AI in business: looking beyond the hype towards success

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A couple of years ago, there was a joke doing the rounds at technology conferences that AI in business is like teenagers and sex: everyone talks about it, but few actually get it. Is the ribald witticism outdated in 2019? Or has the increased hype enveloping AI that it will magically solve most business problems only further confused executives? So much so they are not engaging with AI's myriad technologies or are left clumsily fumbling with algorithms that fail to perform, while cannier rivals score big. Moreover, has the crucial point that AI in business is best utilised as a means of achieving very specific, narrow-focused objectives, and is not an end point in itself, been obscured by the sheer volume of misleading buzz?


How artificial intelligence can radically transform your business

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"Over 40 per cent of businesses believe that the model they're using today will cease to exist in five years," says Clare Barclay, chief operating officer of Microsoft UK. "All sorts of technology, AI included, is changing the shape of the business landscape." Data from Microsoft's Maximising the AI Opportunity report shows that early adopters of enterprise AI have already seen a five per cent improvement in productivity, performance and business outcomes compared to those that have yet to explore this exciting new field. The AI tools they're working with include chatbots for first-line customer support and sales, forecasting and data simulation algorithms, and automation functions such as process simulation for science and manufacturing, allowing production lines to be made more efficient. The report combines survey data from 4,000 employees and 1,000 business leaders at enterprises with expert guidance, all to help shed light on the rise of artificial intelligence and help businesses approach AI in an informed, ethical and cost-effective manner. How can technology play a role in helping businesses solve problems?


AI in HR: how it could help and what you need to be doing

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That artificial intelligence (AI) is dramatically transforming the human resources industry is somewhat ironic, given the growing global clamour for robots, usurping millions of jobs. HR, though, is not traditionally associated with pioneering nascent technology, and failure to deploy and develop AI could prove a fatal mistake. "When so much time is spent debating how AI and automation might replace roles, it's easy to forget that these very same technologies have a huge role to play in finding, securing and retaining employees," Andrew Lawson, executive vice president and general manager of Salesforce in the UK, points out. "In this era of constant change and digital skills shortages, finding the right talent is more challenging than ever. By using AI and automation, businesses can identify a diverse range of top candidates quickly and easily, and at a pace that keeps stride with the frenzied speed of modern business."


Inside the black box: Understanding AI decision-making ZDNet

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Neural networks, machine-learning systems, predictive analytics, speech recognition, natural-language understanding and other components of what's broadly defined as'artificial intelligence' (AI) are currently undergoing a boom: research is progressing apace, media attention is at an all-time high, and organisations are increasingly implementing AI solutions in pursuit of automation-driven efficiencies. The first thing to establish is what we're not talking about, which is human-level AI -- often termed'strong AI' or'artificial general intelligence' (AGI). A survey conducted among four groups of experts in 2012/13 by AI researchers Vincent C. Müller and Nick Bostrom reported a 50 percent chance that AGI would be developed between 2040 and 2050, rising to 90 percent by 2075; so-called'superintelligence' -- which Bostrom defines as "any intellect that greatly exceeds the cognitive performance of humans in virtually all domains of interest" -- was expected some 30 years after the achievement of AGI (Fundamental Issues of Artificial Intelligence, Chapter 33). This stuff will happen, and it certainly needs careful consideration, but it's not happening right now. What is happening right now, at an increasing pace, is the application of AI algorithms to all manner of processes that can significantly affect peoples' lives -- at work, at home and as they travel around.


Inside the black box: Understanding AI decision-making ZDNet

#artificialintelligence

Neural networks, machine-learning systems, predictive analytics, speech recognition, natural-language understanding and other components of what's broadly defined as'artificial intelligence' (AI) are currently undergoing a boom: research is progressing apace, media attention is at an all-time high, and organisations are increasingly implementing AI solutions in pursuit of automation-driven efficiencies. The first thing to establish is what we're not talking about, which is human-level AI -- often termed'strong AI' or'artificial general intelligence' (AGI). A survey conducted among four groups of experts in 2012/13 by AI researchers Vincent C. Müller and Nick Bostrom reported a 50 percent chance that AGI would be developed between 2040 and 2050, rising to 90 percent by 2075; so-called'superintelligence' -- which Bostrom defines as "any intellect that greatly exceeds the cognitive performance of humans in virtually all domains of interest" -- was expected some 30 years after the achievement of AGI (Fundamental Issues of Artificial Intelligence, Chapter 33). This stuff will happen, and it certainly needs careful consideration, but it's not happening right now. What is happening right now, at an increasing pace, is the application of AI algorithms to all manner of processes that can significantly affect peoples' lives -- at work, at home and as they travel around.