Recognizing and solving for AI bias
AI is unlocking tremendous value for businesses by solving many last-mile automation problems that previous waves of technology could not address. But just like any technology early in its evolution and application, there are a few...
Top 3 practical considerations for AI adoption in the enterprise
More companies are investing in AI. However, to succeed, they need to make practical considerations for explaining its reasoning, low-data density environments, and the need for richer knowledge graphs.
The path to explainable AI
As more and more enterprises use artificial intelligence to make decisions on their behalf, governance is critical, and traceability into AI reasoning paths key to build trust from customers, employees, regulators, and other key...
How to determine the value of enterprise data
The value of data is getting increasing attention from boards and CXOs as digital technologies disrupt entire industries, so getting a handle on the enterprise value of data is becoming more important for most corporations.
Leveraging analytics across the enterprise
Unlocking the value of data will be more and more a part of the digital transformation of enterprises.
5 top trends driving digital agendas in 2018
Digital technologies will continue to offer companies the opportunity to radically alter their business models, transform operations and create better customer experiences.
Game changer or jobs at risk? AI and work of the future
While much of the discourse around AI and automation has been concerned with the looming threat to the workforce, this ignores the fact that history has shown disruptive technologies often lead to progressive evolution.
Defining AI: reasoning, interaction and learning
What is possible today is represented by the intersection of these three fields. Progressive CIOs and other executives must pick the business use cases that are at this intersection to get the most out of AI.
IoT architecture: To run on the cloud or not?
Industry experts expect the Internet of Things to generate about 44 trillion gigabytes of additional data worldwide by 2020. Which drives us to the central question: What is the best technology architecture to adopt to plan for this...
Why RPA implementations fail
RPA hype is at an all-time high, with an alphabet soup of providers and offerings. Industry watchers are declaring RPA a must-evaluate technology, and some are heralding the start of the next industrial age. Software providers on both...
Bimodal transformation: Avoiding five common pitfalls to success
A bimodal transformation approach can instill innovation, provide a less-risky way to experiment, and encourage change. But it's critical that companies stay focused on a well-defined project plan and keep sight of any potential...
Three ways to make sense out of dark data
To address the challenge of dark data, use artificial intelligence to unlock unstructured data, deploy modular and interoperable digital technologies, and build traceability into core design principles.
How computational linguistics went from Cold War communications to transforming enterprise work
The Cold War is often cited as the starting point for the scientific work around natural language processing (NLP) that has since evolved into computational linguistics, an artificial intelligence (AI) technology now in commercial...
