Content creation is the tectonic origin of AI innovation. That’s a big change. For decades, organizations have created content based on the fundamental premise: content is created by humans, for humans. Today, humans are already working with machines to co-create nearly all content formats, manage content lifecycles, and optimize media.
As AI accelerates and agent systems begin to orchestrate more digital journeys, machines are both content creators and primary content consumers. Why? Because these machines increasingly determine what content buyers see, especially on answer engines. Enter your new marketing ABCs. Business-to-Agent joins Business-to-Business and Business-to-Consumer to shape the future of content creation and consumption.
Today’s content still misses the mark – and AI alone can’t fix it
Despite making huge investments in genAI, most companies remain stuck in traditional content processes and technologies. The biggest culprit: Content creation still relies on fragmented content repositories with siled data and manual processes. Unsurprisingly, even though four out of five B2B organizations have adopted or implemented genAI for content use cases and just over half of B2C and advertising decision makers expect to invest in more user-generated and influencer content, digital leaders say the impact on business outcomes remains elusive.
The AI capabilities of CMS and DAM solutions cannot solve core operational challenges and disjointed workflows. And the content generated exacerbates the potential for misinformation, misbranding, privacy violations, and compliance violations. This situation results in more content being generated at machine speed, resulting in more wasted content. This is unacceptable because in addition to usage-based pricing for AI capabilities, the cost of cloud storage also increases.
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Consumers and buyers are overwhelmed with irrelevant content as the systems driving digital experiences make decisions about what content to display increasingly opaque, but today’s dire state is not irreversible.
Introducing intelligent content
When done well, we define “intelligent content” as content that combines human creativity, AI, and data to learn, understand, and adapt to real-time behavior to self-optimize dynamic experiences and meet engagement goals. Let’s find out why it’s important.
For organizations, intelligent content represents a shift from creating more content to creating smarter content. This reduces waste, improves relevancy, and delivers results that static content can never achieve. Intelligent content includes:
dynamic. Adapt in the moment based on signals from buyers, context, systems, and agents. This is not personalization as we know it. Continuous real-time optimization to meet audience objectives. Generated by existing content technology and agent AI. Existing content and digital asset management technologies are the foundation for abstracted content models, knowledge graphs, and agent layers that power intelligent content. Co-created by humans and machines. Humans will never disappear in intelligent content creation. Rather, they envision, strategize, and create governance guardrails. Machines design, generate, and optimize at scale. This human-machine content creation partnership reimagines roles across design, editing, operations, and analysis. Adopt a new digital operating model that combines B2A.
Organizations that continue to create content specifically for humans and not machines will increasingly lose visibility, relevance, and performance in AI-mediated digital experiences. Systems that build agent content systems based on structure, governance, modularity, and human-machine collaboration will set the standard for the next era of engagement. Start here:
Build for both human and machine users. Create content for humans that stirs emotions. Structure your content so that machines understand meaning, relationships, and context. Develop guardrails for content generation by agents. Treat the AI agent as an active participant in your operating model. Define requirements for accuracy, tone, compliance, and engagement. These guardrails give agents clear instructions and human oversight. Design new operating models for humans and machines. Designers and creators are increasingly defining pattern libraries rather than finished assets. What this means: Machines will now be able to dynamically generate consistent, on-brand content variants. This human-machine partnership will enable humans to lead in a new era of digital content operations.
The original article is here.
The views and opinions expressed in this article are those of the author and do not necessarily reflect those of CDOTrends. Image credit: iStockphoto/Julia Garan
