Many consumers are now used to having generative artificial intelligence (GenAI) tools like ChatGPT put answers instantly at their fingertips. Organizations have typically responded by providing interactive, GenAI-powered chat bots on their websites that can help customers answer common questions and quickly navigate to additional resources.
However, far fewer companies are effectively addressing how the democratization of GenAI has begun shifting the way employees in customer-facing positions use content. In 2026, this will become a trend that businesses can no longer ignore.
Avoiding GenAI Errors in Customer Communications
It really comes as no surprise that employees would expect the same convenience of GenAI-driven answers in their jobs as they have in their personal lives—whether they’re helping a customer at a retail counter or answering a support.
The problem comes when these employees rely on general AI tools that analyze public information from the web, propagate generalized or hallucinated responses outside of a company’s high-valued, proprietary knowledge. This could open the employee up to misinformation, inaccurate recommendations, or worse, even safety issues, all outside of the company’s control—potentially leading the organization to lose customer loyalty and brand value, pay regulatory fines, or face other negative impacts.
If companies haven’t done so already, they need to go beyond delivering instructional courses and provide employees with intuitive AI assistants that can help them get the answers they need in real time. These AI assistants need to be specifically designed to support their jobs and utilize only authorized company data and content.
Providing employees with corporate AI assistants that are easy to access anywhere they are working is the most effective way to combat shadow uses of GenAI. This ensures the integrity of information available to users while empowering employees to become more productive.
Raising the Bar for Reusable Customer Content
Empowering employees with GenAI-driven chat bots will require collaboration with any teams responsible for corporate content and learning and development (L&D) programs. Meanwhile, expectations have evolved from chat bots to full multimedia, multi-modal experiences that assist employees, customers and partners in more ways than ever. In 2026, this will put a higher premium on reusable content.
Imagine descriptions in a how-to manual that can be reused to not only fuel an AI-driven chat bot but also create an AI-powered interactive instructional video and even trigger an AI-based alert if a step guiding customers through a process is missed. This level of reuse is only possible if content is broken down into bite-size chunks—such as topics, components, and learning nuggets—that can be easily mixed, matched and consumed as needed.
Meanwhile, the content to be repurposed for AI often resides in multiple systems that support technical documentation, sales and marketing content, training materials, and other related resources. In addition to relying on structured, reusable content, two investments can help AI tools to access and use distributed learning content more efficiently.
First is applying metadata tags to content to facilitate search and analysis. Anyone involved in learning content creation and management should get trained on best practices for tagging content if they have not already developed this skill.
Second is aggregating existing content from different systems and providing the ability to push it out to a range of information delivery platforms, including AI-driven systems and applications. Organizations may choose to use their existing enterprise content management (ECM) systems or newer offerings that add advanced aggregation capabilities. Either way, these systems should provide out-of-the-box connectors and application programming interfaces (APIs) to link the range of solutions used to deliver content for customers—such as help websites, chat bots, product documentation, knowledge bases, and training videos and materials—whether commercially available or homegrown.
Many companies have already adopted either a structured component or topic-based approach for developing their content, giving them a jump start in unlocking the value of GenAI. For those that have not yet taken this step, now is the time to follow their lead as a critical foundation for ensuring the effectiveness, scalability and maintainability of their AI-powered customer experiences.
Increasing Focus on Content Curation
At the same time, the sheer volume of content created by GenAI doesn’t solve many of the problems faced by enterprise teams seeking to avoid duplication and ensure that information is consistent, accurate and valid.
Therefore, experts will be needed to assemble existing content components or topics into different communications vehicles for consumers and employees with customer-facing roles, for example chat agents, webinars, podcasts, and how-to guides, to name a few. These curators will also need to manage this content to reduce duplication, maintain consistency, understand and address content gaps, and ensure that vast stores of content can be easily searched.
Moreover, GenAI tends to leapfrog all the steps that enterprise content groups have worked so hard to implement in terms of quality control, peer review, misinformation protection, etc. So, content curators will also need to maintain and enforce quality safeguards while also owning the process of feeding curated content efficiently to different communications vehicles and AI tools downstream.
The good news is that many corporate content creators already have the fundamental skills to become content curators. It’s more about making the cultural mind shift.
Conclusion
The key to putting relevant, AI-driven content at customers’ and employees’ fingertips is to start with component- or topic-based content; structure this information for reuse; and then curate it for relevance, quality and consistency. By adopting these practices, organizations can maximize the effectiveness, scalability and maintainability of their GenAI-powered content while ensuring accuracy and consistency for both customers and the employees who support them.