Building effective business content with AI

Jean-Marc Chanoine at Templafy explains why enterprises are failing at GenAI content creation

 

As we enter 2025, the promise of generative AI enhancing enterprise content creation remains largely unfulfilled. While the tools provide sophisticated meeting summaries, search optimisation and time-saving workflows, they fall short of the transformative potential many enterprises anticipated when developing content.

 

The core issue remains: generative AI still struggles to deliver high-quality, context-aware business content that meets enterprise standards. This gap persists despite strong demand: our research shows that nearly 7 in 10 employees (67%) want document creation tasks automated. As organisations explore AI-driven solutions, they’re discovering that creating effective, enterprise-grade content is far more complex than early hype suggested.

 

The predictive nature of generative AI

Generative AI models operate primarily by making predictions. They analyse vast amounts of existing content to forecast what comes next, producing results that can range from highly relevant to completely inaccurate. While this works well for tasks like auto-completing emails or summarising calls, it struggles when creating complex, high-stakes business content that aligns with corporate identity or rebranding strategy.

 

The challenge lies in the fundamental difference between how AI and humans think—AI predicts but lacks true comprehension. It doesn’t grasp the underlying reasons why something should be written in a particular way. Essential aspects of business content creation—context, nuance, intent, and audience needs—are often overlooked by the predictive nature of generative AI.

 

What we’ve learned is that crafting high-quality business content goes beyond predicting the next word or sentence. Every piece of content in business serves a specific purpose and must adhere to legal and content standards while maintaining a consistent brand voice. For AI to be truly valuable in this process, it must move beyond mimicking past content and be capable of addressing intent and understanding the audience to exert brand control and safeguard reputational risk. 

 

Three pillars of business content creation

Unlocking the full potential of generative AI in business content creation hinges on three key pillars: purpose, quality, and policy. Simply relying on the model’s predictions is no longer sufficient. For effective results, enterprises must complement AI outputs with human-driven insights and decision-making in these critical areas.

 

1. Purpose

Identifying the purpose is the cornerstone of any business content. Whether crafting a sales pitch, company announcement, or marketing campaign, understanding the "why" behind the message is essential. A limitation of generative AI is its inability to comprehend purpose—it simply predicts based on past patterns.

 

This is especially problematic in business, where stakes are high and context is often complex. To address this, organisations need systems that enable users to clearly define the intent behind their content, providing the AI model with a clear direction. The purpose must be prioritised in any AI-assisted content creation process.

 

2. Quality 

Quality is inherently subjective, and this is an area where AI models often fall short. While AI can generate grammatically correct content that appears polished, it doesn’t always ensure true quality. Content quality isn’t just about technical accuracy—it’s also about relevance, persuasiveness, and alignment with business objectives. Whether you’re rebranding your business, or striving for brand consistency, quality is essential. 

 

The quality of AI-generated content is closely tied to the quality of the prompts given by users. The saying "garbage in, garbage out" rings especially true in this case. Without clear, well-thought-out inputs, even the most sophisticated AI models will struggle to deliver high-quality results. Unfortunately, many organisations lack the tools to guide users in crafting effective prompts, leading to a cycle of subpar outputs.

 

The key to improving quality lies in collaboration between humans and AI. Companies need to invest in tools that help employees provide the right inputs, ultimately driving better content outcomes. While AI can assist, it cannot produce top-tier content on its own.

 

3. Compliance

The third critical factor when using generative AI for business content creation is ensuring adherence to policies and regulations. The swift sequence of global government elections in 2024, now shaping the landscape in 2025, has led to a growing wave of industry and government regulations. Staying updated is crucial to ensure content aligns with the latest legal standards.

 

Generative AI models are trained on vast datasets, but they aren’t equipped to stay updated with the latest laws and regulations. As a result, models may fail to account for new privacy laws or evolving corporate standards, leading to non-compliant content.

 

This is where the right tools become essential. Policy adherence is too complex and fluid to be managed solely by AI. Companies need systems that continuously update and enforce the latest policies, ensuring compliance at every stage of content creation. While AI models can provide the foundation, maintaining compliance requires external management to keep up with regulatory changes.

 

Tools that go beyond predictions

The limitations of generative AI in business content creation are clear, but the path ahead is equally straightforward. In 2025, businesses need solutions that do more than make predictions—they require tools that help users define and apply purpose, quality, and compliance throughout the content creation process.

 

What’s needed is a hybrid approach where AI works alongside human input and external tools to ensure that content meets the necessary standards of intent, quality, and legal compliance. This could involve developing new ways to interact with AI and refining prompt systems to generate more effective outputs.

 

Generative AI still holds vast potential for transforming business content creation, but unlocking that potential requires addressing its current limitations. By prioritising purpose, quality, and compliance, businesses can create content that delivers real value, not just predictable results.

 

Looking to the future, the next phase of generative AI must go beyond basic applications like meeting summaries or search enhancement. To truly revolutionise business content creation, the technology needs to advance, supported by the right tools and strategies, to fulfil the high expectations set by the tech world. 

 

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Jean-Marc Chanoine is SVP of Americas and Global Partnerships at Templafy

 

Main image courtesy of iStockPhoto.com and sompong_tom