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Smart Implementation of Machine Learning and AI in Data Analysis: 50 Examples, Use Cases and Insights on Leveraging AI and ML in Data Analytics

Now that more companies are mastering their use of analytics, they are delving deeper into their data to increase efficiency, gain a greater competitive advantage, and boost their bottom lines even more.

For call centers, using ML and AI means having speech analytics software in place – in fact, decades ago call centers began using primitive forms of artificial intelligence.

To help your company understand how machine learning and AI in data analysis can benefit your business, we have rounded up examples of smart implementation, insights from the experts, and business use cases to give you the information you need to start using these types of advanced data analysis yourself.

WittySparks is a blog run by creative minds who practice in a host of fields and write about hot topics in digital marketing, content marketing, business, and technology, among other fields.

In this marketing strategy article, Dan Shewan shares 10 examples of companies using machine learning in innovative ways, including image curation at scale, improved content discovery, and to leverage chatbots.

In his ThoughtSpot article, chief data Evangelist Doug Bordonaro explains that you don’t really need to understand machine learning, artificial intelligence, and deep learning to take advantage of them for your business.

@thoughtspot Three key details we like from 5 Ways Machine Learning Can Make Your BI Better: In his Medium article, investor and technologist Nathan Benaich uses his expertise in AI and emerging technology to encourage readers to delve into machine learning.

Their AI Business Use Cases share detailed glimpses into how machine learning makes it possible to automate common data workflow, detect objects by image, and understand text.

They refer to AI and machine learning as “the most important general-purpose technology of our era,” because the machine continually improves its performance without humans needing to explain how to accomplish all its tasks.

The Fatal Flaw of AI Implementation MIT Sloan Management Review leads the way for academic researchers, business executives, and other influencers and thought leaders about advances in management practice, especially those shaped by technology.

In her MIT SMR article, Jeanne Ross warns companies to be cautious about implementing AI because companies that do not insert value-adding AI algorithms into their processes correctly suffer. @mitsmr Three key details we like from The Fatal Flaw of AI Implementation: eeNews Europe delivers news, analysis, product, and design information to the electronics engineering community.

@ciouk Three key details we like from How 11 CIOs are Using Machine Learning to Boost Innovation: After Erik Brynjolfsson and Andrew McAfee published their HBR article arguing AI and machine learning will become “general-purpose technologies,” HBR senior editor Walter Frick sat down with Hilary Mason, the founder of Fast Forward Labs, to discuss how companies can put these technologies into practice and how to take advantage of them. @HarvardBiz Three key details we like from How AI Fits into Your Data Science Team: InnovationEnterprise is the leading global voice in enterprise innovation, providing access to cutting-edge content across nine distinct channels.

In their perspectives report, that provide a comprehensive overview of AI and machine learning and examine how smart apps are impacting small businesses and the implications of the technology on small businesses.

@HITAnalytics Three key details we like from How Healthcare Can Prep for Artificial Intelligence, Machine Learning: Maruit Techlabs is a professional team delivering end-to-end software solutions related to chatbots, mobile platforms, application development, and web analytics.

Their machine learning article explores how the technology boosts predictive analytics, yet only 60% of business leaders who cite growth as a key source of value from analytics have predictive analytics capabilities.

Lukas Biewald’s TechCrunch article asserts that machine learning is forcing massive changes in company operations and explores how businesses use machine learning every day.

@Clickatell Three key details we like from How to Use Machine Learning in Business: Barnard Marr, bestselling author, keynote speaker, strategic performance consultant, and analytics, KPI, and Big Data expert, shares how Walmart uses machine learning, AI, IoT, and Big Data to improve performance.

@BernardMarr Three key details we like from How Walmart Is Using Machine Learning AI, IoT and Big Data to Boost Retail Performance: Edgy Labs is comprised of a group of technologists and successful tech entrepreneurs who specialize in growth hacking, SEO, artificial intelligence, virtual reality, augmented reality, and the Internet of Things.

@edgylabsdotcom Three key details we like from How You Use Machine Learning Everyday and Business Will, Too: Deloitte is a global network of member firms that helps clients achieve their goals, solve complex problems, and make meaningful progress.

Here, Philipp Gerbert, Martin Reeves, Sebastian Steinhäuser, and Patrick Ruwolt share the findings of a report BCG conducted with MIT Sloan Management Review to determine exactly how businesses use AI and establish a baseline to help companies compare their efforts and goals with the technology and to offer guidance for future initiatives.

They also share this article by Scott Hackl, global head of sales for Finacle at EdgeVerve, which presents his argument that banks and credit unions should use Ai and the power of advanced analytics in order to become agile and remain relevant.

She also addresses the ways in which the advanced technology can work for small businesses and investigates several services and products that make AI and machine learning accessible for those businesses.

@Esri Three key details we like from A New Business Intelligence Emerges: Geo.AI: Mary Branscombe’s CIO.com article offers a realistic look at the ways in which machine learning can impact business and the ways in which you can use it today in your company.

In this article, they explore deep learning and machine learning and the ways in which Gartner predicts deep learning will be a critical component of demand, fraud, and failure predictions by 2019. @BusinessTechSA Three key details we like from Using Machine Learning and AI to Add Value to Business: KPI and Big Data expert Bernard Marr’s Forbes article examines the significance of AI, machine learning, and Big Data for B2B companies.

@Forbes @BernardMarr Three key details we like from Why AI, Machine Learning and Big Data Really Matter to B2B Companies: SalesforceIQ delivers relationship intelligence technology to help companies save time and close more deals via smarter selling and better relationships.

Top 45 Artificial Intelligence Companies

Artificial intelligence has exploded in the past few years, with dozens of AI startups and major AI initiatives by big name firms alike.

The New York Times estimates there are 45 AI firms working on chips alone, not to mention the dozens of AI software companies working on machine learning, deep learning and AI projects.

While machine learning is the largest skill cited as a requirement, deep learning is growing at the fastest rate: from 2015 to 2017 the number of job openings requiring deep learning increased 34-fold, the report states.

Consulting giant Accenture believes AI has the potential to boost rates of profitability by an average of 38 percentage points and could lead to an economic boost of US$14 trillion in additional gross value added (GVA) by 2035.

AlphaSense is an AI-powered search engine designed for investment firms, banks, and Fortune 500 companies focused on searching for important information within earnings call transcripts, SEC filings, news, and research.

finished their research 24.5% faster, required 4.4 times fewer searches to accomplish the same research task, and rated the cases they found to bw 20.8% more relevant than those found on a legacy research tool.

The software helps business analysts build predictive analytics with no knowledge of Machine Learning or programming and uses automated ML to build and deploy accurate predictive models quickly.

DataVisor uses machine learning to detect fraud and financial crime detection, utilizing unsupervised machine learning to identify attack campaigns before they conduct any damage.

Freenome uses artificial intelligence to conduct cancer screenings and diagnostic tests to spot signs of cancer earlier than possible with traditional testing methods.

The IPU’s unique architecture allows developers to run current machine learning models orders of magnitude faster and undertake entirely new types of work not possible with current technologies.

It has formed an alliance with seven technology companies from around the world that specialize in gathering different types of health-care data, and will use algorithms to analyze genomic, physiological and behavioral data and provide customized health and medical advice.

It recently released Iris.ai 4.0, which adds the Focus tool, an intelligent mechanism to refine and collate a reading list of research literature, cutting out a huge amount of manual effort.

Lobster is an AI-powered platform that helps brands, advertisers and media outlets find and license user-generated social media content by scanning major social networks and several cloud storage providers for images and video, using AI-tagging and machine learning algorithms to identify the most relevant content.

Instead of self-driving cars, Nauto is an AI-technology designed to improve the safety of commercial fleets today as well as autonomous fleets by assessing how drivers interact with the vehicle and the road ahead to reduce distracted driving and prevent collisions.

The company’s Alme platform powers natural language business products that are continually enhanced through A.I.-powered tools that empower human trainers to assess performance and end-user satisfaction.

OneModel is a talent analytics accelerator that helps HR departments handle employees, career pathing, recruiting, succession, exits, engagement, surveys, HR effectiveness, payrolls, planning, and others, all in one place and in one uniform way.

OpenAI is a non-profit research firm that operates under an open source type of model to allow other institutions and researchers to freely collaborate, making its patents and research open to the public.

It uses data from satellites, drones, balloons and other aircraft to look for answers or insight on things related to the agriculture and energy industries that normally wouldn’t be visible to human eyes.

Its natural language generation system can generate millions of human-sounding variants of marketing at the touch of a button, allowing customers to tailor their copy to targeted customers.

Pointr is an indoor positioning and navigation company with analytics and messaging features to help people navigate busy locations, like train stations and airport terminals.

Their latest initiative, which includes a team of 175 data scientists, uses machine learning to help employees more efficiently perform tasks by simplifying and speeding them up.

Siemens focuses on areas like energy, electrification, digitization, and automation, as well as resource-saving and energy efficient technologies and a leading provider of devices and systems for medical diagnosis, power generation, and transmission.

It gathers and analyzea massive pools of medical and clinical data at scale to provide precision medicine that personalizes and optimizes treatments to each individual’s specific health needs.

One of the largest social media companies to come out of China, they recently founded an AI lab which developed tools to process information across its ecosystem, including natural language processing, news aggregators and facial recognition.

Twilio is a cloud communications platform as a service (PaaS) company that allows software developers to integrate text messages, phone calls, and video calls into applications through the use of various APIs.

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