The term Artificial Intelligence (AI) conjures up a certain vision reminiscent of science fiction movies. But its real impact at present is much more understated. Enterprise Cognitive Computing (ECC) is now proving to be an essential bit in the area of robotics and automation. It is utilized to use AI for enhancing business operations. It helps in getting formulaic and routine tasks done. For ECC to be successful, large quantities and clean content of data warehousing needs to be done. ECC has the ability to sieve through humongous quantities of data to bring out the useful business insights. A study conducted in 2017 confirmed, that more than three- fifths of industry representatives, want to the adoption of ECC applications within five years. But by now, few have walked the talk. ECC can also help a lot with research and development, especially in the pharmaceutical space.

Source:https://sloanreview.mit.edu/article/using-ai-to-enhance-business-operations/

Uploaded Date:24 June 2019

There is much hype now in the digital age regarding the use of artificial intelligence to business. A lot of stories have emerged on AI bots and killer robots. But before plunging headlong, any company needs to understand what exactly works, and what is mere hype. Self- driving cars are proving to be quite a rage now. But at present, more than the accrual usage, more important is the data warehousing. This will ensure that the right insights are generated for a future when such vehicles will be in greater use. A lot of the technologies which are proving to be hits, are not completely novel, but in fact extensions of earlier innovations such as that of business analytics. The Internet of Things is also proving to be a substantial hit. Investments are also soaring in. The entire investment trajectory is following the S curve. In sales and marketing in particular, AI investments are getting hot.

Source:https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/artificial-intelligence-in-business-separating-the-real-from-the-hype

Uploaded Date:15 June 2019

The payments industry has long had a challenge with obtaining fair compensation. One of the reasons for this is the spread over diverse markets as is the case presently. However, there is good news now, in the shape of reduced customer- attrition rates and volume losses. This is by use of advanced business analytics. This involves mining diverse data to extract the deeper insights. There has been a positive client- revenue impact as per data supplied by McKinsey. To make sure that usable insights are extracted, the leadership needs to ensure clean and proactive data warehousing. Otherwise, inaccuracies will creep in. Data engineering and improvements in computational engineering are further making inroads. Spark Beyond is one such new tool that is proving to be extremely useful in this. Another is XG Boost, which uses Machine Learning capabilities. All these help in early adoption of pricing rates as per customer or client requirements.

Source:https://www.mckinsey.com/industries/financial-services/our-insights/how-machine-learning-can-improve-pricing-performance

Uploaded Date:15 June 2019

Artificial Intelligence (AI) may now well be considered the automobile that symbolizes the digital economy. Its fuel is big data. SMEs will need to create value so that they may leverage the power of AI, else as is the trend, the Big Tech firms will continue to monopolize this too. The AI Forum was held recently in Singapore to discuss the future of the industry and the challenges that will be associated. First of all, AI will need to be demystified. Before embarking on its full- scale adoption, a complete audit needs to be done on it, to understand its expected financial impact. The INSEAD in order to cope with these changes, has added micro- classes on the topic, in its Executive MBA curriculum. Which all applications are to be adopted, also need to be determined. The boundaries of work and transformation sought, too need to be well- defined at the outset.

Source:https://knowledge.insead.edu/blog/insead-blog/three-objectives-for-moving-forward-with-ai-11561

Uploaded Date:08 June 2019

There are major ways in which the world economy has by now been affected by Artificial Intelligence (AI). The potential to contribute to the pool of global economic activity has risen multifold. A study conducted by the McKinsey Global Institute confirms that by the year 2030, about seventy percent of the companies would have adopted AI in some form or the other. The adoption rates for AI though could differ widely among companies, workers and even countries. Among companies, digital- natives or early adopters would be the ones primed to take key advantage. Workers will be affected by the talent recruitment patterns, where those with higher digital skills will get preference. Among countries, it is those which are either developed, or on the cusp of high growth, who will gain from most of the AI initiatives. Skilling and reskilling people is now of utmost concern for most players in the market.

Source:https://www.mckinsey.com/featured-insights/artificial-intelligence/notes-from-the-ai-frontier-modeling-the-impact-of-ai-on-the-world-economy

Uploaded Date:07 June 2019

Enterprise decision- making is now being influenced a lot by the newer paradigms that are gaining strength. Business decisions are now being made by making use of the vast treasure troves of data now available. Artificial Intelligence (AI) is set to combine with the latent human intelligence to curate greater autonomy at work. Organizations are now investing a lot on business analytics, so now increasingly resembling math houses. Data science is being made use of for extracting business insights. Even AI is being tweaked from the predictive to the prescriptive model. Companies need to build an engineering mindset in their teams to take advantage of this era of change. Constant learning, relearning and unlearning has to take place. Design thinking and behavioral science will need to act as the pivots behind this transformation.

Source:https://www.forbes.com/sites/cognitiveworld/2018/10/15/reimagining-enterprise-decision-making-with-artificial-intelligence/#3e86ccf52fd6

Uploaded Date:07 June 2019

It is now well- appreciated that Machine Learning (ML) and Artificial Intelligence (AI) will both play a major role in all kinds of up coming businesses, including in manufacturing. The foundation for the success of this is data warehousing, which needs to be executed with utmost care. If one can collate this with Maslow’s Hierarchy, then data is the base level on which all else is dependent on. This includes external data, sensors and user- generated content. The right infrastructure and data’s storage form the second tier. Business analytics, metrics, features and aggregates find themselves higher up the chain. Further ahead is A/B Testing and ML algorithms. Right on top of this pyramid lie AI and deep learning. This pyramid has been created by Monica Rogati.

Source:https://www.forbes.com/sites/willemsundbladeurope/2018/10/18/data-is-the-foundation-for-artificial-intelligence-and-machine-learning/#6215dac251b4

Uploaded Date:07 June 2019

Newly minted technologies are not only disrupting the age- old work styles, they are questioning the very existence of industries. Indeed, this is further giving way to more questions on the society itself. Pitched battles are now figuratively being fought between teams of robots and humans on either side. While the former do bring a certain sense of order and efficiency, the latter may have the edge when it comes to creativity and understanding emotions. Talent recruitment processes too are getting altered, as several industries are staring at a possible jobless future. Silicon Valley and Wall Street are both getting bombarded with such ideas. The human agenda thus needs to be reclaimed. Algorithms cannot provide us with direction, but are merely a means of completing the tasks.

Source:https://www.strategy-business.com/article/Team-Human-vs-Team-AI?gko=4d55d

Uploaded Date:20 May 2019

The retail sector is making good use of Artificial Intelligence (AI), with several examples to prove this. One is Lowes using robots for locating goods. Walgreens uses AI for tracking the spread of Flu. Makeup can be found easier now at Sephora. An individually curated taste- matching perfect coat can be found by North Face. Neiman Marcus uses AI to search visually. Ordering of tacos may be done by customers of Taco Bell. Thred Up uses AI in its data warehousing operations, by remembering customer preferences. The other retailers using AI include the likes of Amazon, Macy’s, Walmart, West Elm, Uniqlo, Olay, Sam’s Club, H&M, Kroger, Starbucks, Zara, Rebecca Minkoff and Starbucks.

Source:https://www.forbes.com/sites/blakemorgan/2019/03/04/the-20-best-examples-of-using-artificial-intelligence-for-retail-experiences/#7d32f24d4466

Uploaded Date:15 May 2019

Artificial Intelligence (AI) is not a single technology, but a suite of them, to help mimic human functions. Machine Learning (ML) is its most popular sub- field. There are different ways in which companies use this AI. The vast quantities of data warehousing, gets analyzed to process meaningful insights. AI is also used for customer service and marketing mix optimization. Enhancement and extension services are also offered. AI may also be used to detect anomalies and frauds in the system. While working with AI though, a few factors need to be considered. First of all, the data sources need to be determined, on which the advanced business analytics needs to be conducted. The business opportunities also need to be put within a broad boundary. The system needs to be designed with the end goal in sight. Finally, the right investment needs to be made on the process, while also raising awareness on it.

Source:https://www.bain.com/insights/customer-experience-tools-artificial-intelligence/

Uploaded Date:25 January 2019

Artificial Intelligence (AI) and Machine Learning (ML) are among the top research priorities for the tech giants like Google. This is good news for tech freelancers, as many of them, work in these areas. The use of AI for overall social good, and the ethical principles to be applied is one such sub- area. Another is assistive technology, of which Google Duplex is a good example. Quantum Computing and Natural Language Understanding are two others. Tracking perceptions using tools such as Google Lens is another major business innovation at play now. The algorithms too need to be tied up to the theory. Night Sight used on Pixel phones, is an example of the art of Computational Photography. Much of the business research now may be gauged through digital outreach from tools such as the Google AI Residency. Some of the other areas of growth scope are health, new place discovery, robotics, open source software, Auto ML, TPUs, software systems and applications to newer areas.

Source:https://www.forbes.com/sites/jonyounger/2019/01/16/googles-ai-and-ml-research-priorities-freelancers-take-note/#26f0a96e344c

Uploaded Date:22 January 2019