A new customer experience: How AI is changing marketing

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Content provided by IBM with Insider Studios. In the summer of 1956, 10 scientists and mathematicians gathered at New Hampshire's Dartmouth College to brainstorm a new concept Assistant Professor John McCarthy called "artificial intelligence." According to the original proposal for the research project, McCarthy--along with fellow organizers from Harvard, Bell Labs and IBM--wanted to explore the idea of programming machines to use language and solve problems for humans while improving over time. It would be years before these lofty objectives were met, but the summer workshop is credited with launching the field of artificial intelligence (AI). Sixty years later, cognitive scientists, data analysts, UX designers and countless others are doing everything those pioneering scientists hoped for--and more.


From Watson to Einstein: The AI tech automating the future of marketing

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As tech giants make bigger leaps into artificial intelligence, they see marketers as key customers for a variety of services and are promising more nuance and layers than the technology's early days might suggest. Companies such as IBM, Salesforce and others believe AI has the potential to transform marketing as much as the digital revolution has over the past several years. IBM, which first made an AI media splash in 1997 when its Deep Blue supercomputer beat chess champion Garry Kasparov, has emerged as an early market leader with newer, smarter Watson software. Google is also ramping up R&D spend on AI; Microsoft is integrating AI across its enterprise; Facebook is building out facial recognition AI for basic user experiences and Salesforce is championing a new platform called Einstein to help optimize for individual customer data. In late September, all of these companies and others banded together to create the Partnership on Artificial Intelligence to Benefit People and Society, a group with the objective of addressing opportunities and challenges, along with standards and best practices, for AI developers.


A.I. and Ad Agencies: Bringing Cognitive Intelligence to Clients

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These two industries have collided to augment and even build worlds from scratch, telling comprehensive and compelling stories. Yet one of the most astounding and useful advances comes not from a new type of virtual reality but in how marketers soon will be able to analyze the most sophisticated tool around: the human mind. I'm speaking here of the principle known as "cognitive intelligence," or C.I., which offers a crystal-clear window into the behaviors, wants and needs of the people around us. Cognitive is an umbrella term encompassing numerous aspects of how machine thinking mimics how we as humans think. Terms like machine learning, artificial intelligence, deep learning, adaptive neural networks, etc. all touch on components of what is encompassed in the broader term "cognitive."


Riding the wave of AI: Is your marketing campaign as smart as it can be? – The Nonepaper

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As 2019 gets underway and your marketing plan unfolds, you've probably set some goals for the coming year: We're going to break down the data silos that keep us from understanding our customers. We're going to improve our messaging relevance. We're going to target customers more accurately on their preferred channels What if you could just find the time to make any one of these resolutions a reality? Although the promise of one-to-one marketing has been around for many years, brands still send customers too many marketing messages that are irrelevant, generic or only slightly personalized. The problem is that marketers today have too much data and not enough creative time to respond to soaring customer expectations for a personalized buying experience.


2018: The 'Year of AI and Machine Learning' for Financial Marketers

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Financial marketers must understand the latest artificial intelligence and machine-learning marketing applications to succeed. Not only do consumers expect a new level of personalized communication and engagement, but revenue and cost pressures require a more efficient marketing mix with improved results.