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Take a Bow for the Next Generation KM

There may be several generations that a KM system appeals to in different ways, but there are no generational differences when it comes to expecting high quality customer service and knowledgeable agents.

Transform Customer Service With Next-Gen Knowledge: Why and How

The consumer has spoken. Forrester Research asked 5,000 of them, "What created the biggest pain when you contacted a business for customer service?" They answered lack and consistency of agent knowledge, followed by the difficulty of finding relevant answers on company websites. So, what is driving this dissatisfaction?

Artificial Intelligence Done Right

Artificial intelligence (AI) has captured the imagination of a wide variety of businesses. I have this image of CEOs in boardrooms around the globe declaring, "We must have AI! Our competitors use AI! We can't be left behind!" There might be some table-pounding associated with this scenario. There will certainly be corporate minions scurrying around to fulfill the AI dreams of their CEO.

AI Guidelines for Businesses: Using AI in Your Own Company

Artificial intelligence (AI) is one—if not the—key technology of our decade. Technological advances in this field are not only fundamentally changing our economies, industries and markets, but are also exerting enormous influence on traditional business practices, many of which will disappear, while others will be transformed or completely reinvented.

Understand. Anticipate. Improve. How Cognitive Computing Is Revolutionizing Knowledge Management

For decades, organizations have tried to unlock the collective knowledge contained within their people and systems. And the challenge is getting harder, since every year, massive amounts of additional information are created for people to share. We've reached a point at which individuals are unable consume, understand, or even find half the information that is available to them.

3 Things to Know Before Starting Your AI Journey

AI-Powered Search Engines—referred to as "Insight Engines" by Gartner and "Cognitive Search" by Forrester—can deliver significant value to organizations these days, provided certain risks are avoided.

From “Searching” to “Finding”: How AI is Unlocking the Power of Unstructured Data

Unstructured data, which comprises almost 80% of any enterprise's data, holds untapped value when it comes to addressing challenges and embracing opportunities.

AI and the Building Blocks of Intelligent Content

The data, information, and analytics economy runs on well-curated, structured data. No matter your industry—having good curated data and content is critical. It's increasingly important as more data and content are generated. Intelligent tools to sift through content are more robust and at the same time, more "needy." That means modern technology platforms, systems, and even content consumers require well-structured data and content to perform well. As most artificial intelligence (AI) practitioners state—"nothing starts without good data."

A Best Practice Approach to Insight Engines: 5 Levels of Insight Engine Maturity

Enterprise search projects start with intentions to provide ‘Google for our organization' but too often fail to deliver on that promise. In our experience, these projects fail due to a lack of sustained effort and governance. The commercialization of next-generation search technologies allows you to fulfill this promise if you take a systematic approach to implementation.

IVRs and AI, Unite!

While interactive voice response systems (IVRs) have been invaluable in reducing contact center costs, we need to be honest: not many are delivering experiences that meet consumer expectations. It's no surprise given the rise of digital channels.

Key Considerations in Maximizing the Value of Cognitive Search

I am a firm believer in The 7 Habits of Highly Effective People, by Stephen Covey. If you've not read this book, it is worth the time. I mention this because my focus at BA Insight is around Covey's second habit, which is, "Begin with the end in mind." Seems simple, right? Well it is, but it's also quite rare. When approaching any enterprise search project, at any phase, I always try to come back to this idea. What is success? When are we done? What does finished look like? These are all different ways of saying, "Make sure you have goals!"

AI-Powered Customer Service: Use-Cases and Real-World Examples

Cognitive/AI technologies for customer engagement are white hot. No wonder professionals, who had removed AI from their resumes, are scrambling to add it back in!

Text Analytics and Natural Language Processing: Knowledge Management’s Next Frontier

Text analytics and natural language processing are not new concepts. Most knowledge management professionals have been grappling with these technologies for years. From the KM perspective, these technologies share the same fundamental purpose: They help get the right information to employees at the right time.

Everything Old Is New Again

I'm entranced by old technologies being rediscovered, repurposed, and reinvented. Just think, the term artificial intelligence (AI) entered the language in 1956 and you can trace natural language processing (NLP) back to Alan Turing's work starting in 1950. Text analytics has its antecedents in data mining. Data mining itself has a long history, all the way back to Thomas Bayes, who died in 1761, and his eponymous theorem that still informs algorithms regarding inference, probability, and predictions.

Keeping It Personal With Natural Language Processing

Look at your organization and consider the unstructured text or audio data you gather and the possible revelations it may hold. That data reflects the voices of those you serve and holds the potential to help you deliver better experiences, improve quality of care and enrich human engagement. There are powerful stories to be told from your unstructured text data. And the best way for you to find them is with natural language processing.

Data Uncertainty, Model Uncertainty, and the Perils of Overfitting

Why should you be interested in artificial intelligence (AI) and machine learning? Any classification problem where you have a good source of classified examples is a candidate for AI. Historically, optical character recognition (OCR) was a difficult problem. We have recently experienced enormous improvement in the performance of OCR because, at least in part, we have a very large collection of already classified examples. Similarly, automatic translation between languages has made tremendous advances because we have access to enormous collections of translated documents that can be used to train the classifier. Other contexts that seem to recommend themselves to machine intelligence and AI learning are concept identification in texts, entity extraction, assigning peer reviewers to submitted documents, sentiment analysis, quality evaluation, and priority assignment.

5 Ways Text Analytics and NLP Make Internal Search Better

Implementing AI-driven internal search can significantly impact employee productivity by improving the overall enterprise search experience. It can make internal search as easy and user-friendly as internet search, ensuring personalized and relevant results.

Governance to Keep Private Information Private

"There's an ongoing paradox when it comes to privacy. On the one hand, privacy matters, and individuals want their personal information to be private. On the other hand, social media, particularly Facebook and Twitter, encourage us to share information that we might otherwise keep private."

Data Privacy Regulations Versus Blockchain Technology

Data privacy refers to the use and governance of personal data, including policies implemented by businesses and governments that govern the collection, sharing and use of an individual's personal information. Information privacy refers to the individual's right to exert some control over their own personal information that is collected and used by others. These two views of privacy are reflected in legislation enacted to govern organizations and, most recently, give more power to individuals.

Flying Into Intelligent Search

An apocryphal story about a pilot trying to land at the Seattle Tacoma Airport (SeaTac) in heavy fog holds some lessons for intelligent search. The pilot of a small plane has no visibility due to the fog. Depending on who's telling this story, an electrical malfunction disabled the instruments, the instruments simply don't work, or the pilot is only rated for visual flight. Thus, the pilot can't figure out how to get the plane to SeaTac.