If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
In the post-pandemic, post-Brexit world, businesses of all sorts face a range of new challenges – and many will be wondering if AI-based automation could help them win through. From adding more self-service capabilities for hotel guests through modernising e-commerce fulfilment to replacing missing workers in farming, the opportunities are many, but so are the pitfalls. Given all this, some research that we carried out last year on attitudes to AI – and in particular its subset, machine learning (ML) – is looking even more relevant now than it was then. It gives a picture not just of where AI could add value, but of key routes to get there and of hurdles that must be overcome along the way. As well as asking how our respondents perceived AI and ML, and hearing a lot of weariness with the noise and hype, we asked how well their organisations understood "the AI imperative".
Nearly three-quarters of businesses now consider artificial intelligence (AI) critical to their success, and AI continues to grow in importance across companies of various sizes and industries, according to a new report. And despite turbulent times, more than two-thirds of respondents to Appen Limited's 2020 State of AI Report do not expect any negative impact from the COVID-19 pandemic on their AI strategies. Nearly half of companies have accelerated their AI strategies, 20% doing so "significantly," betting their AI projects will have a positive impact on their organization's resiliency, efficiency, and innovation, according to the annual report. SEE: Managing AI and ML in the enterprise 2020: Tech leaders increase project development and implementation (TechRepublic Premium) Yet almost half (49%) of respondents feel their company is behind in their AI journey, suggesting a critical gap exists between the strategic need and the ability to execute among business leaders and technologists, Appen said. Surprisingly, respondents are not that leery of AI: The report also found that only 25% of companies said unbiased AI is mission-critical.
Artificial intelligence, seen as the cure-all for a plethora of enterprise shortfalls, from chatbots to better understanding customers to automating the flow of supply chains. However, it is delivering the most impressive results to information technology departments themselves, enhancing the performance of systems and making help desks more helpful. At the same time, there's a recognition that AI efforts -- and involvement -- need to expand beyond the walls of IT across all parts of the enterprise. This is one of the takeaways of a recent survey of 154 IT and business professionals at companies with at least one AI-related project in general production, conducted and published by ITPro Today, InformationWeek and Interop. Among those survey respondents with at least one AI application in general production, those with "excellent" and "very good" results comprise 64% of the group -- excellent results account for 23% of respondents and 41% report very good results.
Artificial intelligence, seen as the cure-all for a plethora of enterprise shortfalls, from chatbots to better understanding customers to automating the flow of supply chains. However, it is delivering the most impressive results to information technology departments themselves, enhancing the performance of systems and making help desks more helpful. At the same time, there's a recognition that AI efforts -- and involvement -- need to expand beyond the walls of IT across all parts of the enterprise. This is one of the takeaways of a recent survey of 154 IT and business professionals at companies with at least one AI-related project in general production, conducted and published by ITPro, InformationWeek and Interop. Among those survey respondents with at least one AI application in general production, those with "excellent" and "very good" results comprise 64% of the group -- excellent results account for 23% of respondents and 41% report very good results.
Amid a growing backlash over AI's racial and gender biases, numerous tech giants are launching their own ethics initiatives -- of dubious intent. The schemes are billed as altruistic efforts to make tech serve humanity. But critics argue their main concern is evading regulation and scrutiny through "ethics washing." At least we can rely on universities to teach the next generation of computer scientists to make. Only 15% of instructors and professors said they're teaching AI ethics, and just 18% of students indicated they're learning about the subject.
Artificial intelligence has long caused fear of job loss across many sectors as companies look for ways to cut costs, support workers and become more profitable. But new research suggests that even in STEM-based sectors like cybersecurity, AI simply can't replace some traits found only in humans, such as creativity, intuition and experience. There's no doubt, AI certainly has its place. And most business leaders agree that AI is important to the future success of their company. A recent survey found CEOs believe the benefits of AI include creating better efficiencies (62 percent), helping businesses remain competitive (62 percent), and allowing organizations to gain a better understanding of their customers, according to Ernst and Young.
If companies were already investing in automation and AI technologies before March 2020, they have only accelerated those investments since. No one expected the jolt the COVID-19 pandemic would bring to business. With leaders looking for ways to avoid human contact, machines, software, and new processes that avoid those humans are even more imperative. That's why we've committed a whole day of our Transform 2020 digital conference to the Technology and Automation Summit, presented by collaborative data science software maker Dataiku, on July 15. Hear from industry leaders at Dataiku, Intuit, Chase, Walmart, Goldman Sachs, and more about their journeys and learnings in implementing these technologies, how they unlocked value/ROI from them, and their thoughts about what the future holds.
The image of robots working on a factory floor is being replaced with the reality of robots working in a myriad of industries ranging from healthcare and logistics to retail and telecommunications. How are these robotic systems affecting these industries? This past June TechRepublic Premium surveyed 234 professionals to find out. This ebook, based on the latest ZDNet / TechRepublic special feature, looks at how the explosive growth in robotics is affecting specific industries, like healthcare and logistics, and the enterprise more broadly on issues like hiring and workplace safety. According to the majority of survey respondents (65%), robots and robotic systems do not play a significant role in their industry right now.
In this episode of the McKinsey on AI podcast miniseries, McKinsey's David DeLallo speaks with McKinsey Global Institute partner Michael Chui and associate partner Bryce Hall about the latest trends in business adoption of artificial intelligence (AI). They discuss where the technology is being used most across industries, companies, and business functions; the keys to getting impact from AI investments; and what lies ahead. There's no shortage of predictions about how it could fundamentally change the way we live and work. Over the past few years, companies around the world have been figuring out exactly how AI technologies can improve their performance in a number of areas across their business. But is AI actually delivering significant results? Moreover, what can we expect to see as we move into a new decade of AI use and development? To answer some of these questions today, I'm joined by Michael Chui, a McKinsey partner with the McKinsey Global Institute, who is based in our San Francisco office, and associate partner Bryce Hall from our Washington, DC, office.
Personalized marketing for retail consumers and account-based marketing for B2B customers now have proven value. Online interactions with customers generate large volumes of data for granular learning about consumer behavior for customization of product recommendations, messages, and content. The missing piece is a scalable and just-in-time way to gauge customer preferences and make product recommendations while visitors engage with websites. Deep reinforcement learning algorithms have been trained at the threshold level where they begin to achieve conversion rates to match the costs of data analysis. The touchstone of reinforcement learning (RL) is that it experiments with multiple pathways to achieve the objective of acquiring customers or any other goal.