Just like electricity changed the last centuries for the better, AI will transform this era. AI can help society scale new heights – making us healthier, more prosperous and more sustainable. But as we celebrate and anticipate AI’s enormous potential for economic and social good, there are - as with any new wave of technology - questions and concerns.
Data breaches – a game of Russian roulette, carefully selected targets or exploiting the circumstances?
From a criminal viewpoint, cybercrime has grown into an international and profitable business, one among other business fields. Behind data breaches one can usually find hacker groups supported by authoritarian governments, independent criminal groups or individuals skilled in information technology who have fallen onto the wrong side of the law, whose day jobs involve scanning through corporate web interfaces for gaps the size of a single line of code or malware.
Data virtualization, which has emerged alongside traditional solutions, aims to achieve the same end results data lakes and data warehouses. Which is better: self-service virtualization or a comprehensive data warehouse?
When I was one of the speakers at the webinar “Interactive Assistants - Give the customer the right answer in all situations”, I was asked how to avoid including sensitive data in chatbot logs and the problems it can cause in terms of data security issues.
Smart AI algorithms in all their glory, but without a steady supply of large amounts of reliable data, they are useless. I will describe how data on-site opens great opportunities and cloud solutions so that even smaller companies can keep up.
Many companies have all the customer instruments in place that is needed to transform their business to a circular business model in my opinion. It is therefore a question of reorganizing the customer instruments, to reap the savings circular modelling represents.
The right technology with the wrong culture is not enough – both should be addressed for successful application modernization programs
Technology is only part of the work of modernizing applications. Culture and attitudes also need to be considered, as well as business models that legacy applications were built around.