As technology continues to evolve, so does the future of service operations and in particular how knowledge can improve productivity and knowledge worker outcomes. Advancements in natural language processing (NLP) and deep learning will make AI-driven operations even more intuitive and human-like. The future of operations requires a seamless integration between AI and humans to create and deliver exceptional knowledge worker experiences. My recent report, Generative AI: What It Means For Knowledge Management, highlights some of the significant influences of generative AI (genAI) in an agile knowledge management (KM) practice.
This year I’ve been writing a lot about agile knowledge management. Forrester defines it as:
An adaptive practice that continuously and iteratively captures, shares, and improves knowledge to keep pace with the changing needs of the business, with demonstrated results within a cultural structure where leadership, management, staff, and technologies all work seamlessly toward a common goal of improved agility of decision-making and innovation.
My report on genAI’s impact on KM directly ties to the success of agile knowledge management in four key ways.
1) Connectivity To Knowledge
Agile knowledge management requires a light and lean approach. To enable this transition, tech leaders need the right technology that can support the capture of knowledge where people work.
ChatGPT can be an advanced interface for accessing organizational knowledge bases, enabling users to retrieve information quickly and intuitively. Our typical search approaches are coming to an end. Rather than facing an endless list of results and looking for the right answer, users can ask questions in natural language and receive precise answers sourced from vast repositories of documents, databases, and past interactions by interacting with ChatGPT. This reduces the time spent searching for information and increases efficiency, especially in fast-paced environments where quick access to accurate information is crucial to the decision-making process.
2) Collaborative Knowledge Sharing
Trust is at the heart of a successful agile knowledge management practice. The demand for knowledge to be shared within the organization is high, but “knowledge is power” has remained a habitual mantra for knowledge workers, hindering transitions to a successful agile knowledge management practice. Flow of information is at the core of driving transformation, and reducing friction in any form (culture, trust, technology, etc.) needs to be a priority.
ChatGPT can act as a facilitator for this process. It can summarize meetings, extract action items, suggest resources based on discussion topics, offer insights from previous projects or experiences, and even draft a new knowledge article from a transaction with an employee or customer. Leveraging generative AI helps create a more connected and informed workforce where knowledge is dynamically shared and updated, fostering a culture of continuous learning and adaptation. With so many public examples of data exposure, enterprises will need to trust that their information is secure and not being publicly shared to invest in genAI as a way to build productivity. Building trust and acceptance among knowledge workers will require effective communication, transparency, and education about the capabilities and limitations of genAI.
3) Adaptive Learning
Agile knowledge management is not a bottom-up or a top-down approach but one where the organization concurrently moves toward business-defined outcomes with a clear framework for decision-making. Organizations must shift to co-creating knowledge, embracing the idea that the more people contribute their experiences and knowledge, the higher the overall value.
In agile environments, continuous learning and adaptability are essential. ChatGPT can answer queries related to specific tasks, explain complex concepts, and even guide users through new processes or tools. An on-demand learning approach helps users quickly acquire and apply new knowledge, keeping pace with the agile transformation and evolving needs. Connections between knowledge workers happen more organically and dynamically — where trust is the only barrier to sharing information across the organization.
4) Improve The End-To-End Experience
The value of agile knowledge management is best measured in knowledge worker productivity and satisfaction. Early experimentation can drive significant gains in the employee experience. Generative AI is revolutionizing operations, providing businesses with a powerful tool to improve team productivity and the knowledge worker experience. Embracing this technology can significantly elevate the quality of service operations, propelling businesses into a future where AI and human collaboration redefine the knowledge worker’s experience.
Have questions? That’s fantastic. Let’s connect and continue the conversation! Please reach out to me through social media or request a guidance session. Follow my blogs and research at Forrester.com.