Let’s start with the definition of "REPLACE," from Merriam-Webster: To restore to a former place or position (e.g. replace cards in a file); To take the place of especially as a substitute or successor; To put something new in the place of (e.g. replace a worn carpet).

Now, let’s check the definition of "ENHANCE": To increase or improve in value, quality, desirability, or attractiveness (e.g. enhanced the room with crown molding); To increase or improve (something); To make greater or better (e.g. the products claim to enhance beauty).

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AI-powered productivity company enaible has released a new survey looking at executive viewpoints on workforce productivity in light of the economic and remote working impact of COVID-19.

It finds that 83 percent of respondents are relying on productivity to improve both margins and profitability, and 83 percent believe that worker productivity will be critical in their companies' ability to recover from the economic impact of the coronavirus pandemic.

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New research into global patent registrations and information on the economic value of patents in the AI sector reveals that Samsung, IBM and Tencent dominate with the highest number of patents filed.

But the study from specialist in the law and economics of IP, OxFirst,  also shows fierce competition between the US and China which overshadows other countries, including those in Europe.

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The future of work is happening now: despite skeptics prophesying growing unemployment rates, AI not only creates new job roles but also changes the employee experience for the better. Assisted with AI tools and analytics, workers no longer have to spend hours (and, consequently, years) on meaningless routines, since they can focus on job aspects that truly bring value.

So how will artificial intelligence transform employee experience and enhance employee engagement? Read on to learn how AI contributes to digital workplace transformation.

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In the past six months, COVID-19 has evolved from a speck on the world radar to a full-blown pandemic. While it has claimed the lives of many and shed a massive spotlight on some of the major issues in healthcare, it has also served as a catalyst for innovation.

As with nearly every element of the healthcare system, applications of machine learning and artificial intelligence (AI) have also been transformed by the pandemic. Although the power of machine learning and AI was being put to significant use prior to the Coronavirus outbreak, there is now increased pressure to understand the underlying patterns to help us prepare for any epidemic that might hit the world in the future.

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Crowdsourced security platform Bugcrowd has released a new report which shows that 78 percent of hackers on its site say AI-powered cybersecurity solutions alone aren’t enough to outmaneuver cyber attacks over the next decade.

The 2020 Inside the Mind of a Hacker report also reveals that 87 percent say that scanners can’t find as many critical or unknown assets as humans.

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When progressive technologies start to deliver on their potential, we can expect a wholesale shift of vendors looking to get on the bandwagon. First the technology enthusiasts and early adopters will come to validate the promises of the newest technology and hone its potential into something viable for the mainstream. Once that is done, the early majority, late adopters and finally, even the skeptics jump in as well.

Finally the time is here for Artificial Intelligence and Machine Learning (AIML) in cyber. There is a widespread move out of the early adopter stage and into the early majority stage of adoption. We need to get onboard if we are going to thwart cybercriminals. The good news is that the industry is recognizing the power and the value of AIML and is finally making investments in this space.

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We hear a lot about what artificial intelligence means for business and research, how it can speed up and streamline tedious processes and so on.

But if machine intelligence is going to be our new normal how does that affect what it means to be human? Emeritus professor of mathematics at Oxford University, John C. Lennox has written a new book exploring these questions. In this exclusive extract he looks at how our brains compare to computers.

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IBM is announcing changes to its AI Fairness 360 toolkit to increase its functionality and make it available to a wide range of developers.

AIF360 is an open source toolkit that contains over 70 fairness metrics and 11 state-of-the-art bias mitigation algorithms developed by the research community to help examine, report, and mitigate discrimination and bias in machine learning models throughout the AI application lifecycle.

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How do you know you had a good day at work? If you did, how would your boss know?

These questions are especially important in the current environment where so many people are working from home without the insight that watercooler discussions, office pop-ins and other face-to-face contact would typically provide. Our reliance on technology to get work done has been growing for decades, but work-from-home orders due to the coronavirus pandemic have accelerated that reliance even more.

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Microsoft and Sony Semiconductor Solutions have announced details of a new partnership that will see the two companies working on AI-powered smart cameras and video analytics together.

The partnership means that Microsoft Azure AI capabilities will be embedded on Sony’s intelligent vision sensor IMX500. Additionally, Sony will create an enterprise-focused smart camera managed app that will be powered by Azure IoT and Cognitive Services.

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Today, 80 percent of digital marketers feel growing pressure to meet customer acquisition and revenue goals, saying they feel like they are "running on a never-ending hamster wheel."

And that’s true: You may be overstretching your marketing muscle to get your customers to find you through organic search -- but it’s something you have little control over and is reactive. Traditional advertising media is becoming more obsolete, but the problem is that many businesses still don’t realize how technology can reverse that. Take the example of the automotive industry, where customer acquisition is still very reactive. The majority of customers still find the auto dealer and brand, and not the other way round. A recent study found that car dealers' first point of contact with more than half of their buyers is when they physically walk into the dealership, essentially leaving it to chance that their dealership or brand gets picked for a walk-in. There’s no doubt that companies across the board are rapidly experimenting with adopting artificial intelligence (AI) in various departments, including business performance and automating the human tasks, the low-hanging fruits. But it’s time you thought about bringing it in to enhance your customer acquisition strategy.

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AI and automation were becoming standard business practices long before the pandemic. As coronavirus shutdowns send shockwaves throughout the economy, though, companies turn to these solutions faster than ever before. Organizations around the world are investing in automated systems to maintain efficiency through the outbreak.

Companies are having to deal with a myriad of complications as a result of the ongoing COVID-19 pandemic. Many have had to scale back and let staff go, and some are facing new and unexpected demands. Tools like AI have become vital to sustainment amid the growing recession.

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Normally at this time of year IBM's annual Think conference would be getting underway. This year's event is, of course, being held digitally and has kicked off with some new announcements.

The first is the unveiling of IBM Watson AIOps, a new offering that uses AI to automate how enterprises self-detect, diagnose and respond to IT anomalies in real time.

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There are privacy concerns following the revelation that confidential data from UK coronavirus patients is being used by technology firms and government to build predictive computer models to help fight the pandemic.

US big data firm Palantir and UK AI startup Faculty are working together to put together what has been described as a "COVID-19 datastore". Pulling together information from government databases as well as information from health services, the project also makes use of highly personal data relating to individual patients according to documents seen by the Guardian.

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