Decision Intelligence News
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Decision Intelligence News
AI/BI/CI/DI: Decision intelligence (DI) solves the world's most complex problems by connecting actions to outcomes.  It connects collaborating human decision makers to knowledge and also to technologies like machine learning, AI, deep learning, visual decision modeling, complex systems modeling, big data, predictive analytics, UX design, statistical analysis, business intelligence, business process management, causal reasoning, evidence-based analysis, and more. See https://en.wikipedia.org/wiki/Decision_Intelligence. For an overview, see the webinar at http://youtu.be/XRTJt3bVCaE, http://www.lorienpratt.com, and the Decision Intelligence group: http://www.linkedin.com/groups?gid=205078.   Also, my company offers DI and machine learning consulting services.  See http://bit.ly/1X8O2zF to learn more.  Don't miss the latest DI news! Sign up at subscribe.decisionintelligencenews.com.
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Scooped by Lorien Pratt
February 20, 2019 12:46 PM
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Retail AI: Death By A Thousand Cuts

Retail AI: Death By A Thousand Cuts | Decision Intelligence News | Scoop.it

"When people say 'AI software', what do they really mean? This is a critically important question to understanding the impact that AI can have on the retail industry (on any industry, really), and a significant source of the gap that exists between AI hype and reality.

 

"While McKinsey focuses on AI types of classification, prediction, and generation, I’ve found it more useful to look at natural language processing, computer vision, and prediction. But each of these are umbrella terms for lots of what amount to 'micro-capabilities', which is an important limitation when thinking about AI. Artificial General Intelligence (AGI, but sometimes referred to as Human-Level Artificial Intelligence) is at least 20 years off, according to experts in the field, and possibly 50 years. And both ends of the estimate acknowledge that some kind of breakthrough that we have not currently achieved would have to happen before we can get there – there is no current known path to achieving AGI."

Lorien Pratt's insight:

AI systems can be applied to human interactions, but the key to teaching machines how to intuitively read human behavioral cues still remains unknown. After all, how can an algorithm accurately interpret variables as subjective as speech inflection? With this in mind, how can 'Human-Level Artificial Intelligence' be viable within our lifetimes if we don't know how to get there yet? The capabilities of AI technologies are expanding at an incredible pace, but there is still so much we need to discover and explore before our machines will be able to know how we feel by the sound of our voice.

Scooped by Lorien Pratt
February 18, 2019 2:11 PM
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10 Ways AI & Machine Learning Are Revolutionizing Omnichannel

10 Ways AI & Machine Learning Are Revolutionizing Omnichannel | Decision Intelligence News | Scoop.it

"For any omnichannel strategy to succeed, each customer touchpoint needs to be orchestrated as part of an overarching customer journey. That’s the only way to reduce and eventually eliminate customers’ perceptions of using one channel versus another. What makes omnichannel so challenging to excel at is the need to scale a variety of customer journeys in real-time as customers are also changing.

 

"89% of customers used at least one digital channel to interact with their favorite brands and just 13% found the digital-physical experiences well aligned according to Accenture’s omnichannel study. AI and machine learning are being used to close these gaps with greater intelligence and knowledge. Omnichannel strategists are fine-tuning customer personas, measuring how customer journeys change over time, and more precisely define service strategies using AI and machine learning. Disney, Oasis, REI, Starbucks, Virgin Atlantic, and others excel at delivering omnichannel experiences using AI and machine learning for example."

Lorien Pratt's insight:

Omnichannel is a strategy that uses a variant of systems thinking to understand the desires and needs of customers in various retail settings, as well as in many B2B environments. Machine learning and AI are providing greater understanding of these desires and needs and assisting in the decision-making necessary to provide customers with an optimal experience, thereby increasing satisfaction and sales while reducing unpleasant experiences and customer churn.