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Artificial Intelligence

Artificial Intelligence (AI) has long disappointed in its actual business implications in spite of the enormous potential inherent from day one. Now, finally it is emerging out of its own shadow by providing genuine business value. Algorithms have now cracked human speech patterns and can even recognize objects or optical patterns. Three major events brought out AI’s success to the wider public, beginning with chess world champion Garry Kasparov’s loss to the IMB-developed computer- Deep Blue. IBM’s Watson and Google’s self-driving cars were the other two. AI has shifted the traditional notions of competitive advantage by creating massive value out data warehousing, as this data is further used by digital giants such as Google, Uber and Facebook to gain business advantages. AI is also providing in-depth customer access through this data, providing cutting-edge business intelligence on user requirements. Capabilities have also jumped up accordingly as AI can now process human language. Any AI implementation into work needs to look at four major applications which are- customer needs, sources of data, advances in technology and the decomposition of processes.

Source:https://www.bcg.com/publications/2017/competing-in-age-artificial-intelligence.aspx?linkId=45055693

Uploaded Date:12 March 2018

While Artificial Intelligence (AI) has been around for a while now, it has disappointed making extravagant promises for decades. Now, finally inputs of genuine worth are beginning to get noticed. Algorithms are getting more accurate, computers faster and robots more reliable, but none of this would have been possible without its main fuel at the back. That is the billions of Gigabytes of data warehousing now being done which is behind this growing sophistication and accuracy. The entrepreneurial drive using such capabilities is now exponentially higher than what was even a few years back. It is now driven by tech giants such as Amazon, Baidu, and Google. The early adopters of AI technology are reaping in the benefits, so even those who took time are now either implementing, or still unsure whether it fits into their respective business models. A study was conducted by the McKinsey Global Institute (MGI) to understand the feasibility of AI involvement in various industries, and early signs suggest that it will work well. While USA is the top source for absorbing AI investments, with China a distant second, the rest of the world is catching up fast. South Kore and the UK want to develop AI clusters to encourage such tech-based businesses.

Source:https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/how-artificial-intelligence-can-deliver-real-value-to-companies?cid=soc-web

Uploaded Date:01 March 2018

Artificial Intelligence (AI) is not longer the sole preserve of tech geeks, but is being used in several day-to-day operations especially those involving customer experiences. One such recent implementation was a chatbot used by 1-800 Flowers which used an algorithm to speed up the customer experience. Retail firm North Face uses IBM’s Watson interface to gauge business intelligence on customer requirements before curtain a personalized shopping experience for them. UK’s Dixons Carphone even provides insurance advice using an AI powered chatbot. Domino’s Pizza uses Facebook Messenger to conduct its digital marketing conduits. Even fraud gets detected by Ticket master. Black Diamond’s equipment is used to help customers ski while also getting a personalized experience. Spotify gauges personal preference using AI to provide the range of music best suited to the particular user. The China Merchant Bank uses the We Chat Messenger to handle customer queries. AI helps Google Photo to tag users whose photos have been identified. A highly interesting use of predictive analytics is done by KFC. They have a facial recognition software powered by AI to actually predict orders.

Source:https://www.forbes.com/sites/blakemorgan/2018/02/08/10-customer-experience-implementations-of-artificial-intelligence/#32e4333b2721

Uploaded Date:27 February 2018

Artificial Intelligence (AI) is set to have a multi-pronged impact this year. First of all, AI will have a major impact at the workplace. This will in the long run affect employment, with retooling of job profiles and a reassessment of the desired skills. However, at present it will affect companies’ talent recruitment more as they will need to do a complete data backed analysis on what different functions to address this year. The interesting this is that this recruitment will not be driven by the technologists alone, but by specific domain experts. There has long been a debate on the return-on-investment (ROI) in the use of Big Data. This is set to be resolved with the use of AI. While cyberattacks have unfortunately already become more common, their severity is set to further rise, ringing in the alarm bells. AI will need to be transparent, provable and explainable for it to be relevant to all kinds of stakeholders. While USA remains the dominant power in such tech, China may soon take over. The likes of Canada, Japan, Germany, the UK and the UAE are also there in the pipeline. The onus on responsible use of AI won’t lie on the prerogative of tech companies singlehandedly, but will be a shared need.

Source:https://www.strategy-business.com/slideshow/Artificial-Intelligence-What-to-Expect-in-2018?gko=5d351

Uploaded Date:27 February 2018

The bitcoin cryptocurrency has been a lot in the news due to its exponential rise in value in 2017, before sliding down again recently. However, the bigger picture is that of the Blockchain technology which powers Bitcoin and all such cryptocurrencies. In a study anchored by MIT Sloan lecturer Michael Casey, it is explained how blockchain is becoming something of a “truth machine”. It is leading to a consensus of facts now, which in fact is the very essence behind human civilizations. Enormous funds are spent on tallying ledger books and balance sheets, because of the breakdown in trust. That is why blockchain technology needs a decentralization. It is already being utilized in various real-life scenarios such as an algorithm powered by blockchain driving a part of the World Food Programme’s operations in the Syrian refugee camps in Jordan. This business innovation in such a critical environment can solve problems for thousands of people, often at the mercy of clerical inefficiencies. Blockchain could also evolve into a Tragedy of Commons sort of problem.

Source:http://mitsloan.mit.edu/newsroom/articles/blockchains-applications-reach-further-than-you-think/?utm_source=mitsloantwitter&utm_medium=social&utm_campaign=truthmachine

Uploaded Date:27 February 2018

While AI (Artificial Intelligence) seems to be everywhere, amidst the hoopla over stars such as Alexa, Alpha Go or Siri, the technology still has a lot to improvise. While innovators say that AI will soon be a part of almost everything, it is better to keep a cautious eye out. As per a recent report by the McKinsey Global Institute, even within sectors, there remains a massive disparity between the leaders and followers. The sectors on top of the AI adoption rates are financial services, high tech, communications, logistics, healthcare and tourism. This is followed by a middle pack comprising media, professional services, retail, energy, education, automotive and consumer packaged goods. Building materials and construction industry is falling behind. Five major limitations have been identified by this study. The first of them is, data labelling, which is the process of each data set being categorized by humans. This leads to a reinforced learning using trial and error. Another limitation is the requirement of vast data warehousing to get any operation underway. A third is that while AI provides quantitative analysis, it does not explain the bigger picture. AI also does not have the ability to improvise in learning, as rather it is too generalized. Ideally, AI is supposed to be free of biases, but ultimately all algorithms are created by humans, so inherent biases creep in. A calibrated approach with lateral thinking is needed to solve this, with a sophisticated strategy for business analytics.

Source:https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/what-ai-can-and-cant-do-yet-for-your-business?cid=other-soc-twi-mip-mck-oth-1801&kui=1UXNVzIzR8YwtGkEDN4iUQ

Uploaded Date:13 February 2018

The reputation economy is one where ratings given to service providers are broken down to produce a value on each person or organization. This is true for drivers of Uber or hosts in Airbnb. This social graph determines the worth of every person. In fact, a study says that in the US alone seventy percent of companies scan candidates’ social media ratings during talent recruitment rounds. Such methodology however is flawed. As an example, one can cite the fact that nearly four-fifths of Americans use Facebook, but far lower numbers similarly use Twitter or Instagram. This prevents genuine triangulation across the three fronts. There is a lot of frivolous data available which can lead to unintended results if weighed too much importance. Similarly, a lot of algorithms go wrong such as COMPAS used by the US justice system which has been proven to be racially biased. An unintended consequence of the reputation economy is that everyone is being judged all the time. A lot of service providers have adopted the stance of “social cooling” where they are expected to remain silent. With data protection now such a major point of discussion globally, this reputation economy will similarly need to be scrutinized for its effect on people.

Source:https://hbr.org/2018/01/as-ai-meets-the-reputation-economy-were-all-being-silently-judged?utm_medium=email&utm_source=newsletter_daily&utm_campaign=dailyalert&referral=00563&spMailingID=18921171&spUserID=OTY0OTMwNTk5NwS2&spJobID=1182008306&spReportId=MTE4MjAwODMwNgS2

Uploaded Date:13 February 2018

There is a lot of debate at present about the future of Artificial Intelligence (AI) and how that will change work. Broadly, the views may be separated out into five schools of thought. The first are the Utopians who are very optimistic as they feel robots will take more work leading to high economic growth. The Dystopians feel the other way-round, as they feel that machines will win a Darwinian struggle till the end, displacing humans. Mass unemployment, and real wage decline will most heavily be felt in Europe and North America. The Technology Optimists on the other hand feel that business innovations will improve quality of life but only when companies fully leverage those. The Productivity Skeptics feel that while robots do have the potential to enhance productivity, due to several other societal challenges, the net effect will be negligible. The Optimistic Realists are those who feel that digitization and AI in particularly can lead to rapid advancement in several sectors where research will be turned on. In order to ensure a bright future in human-machine interaction, technology needs to be used so that operating models may be redesigned and human skills can get augmented by machine usage. A complete redesign of jobs needs to be done. Employees’ innate abilities need to be leveraged so that an intelligent enterprise may be forged.

Source:https://hbr.org/2018/01/how-will-ai-change-work-here-are-5-schools-of-thought?utm_medium=email&utm_source=newsletter_daily&utm_campaign=dailyalert&referral=00563&spMailingID=18894202&spUserID=OTY0OTMwNTk5NwS2&spJobID=1181669277&spReportId=MTE4MTY2OTI3NwS2

Uploaded Date:06 February 2018

It is tempting to blame Artificial Intelligence (AI) for a lot of impending doom. Apparently, a lot of jobs, especially the routine ones will be taken over by bots and robots. In this scenario, the art and science of leadership will also be under the scanner. A lot of traditional leadership roles could now be performed by AI powered tools. This especially relates to the ‘hard’ parts of leadership such as dissemination of information. Those aspects requiring soft skills such as objective decision making and team mentorship will also be affected but in different ways. One way in which this change will take place is the level of humility that will now be expected from leaders. They can no longer expect an easy ride, as due to constant tech changes, they will need to periodically upgrade their learning. Companies such as Nestle have designed their corporate training programmes to include a dose of reverse mentoring where youngsters will train their senior leaders on newer work patterns. Leaders will also now need to be more adaptable as these changes will need to be incorporated constantly to ensure the right digital transformation. They will need to engage more with their team members. A vision needs to be articulated by these leaders to ensure gains in spite of near-term uncertainty as done at Amazon, Tencent Google, Alibaba, Facebook and Tesla.

Source:https://hbr.org/2018/01/as-ai-makes-more-decisions-the-nature-of-leadership-will-change?utm_medium=email&utm_source=newsletter_daily&utm_campaign=dailyalert&referral=00563&spMailingID=18878522&spUserID=OTY0OTMwNTk5NwS2&spJobID=1181524093&spReportId=MTE4MTUyNDA5MwS2

Uploaded Date : 06 February 2018

The usual narrative goes that robots, algorithms, software and artificial intelligence do not suffer from human flaws. Apparently, they behave uniformly with all, follow orders and do not get sick or tired. Yet this perception is flawed, as all these algorithms and software are ultimately created by humans, and their flaws inherently get embedded in. Embarrassing and outright disgusting cases abound with the worst being Microsoft’s chatbot having to be taken off as it had learnt to spout racist language. So, while these tools have tremendous business analytics capabilities, they lack empathy, judgement and the sense of self-awareness. One of the reasons for this is that the engineers who design these tools or virtual characters, may be experts at STEM, but lack the wider understanding of emotion on society, economy and human interaction. A lot of such code is created in intellectual isolation. This is why it is pertinent that coders and engineers get some lowdown on works of liberal arts so the products curated may be more humanized.

Source:https://www.strategy-business.com/blog/Why-Artificial-Intelligence-Needs-Some-Emotional-Intelligence?gko=520ac

Uploaded Date:19 January 2018

Artificial Intelligence (AI) has increasingly been spoken about the last few years as the next major frontier. The good part is that now the early adopters of AI have started experiencing some gains. Digital native tech companies such as Amazon, Google and Baidu have already invested a lot of money in to their internal researches. In addition, AI is making work easier for retailers, public utilities and carmakers. The use of AI among non-tech companies is still relatively low and can be improved. The one biggest impact so far has been the enormous data warehousing capabilities now at play. Enormous gigabytes of data are being created worldwide. Telecom and financial services are two of the other top AI using industries as per a study by McKinsey. The USA is on top of the pile among countries absorbing AI investment with about two-thirds of the total. This is followed by China, with South Kore and the UK coming next.

Source:https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/how-artificial-intelligence-can-deliver-real-value-to-companies?cid=other-eml-ttn-mgi-mgi-oth-1712

Uploaded Date:19 January 2018

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