Artificial Intelligence In Knowledge Management – Home : Knowledge base : Knowledge graphing and data modeling and AI : What is artificial intelligence (AI) for business?
Artificial Intelligence (AI) will be the primary source of transformation, disruption and competitive advantage in the rapidly changing economy. Gartner estimates that by 2021 AI will create $2.9 trillion in business value and 6.2 billion hours of worker productivity. But many are already running into difficulties, with the vast majority of AI initiatives failing to meet their expectations or deliver solid returns on investment. For these organizations, the setback usually comes from a lack of foundation on which to build AI capabilities. Enterprise AI projects end up as isolated efforts without the strategic change needed to support business practices and operations across the organization. So how can your organization avoid these pitfalls? It might be helpful to first define what successful AI transformation looks like for the business.
Artificial Intelligence In Knowledge Management
Enterprise AI involves using advanced machine and cognitive capabilities to discover and deliver organizational insights, data, and information in a way that is closely aligned with how humans seek out and process information.
How Knowledge Management Can Reshape Business Operations
To be successful with AI, organizations will first need to identify which of their current business information and data management challenges are suitable for an AI solution, bearing in mind that AI is not a magic wand that can solve all problems corporate. After selecting the right use cases, organizations need to build the foundational skills to structure their information to be machine readable. In our experience, the most appropriate business use cases for advanced capabilities such as artificial intelligence and machine learning include:
Pace and agility of business: The need to address the rapid change and velocity of business by successfully balancing effective change management and user experience with greater personalization, knowledge retention, sustainability and scalability over time is becoming one of the cornerstones of competitive advantage. This, for the enterprise, requires seamless harmonization and autonomous operation of heterogeneous data and information management solutions.
Data dynamism, governance and scale: According to Forbes, 90% of the data and information we have today was created in the last two years. The volume and dynamism of data and organizational content (structured and unstructured) are growing exponentially and organizations need considerable efficiency to obtain meaningful information and exploit it to make better decisions.
Knowledge Management Strategy
Outdated technology and infrastructure: Most organizations were built to organize and manage data and information by business type, department or function. To add to this complexity, many business leaders say their systems don’t communicate with each other. Increasing digitization, coupled with rapidly aging systems, is further fueling these silos and sources of disparate technology solutions to continue to provide meaningful support to business problems.
The meaning and value of AI in the context of business solutions is constantly evolving. Perceptions of AI have ranged from a robot that will answer all our questions to this silver bullet app that will automate processes and increase analytics capabilities to predict and improve our future. However, many companies make the major mistake of assuming an organization can get started and be successful with AI the moment it gets the green light.
From our experience, organizations in a variety of industries are leveraging or experimenting with some form of AI capabilities and seeing remarkable results. However, many have yet to get any value from their AI investments. Here is a selection of reasons:
Ai Is Greasing The Wheels Of Efficiency For Business Management
In a previous blog, I shared how to organize your data by creating a knowledge graph, creating the necessary foundation for a successful AI initiative.
Based on our experience, the following key considerations continue to consistently deliver scalable and adaptable AI capabilities for the companies we work with:
Many large and successful initiatives we’ve led started small, with business goals defined and delivered incrementally to validate assumptions and drive business alignment one use case at a time. Whatever your industry, our strategic approach to AI, user-centric design approach and in-house technical expertise can help you get started with a 1-2 day workshop on enterprise AI fundamentals to help you understand the capabilities of AI and their relevance to your industry. unique business needs, as well as developing a shared vision with a strategy/roadmap to guide practical development. We mentioned earlier that the implementation of structured knowledge management combined with AI algorithms can be a great support for modern customer service. Today we will take a closer look at these two topics and ask what exactly their role is in the big picture. What is Knowledge? This question may sound philosophical, but in the context of business and knowledge management, it is appropriate. Because over the years every company accumulates huge amounts of knowledge. This includes, but is not limited to: glossary and factual knowledge such as year the company was founded, office locations, number of employees, departments, revenue, etc. Process knowledge, i.e. how various internal and external processes are managed (ideally as efficiently as possible); What are the incident handling guidelines? What mandatory meetings are held and how often? What are the standards for our financial reporting? Archival knowledge, including processes that may not be of immediate importance, but may have informational value in the future, e.g. past incident reports, repeating support tickets, or release note records for your products. Unstructured knowledge, such as emails or handwritten notes, that is created all the time without a good way to keep and archive it. This is especially unfortunate, as many essential processes and facts are lost without even being aware of their existence. This list is by no means exhaustive, and in fact there are very few things in your business, externally or internally, that can’t somehow be claimed to be “knowledge” or are somehow involved in knowledge generation. The Problem With Corporate Knowledge Now we have all this knowledge that should be documented, tracked and ideally exploited, but more often than not, companies lack the processes and structures to optimally preserve this knowledge and make it useful for all employees. Data and documents are often stored and hidden on different servers, in different locations, behind different accounts and partly on local hard drives. Ideas about what data can be found are often stuck in the heads of a small number of managers. This rather selective approach to corporate knowledge, as well as the lack of organizational transparency, have a negative impact on efficiency. Considerable amounts of time and effort are spent locating specific knowledge or, in worst cases where it cannot be located, recreating it from scratch. How can you avoid problems like these? If knowledge of your company is spread everywhere, work and progress are significantly slowed down. Tailored Knowledge Management Solutions Today, there are specialized software solutions for knowledge management. These solutions enable you to consolidate, structure, and deliver your business knowledge on a centralized platform. Ideally, companies can use them to provide all of the above files, documents and spreadsheets from one trusted source. Furthermore, knowledge management software often offers advanced features such as labeling different types of knowledge, categorizing it and being able to distribute it according to different roles and user groups. With the right settings, every employee, every team, and every department has access to exactly the knowledge they need and are allowed to see. At all times, it is clear what can be found where and who is responsible and accountable for the currently archived knowledge. The digital customer service advantage A structured knowledge management can bring benefits and added value to the entire organization, but it is in customer service that its advantages can be particularly well demonstrated. Customer service employees, whether on the phone or chat/email, can use a knowledge base to gain faster access to the right information and make it available to customers. At the same time, knowledge management solutions can be used to present pre-selected information to customers in a self-service portal, essentially allowing them to solve their own problems themselves. Proper knowledge management implemented with long-term care leads to faster and better customer service. Another thing to consider is the fact that customer service is subject to seasonal peaks, as well as significant staffing fluctuations. Being able to quickly hire new colleagues and update them on productivity can be a crucial advantage. This is another area where you can reap the benefits of good knowledge management, and it can lead to huge onboarding time savings and, by extension, significant cost savings. The role of artificial intelligence All of these functions, both inside and outside customer service, can be supported and enhanced by AI algorithms. Knowledge management solutions used in digital customer service can be made more effective
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