Can quantum computing help business leaders make effective decisions — and a lot of money? That’s the trillion-dollar question. I have good news. The answer in our present state of reality is yes. In fact, doing so will allow you to make a quantum leap over the competition.

AI implementation should augment human intelligence, not replace humans. That means helping more people to unleash their creativity or do jobs that would otherwise be beyond their cognitive ability. Replacing humans will only increase the pool of people who won’t be able to function in a technology-driven society. For now, let’s use technology to empower humans to be better.

It is time to reframe and redefine the term "smart city." To date, much of the conversation has been about the smart city as an array of sensors that could lead to better garbage handling or better traffic management. It was always built around the idea of civic authorities providing citizens something they were asking for — even if city hall is short on cash and unable to build the desired technology solution.

Most companies have set up systems to collect a steady stream of valuable customer data, such as audience demographics, purchase history, website behavior, recent interactions and more. But just gathering data isn’t the end game—using the data to boost productivity, sales and customer service is the goal in mind.

While many aspects of life remain on hold, many organizations are charging full steam ahead on digital transformation efforts – even giving some pieces a speed boost

Every quarter one of the most closely watched set of figures in the technology industry is spending on cloud computing. While cloud computing is a good indicator of what is happening in tech buying generally in the enterprise, it has also has implications for other areas of enterprise development such as digital transformation.

"A crisis is a terrible thing to waste." Today, many companies are biting the bullet on digital transformation. Jonathon Narvey talks with Future Infinitive co-founders Vaclav Vincalek and Ken Dobell about the smart way to do this -- and why change is the only constant in business.

All tech jobs are in demand. But quality-assurance people for machine learning algorithms are quite scarce—and not just for mobile or Web applications. This is for projects where ML and AI are involved, where they can truly understand and troubleshoot algorithms. Companies need to know that the output actually makes sense. If you don’t know how it works, you’ve got an unpredictable system.