Artificial Intelligence (AI) is already changing the landscape of business irrevocably. The error rate for machines with certain perceptive tasks stood at thirty percent barely seven years back, but has now dropped to between three and five percent. Even humans have a five percent error rate. While machines or robots may not be ideal for driving, or face recognition or for credit decisions, even humans don’t always get their decisions correct. This newer trend is rectifying Polanyi’s Paradox as it was previously understood. Companies are taking advantage of the enormous quantities of data now generated to procure authentic business intelligence about their operations. Recently a company after conducted training sessions collated the entire data which will soon become a set of records for such future sessions. New business models will emerge out of this automation that is getting generated.

Source:https://hbr.org/ideacast/2017/07/how-ai-is-already-changing-business?utm_medium=email&utm_source=newsletter_daily&utm_campaign=dailyalert&referral=00563&spMailingID=17697807&spUserID=OTY0OTMwNTk5NwS2&spJobID=1061524157&spReportId=MTA2MTUyNDE1NwS2

Uploaded Date:31 July 2017

When the term Artificial Intelligence (AI) was first coined back in 1955 by mathematician John McCarthy, a lot was initially made out. It was predicted in 1957 that within a decade, computers would be able to beat humans in chess, whereas in reality it took them four decades. But over the past few years AI especially Machine Learning (ML) has really caught up. Technologies have proven to be the significant drivers of business over the past two and a half centuries. Especially the general-purpose technologies such as steam engine, internal combustion engine and electricity have given rise to significant business innovations leveraged by the likes of Wal-Mart, Uber and UPS among others. ML has particularly achieved breakthroughs in two broad ways- perception and cognition. Perception includes the identifying patterns and predicting moves accordingly. One such benefit has been in voice recognition done via digital assistants such as Siri and Alexa. Perception also includes image recognition as done frequently on Facebook and visual systems in use for self-driving cars. Cognition includes problem solving post the initial analysis. Google’s Deep Mind is one such example and IBM has an ML aided system that helps it in detecting and subsequently preventing money laundering.

Source:https://hbr.org/cover-story/2017/07/the-business-of-artificial-intelligence

Uploaded Date:31 July 2017

According to a recent study, the business consulting industry in the US alone is worth sixty billion US dollars. The consulting firms’ advice is especially sought on activities such as budgeting, allocation of capital, human resources and corporate strategy. While these consultants have gained a certain expertise in this, a lot of tasks can eventually get automated using Artificial Intelligence (AI). It is estimated that the work which four consultants can together perform on excel spreadsheets can be done quicker by a single robot using AI. This trend will be a difficult pill to swallow for the big consulting firms such as McKinsey, BCG and Bain. The top tech platforms such as Apple, Amazon, Google, Facebook and Microsoft have created AI based products for aiding clients in customer engagement and marketing. Even imbalances and human error trends such as politicizing the workplace are getting freed up using AI in the human resources arena. It has also been observed that capital allocation is often unequitable with the same departments racking up the funds year-on-year. This trend is also getting rectified. In the near future Quant Consultants or Robo advisers are set to disrupt the world of consulting.

Source:https://hbr.org/2017/07/ai-may-soon-replace-even-the-most-elite-consultants

Uploaded Date:31 July 2017

Artificial Intelligence (AI) is going to affect the world of digital marketing and advertising enormously in different ways. One such way is in robotic process automation which as the name suggests automates large manufacturing tasks being used already by the likes of GE, ABB and Seismic. Another aspect AI is used in is speech recognition. Another is biometrics. A fourth area is Natural Language Processing (NLP) and Text Analytics. Here digital assistants collate vast data to predict the next phrase of content to be written. Due to the vast data now being collected, AI is helping in generation of business intelligence which is firther giving rise to informed decision making. Virtual agents such as Siri, Bixy, Jarvis and Alexa are being used by several top IT companies such as Apple, IBM, Google, Amazon and Microsoft. A lot of these companies have also actively invested time and money into machine learning platforms.

Source:http://www.huffingtonpost.com/entry/what-is-ai-and-how-it-will-affect-our-200-billion_us_58eba189e4b0ea028d568b4c

Uploaded Date: 20th May 2017

Human beings have the ability to process some information without being specifically told. This is part of the instinct developed over millions of years’ evolution. While this is called common sense among humans, machines need to be specifically told, hand-held rather at every step. Now things are however changing thanks to the influx of Deep Learning. At Facebook’s AI Lab and on Amazon’s Echo, Deep Learning principles are being applied. Deep Learning would not have been possible without the advent of Big Data, so much of which is now available that it is easier to process cognitive information. Even Microsoft has developed a tool using Deep Learning that seamlessly translates English in to Mandarin with an error rate of barely seven per cent. Voice assistants like Siri or Alexa also use such capabilities. Deep Learning involves neural networks similar to how human beings are structured. We are going through the phase of Deep learning OS 1 version. Major innovation is taking place in software. The design of neural networks for example is evolving. A marketplace is also developing to reuse them. Similarly, the hardware is evolving to combine the optimum mix between physical assets and Cloud based resources.

Source:https://hbr.org/2017/01/deep-learning-will-radically-change-the-ways-we-interact-with-technology?

Concepts such as e-learning and Artificial Intelligence (AI) have already made massive inroads in to corporate training. In fact for every dollar invested by company on online learning, there is a thirty times increase in productivity. Two-fifths of new recruits who receive poor training during their first year at a company, end up quitting. Also two-thirds of workers surveyed claim that training and development is most important part of the workplace policy. That is why investment on training has topped seventy billion dollars in the US alone. It is also considered among the top three non-financial motivators for three-fourths of employees. This trend is particularly strong among the millennial generation, a staggering eighty seven percent of whom confirm its due importance. However a talent research assessment carried out by Raytheon confirms that a mere seven percent of learning organizations are using predictive analytics in training. Automation cannot yet be considered complete as even now computers cannot be relied upon to execute tasks without any human interference. Gut feeling still plays an important role.

Source:http://www.forbes.com/sites/steveolenski/2017/02/06/why-c-levels-need-to-think-about-e-learning-and-artificial-intelligence/#1c9fc0a71d69

Streaming analytics is the latest rage among marketers using Big Data for solutions. It helps in pricing analysis, customer segmentation, marketing campaign results and deciphering coherent business intelligence on user trends. Customer profiles get tracked against real time live events. Detailed servicing options are provided to the customers as this model takes its customer-centricity very seriously. There is even a social media engagement during the journey. Streaming analytics may be used in various fields such as insurance, retail and finance. It is even being used to identify errors in the Internet-of-Things (IoT) chain. It can even be used to detect fraud. Unlike a lot of other data based strategies, streaming is relatively economical. Amazon has already tried its pilot project with over a million unique users.

Source:https://martechtoday.com/introduction-streaming-analytics-marketing-customer-engagement-194452

Digital marketing has become much more complicated now. Earlier keyword optimization would allow any brand to get noticed by Google, but now it is robots who control the flow of content. Thus marketers will need to work with robots and understand their algorithm to succeed in this. Thus marketing automation must be used to email clients using Google or Microsoft’s software while social media automation software can have a similar impact on Facebook or Twitter. Mobile marketing automation can help companies handle Apple’s operating system. Moz does a detailed analysis on keyword ranking and even rating of pages as per Google’s listing. Google has now started gauging the power of Artificial Intelligence to provide solutions to technology vendors. Rank Brain even contends that Google now uses deep-learning capabilities. Content is then delivered accordingly.

Source:https://martechtoday.com/robots-gatekeepers-customers-194472

A Japanese life insurance company Fukoku Mutual Life has slashed the jobs of more than thirty employees, replacing them with robots armed with Artificial Intelligence (AI). This business innovation will apparently save Fukoku hundreds of millions of yen annually. The AI system is based around IBM’s Watson Explorer system. Another firm Dai-Ichi Life had earlier introduced a similar move. Due to Japan’s ageing population and high prowess in robotics, the country is primed for growth in this field. Soon robots using AI may be a factor in politics as well, helping bureaucrats cut through routine work procedures. Their introduction hasn’t been all smooth as an earlier experiment at a university’s testing system using them backfired.

Source:https://www.theguardian.com/technology/2017/jan/05/japanese-company-replaces-office-workers-artificial-intelligence-ai-fukoku-mutual-life-insurance

A new tool called Afiniti has been developed to help call centre employees using the power of Artificial Intelligence (AI). It records huge amounts of data to generate coherent business intelligence about thousands and eventually millions of customers as well as all its call centre employees. The data is processed to draw conclusions on tastes, preferences or requirements of the customer base. Customer’s phone numbers are used to study behavior and usage patterns across the board. Their social media usage trends on Facebook, Twitter and LinkedIn are also assessed. In addition, the demographic data on gender, age, ethnicity and parenting status are also collated. On the other hand, Afiniti also records the call details, and transaction records of the employees so that they can best be trained on their shortcomings while further leveraging their existing skills. The specific machine learning abilities of the tool, allow it to process granular bits of data to form meaningful information ready to use.

Source:https://consumerist.com/2017/01/06/calling-customer-service-an-ai-is-picking-the-agent-thats-best-for-you/

Artificial Intelligence (AI) and Machine Learning will eventually replace a lot of sales jobs and in fact the process has already started. But instead of completely eliminating jobs, what they will do is to modify them. Business research conducted by Demand-base throws up some startling trends. While a significant eighty percent of marketers surveyed, believe that AI will revolutionize marketing, barely a fourth of the total are confident of their own abilities. An even lower tenth of the sample confirms that AI is being used at their present organization. This provides a conundrum as marketing leaders acknowledge AI’s increasing importance, they aren’t themselves at the cutting edge of its implementation. These leaders in general also voiced some common challenges to with AI’s implementation. One was setting up corporate training programmes involving AI for its employees as most were alien to the concept. Another was the difficulty in establishing metrics to measure. Also integrating AI with existing suite of technologies was proving to be a challenge. Thus in order to leverage the full potential of AI, business leaders especially those from marketing need to take a hands-on role themselves.

Source:http://www.forbes.com/sites/steveolenski/2016/12/14/80-of-marketing-leaders-say-artificial-intelligence-will-revolutionize-marketing-by-2020/#66a3e03521e1