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Top 5 Digital Transformation Trends In Manufacturing

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Today, these advanced algorithms are transforming the way the manufacturing industry collects information, performs skilled labor, and predicts consumer behavior. Smart factories with integrated IT systems provide relevant data to both sides of the supply chain more easily, increasing production capacity by 20%. Robots and other automated technology are also integral in improving speed and efficiency, allowing manufacturing companies to "optimize production workflows, inventory, Work in Progress, and value chain decisions." With this new level of predictive accuracy comes an improvement in condition monitoring processes, providing manufacturers "with the scale to manage Overall Equipment Effectiveness (OEE) at the plant level increasing OEE performance from 65% to 85%."


AI: marketing's friend or foe?

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Many of us will encounter a marketing virtual agent on a near daily basis when being asked qualifying questions or providing automated answers to standard questions, however their potential goes far beyond this and presents exciting opportunities at every stage of the customer journey. Voice assistants create an opportunity to interject compelling content into everyday situations, such as recipes in the kitchen, linked to an ecommerce platform. Recent research has shown that monotonous, repetitive tasks triggers automatic decision making and makes employees more likely to behave unethically. Sure, inertia and lack of technical expertise play a part, but many marketers hold a major question mark over AI's ability to perform a key part of their role: EMPATHY.


AI will fundamentally change how we manage content

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Perhaps it's not a coincidence that just this month, Box announced a partnership with Google to bring AI via image recognition technology to the cloud content management firm. Last week, M-Files, a hybrid content management solution, announced it was acquiring Apprento, a Canadian startup that uses natural language processing (NLP) and natural language understanding (NLU) to provide semantically based intelligent summaries. "In Apprento's case, we were first attracted to their practical experience with applying natural language processing (NLP) and natural language understanding (NLU) to practical business needs. All of these moves suggest that we could be in the midst of an industry shift that Levie and Patel alluded to, as content management firms try to use intelligence to make sense of the increasingly large amount of content moving into the enterprise.


Is Fashion Ready for the AI Revolution?

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In the last few years, a trifecta of cheap, ubiquitous, powerful computing; big data; and the development of deep learning have triggered a revolution in artificial intelligence. The computing devices that now fill our everyday lives generate large data sets, which "deep learning" algorithms analyse to find trends, make predictions and perform specific tasks, such as identifying specific objects in an image. Edited let this loose on a bank of data on 60 million fashion products, collected from retailers and brands in over 30 countries, in over 35 languages: the result is a searchable database of organised, structured information on each of these products. Thread, an online personal styling service, combines human stylists with machine learning algorithms.


Banking's One-to-One Future is Finally Possible

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Almost a quarter century ago, a book was written about how organizations would focus on share of customer as opposed to share of market, building a personalized collaboration driven by big data. Instead of watching as non-banking organizations or fintech start-ups set expectations, the banking industry can now offer individualized engagement, integrating advanced analytics, artificial intelligence, machine learning, robotics and even blockchains to build a cognitive bank. The banking industry continues to be challenged be a low interest rate environment, intense competition from new market entrants, and heightened consumer experience expectations set by highly digital non-bank organizations. It is also proposed that cognitive systems can continually build knowledge and learning, providing the insight needed to increase efficiency and effectiveness throughout the organization.


Banking Technology Vision 2017

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Freedom to innovate THOSE THAT DO EXPECT MORE: Opportunity to develop standards that others follow Expanded opportunities for trusted partnerships 6. www.accenture.com/bankingtechvision DESIGN FOR HUMANS CUSTOMER JOURNEYS NOW RUN INSIDE AND OUTSIDE THE BANK Digital banking models, such as ecosystem platforms and channels not owned by banks, will bring consumers from outside the sphere of the bank's knowledge. WORKFORCE MARKETPLACE ON-DEMAND TALENT AS A TRUE BANKING INNOVATION Create an agile workforce to access sought-after skills, knowledge and experience as-needed for more flexible ways of working. DESIGN FOR HUMANS CUSTOMER JOURNEYS NOW RUN INSIDE AND OUTSIDE THE BANK Digital banking models, such as ecosystem platforms and channels not owned by banks, will bring consumers from outside the sphere of the bank's knowledge. WORKFORCE MARKETPLACE ON-DEMAND TALENT AS A TRUE BANKING INNOVATION Create an agile workforce to access sought-after skills, knowledge and experience as-needed for more flexible ways of working.


IBM Watson: Why is it such a big deal?

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In January this year, a Japanese insurance firm replaced 34 of its employees with an AI system based on IBM Watson. One of the reasons why IBM Watson is so important is because IBM has opened Watson up to businesses and developers. IBM opened up Watson application programming interfaces in 2015, allowing developers to use the cloud-based artificial intelligence system with their own programs. Cognitive intelligence, artificial intelligence, and virtual reality all present opportunities for businesses to serve their customers in new and exciting ways.


How Artificial Intelligence (AI) is disrupting and enhancing marketing

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Jarther Taylor There are multiple ways to think about AI, but I'd describe it as a nexus of data modules; plus the associated data with those modules, and the computing power to run those modules at high speed to deliver a human experience. There's the concept of general intelligence and organisations like Google that are working on things like'Deep Mind' which is an intelligence that has human-like and brain-like capabilities that it can learn skills and insights in one area and apply them to others. Jarther Taylor The biggest opportunity within marketing is understanding that industries are going to be disrupted by AI and for those currently embracing it, they will be ahead of the curve in terms of efficiency and productivity. Kristi Mansfield Some of the most interesting applications of machine learning, predictive analytics and algorithms are in the high-frequency trading industry.


Business and Technology News - ITP Report

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Insurance executives believe that artificial intelligence (AI) will significantly transform their industry in the next three years, with insurers investing in AI to empower agents, brokers and employees to enhance the customer experience with automated personalized services, faster claims handling and individual risk-based underwriting processes, according to Accenture's Technology Vision for Insurance 2017. At the same time, however, the report found that insurers face challenges integrating AI into their existing technology, citing issues such as data quality, privacy and infrastructure compatibility. Titled "Technology for People," the report is based on the insights of a technology advisory board, interviews with industry technologists and a survey of more than 550 insurance executives across 31 countries. According to the report, three-quarters (75 percent) of insurance executives believe that AI will either significantly alter or completely transform the overall insurance industry in the next three years. One-third (32 percent) believe that their own company will be "completely transformed" by AI within that timeframe, and an additional 39 percent believe that AI will "significantly change" their company.


Where Does Automated Customer Benchmarking Make Sense?

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A customer benchmarking engine is an emerging technology which uses an artificial intelligence approach to automate the reasoning that underlies data-driven benchmarking. Its benefits are discussed here, there, and elsewhere. Briefly, it uncovers comparative insights on customers which empower customer-focused employees to be more proactive, or which are shown directly to those customers as a premium information service. The business benefits include churn reduction, market differentiation, extra revenue, and deeper customer relationships. But, automated customer benchmarking doesn't always make sense.