenAI doesn’t always get it right. Any AI model can reflect bias, spread misinformation, or create content that misses the mark on tone, clarity, or brand standards. For enterprises, these risks carry more weight. Content is often produced at scale, published across regions, and seen by large, diverse audiences. A single misstep can impact brand reputation and erode customer trust.

That’s why human oversight is essential. Enterprises need clear processes to review AI-generated content for accuracy, quality, and tone, refine prompts, and train teams on responsible usage. Governance plays a key role in this effort. It ensures ethical standards are upheld while maintaining content consistency and brand integrity across every market.

Integrating AI into complex systems

Enterprise content operations rarely run on a single tool or platform. They involve a mix of legacy systems, custom workflows, and cross-functional teams — many working across different markets with different priorities. Adding GenAI into this environment can be challenging. If tools aren’t built to integrate easily, AI can create more friction than value.

For GenAI to deliver real value, it must fit naturally into how teams already work. That means supporting composable architecture, connecting with existing tools, and integrating smoothly into established workflows. Scalable, integration-ready platforms make adoption easier — avoiding silos and helping teams use AI without disruption.

How Contentful helps enterprises harness GenAI

Contentful brings GenAI into the heart of your content workflow to help you create, personalize, and optimize digital experiences. AI capabilities are built into a flexible platform that fits how your teams already work. Because they understand your content, brand, and goals, you can move faster and stay consistent. Here’s how Contentful puts AI to work across your content operations.

Generate high-quality content at scale with AI-powered creation

AI Actions speeds up content creation by embedding GenAI directly into Contentful. Instead of switching between tools or starting from scratch, teams can generate, translate, rewrite, and optimize outputs — all within their existing workflows.

With contextual AI tuned to your brand guidelines, AI Actions helps teams produce consistent, high-quality variants across channels and markets. Taking repetitive work like alt text, SEO tweaks, and localization off your team’s plate also means they have more time to focus on strategy and creativity.

Teams can use prebuilt templates and customize actions to speed up repeatable tasks. For example, a template might help generate first-draft product descriptions or campaign summaries based on just a few inputs. As a result, teams move faster without sacrificing consistency or quality.

Enhance content accuracy and structure with context

Content creation isn’t just about speed; it’s also about precision. With AI Actions, teams can pair custom prompts with reference materials like brand guidelines or legal requirements. These inputs help generate content that meets specific requirements, reduces errors, and stays true to the brand.

Teams can configure these inputs into reusable custom actions that automate formatting, content reviews, and structural consistency. For example, you might set up an action that rewrites product descriptions to match a specific tone or generates SEO-optimized summaries for campaign pages. The result is less time spent on fixes and more time spent creating content that moves the business forward.

Optimize personalization and content delivery

GenAI gives marketers new ways to scale personalization for different audiences without adding complexity. Contentful’s AI-powered tools help teams identify segments, refine messaging, and launch more relevant experiences faster.

AI Suggestions includes features like Audience Suggestions and Experience Suggestions, which use real-time data to help marketers identify high-impact segments and tailor messaging. Combined with AI Variant Generation, teams can quickly create content variations that align with each segment. 

For example, AI might highlight that repeat visitors from a specific region engage most with product-focused messaging, and then suggest updating your copy or call to action to better match their interests. 

All of this happens in one unified workspace thanks to Contentful Personalization. Teams can manage audiences, run experiments, and optimize experiences without juggling disconnected tools. By bringing together audience insights and AI-powered creation, Contentful enables teams to deliver personalized content at scale and drive meaningful business results.

Bottom line

As enterprise content strategies shift toward scale and personalization, GenAI is playing a central role in helping teams move faster without losing control. But success depends on more than just adding new tools — it requires the right foundation.

Enterprise GenAI adoption demands a balanced approach that addresses real challenges while capturing tangible benefits. This means implementing strong data security measures, establishing quality control processes, and selecting tools that integrate with existing systems. 

Contentful brings that foundation together. With a flexible platform and contextual AI built into the core content workflow, teams can generate, adapt, and personalize content quickly — all while staying consistent, compliant, and on-brand.

When done right, GenAI transforms content operations from a bottleneck into a business advantage. Teams save time on routine tasks, produce more relevant content, and deliver personalized experiences that customers value. For organizations that want to move quickly but maintain quality, GenAI provides both the efficiency gains they need today and the adaptability they'll require tomorrow.

Explore how AI Actions fits into your workflow or try the interactive demos to see it in action.

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