With the emergence of more informed and tech-savvy consumer base, retailers are increasingly replacing the traditional mass-market approach with targeted strategies formed using insights driven from consumer data, said a report. According to a Deloitte India report, a trend called'Tribetailing' is picking pace, especially in the luxury segment in the country. This trend allows retailers to use artificial intelligence (AI), machine learning, and social media analytics to gain information about consumers' shopping history, behaviour, preferences, and online activities. This information, it said, is helping retailers to group consumers in categories and come up with bespoke solutions, and devise personalised marketing and promotional programmes such as membership and loyalty programmes and discounts to target niche consumer segments. "Consumer trends in India are evolving at a rapid pace with the advent of technology and with that the Indian consumer has evolved from a reactive entity to a proactive seeker of products and personalised experiences. This change needs retail brands to change the language of their engagement as the consumer now takes the driver's seat unlike brands telling the story to him/her," said Anil Talreja, partner, Deloitte India.

Here are the top news stories in talent & organization from this week. Female founders and women in business are changing the world, so it's time to drop words such as "mompreneurs" and "she-E-Os", argues Leigh Buchanan. "From a semantic viewpoint, the words or phrases express meanings antithetical to their intent. The word entrepreneur derives from the Old French: to undertake an enterprise. "As for she-E-O, the word being replaced is chief.

PWC Tech World reports that most e-commerce platforms are focused on sectors such as communication commerce, artificial intelligence (AI), virtual reality (VR) / augmented reality (AR) and analytics technologies New Delhi: Global auditing and consulting firm PWC says that e-commerce companies are focusing on artificial intelligence (AI) and virtual reality to reduce logistics costs and detect fraudulent orders. With a growing middle-class population of over 500 million and about 65% of the population aged 35 or under, India represents the most sought-after consumer market for retailers worldwide, according to a report by PWC Tech World. "E-commerce players are reinventing their technology strategies to stay competitive. Many e-commerce platforms are growing their investments in sectors such as communication commerce, artificial intelligence (AI), virtual reality (VR) / augmented reality (AR) and analytics technologies". E-commerce companies are investing heavily in robotics and AI to detect fraudulent orders, reduce revenue rates and reduce logistics costs.

The United States is at the precipice of a defining moment in history. Throughout the past 5 years, progress in artificial intelligence (AI) has greatly accelerated. From the defeat of Go champion Lee Sedol by DeepMind's AlphaGo program to the first deployments of fully-autonomous vehicles on public roads, recent events are challenging us to re-evaluate what may soon be possible for computerized systems. AI systems have already begun to quietly pervade a growing share of businesses, governments, and individual lives around the world, and we are only just beginning to grasp the impacts that this technological revolution will have on our economy, society, and national security. In our paper, we outline the key elements of a comprehensive national strategy for the United States to promote the safe and responsible development of AI, and to maintain U.S. leadership in AI technology.

Artificial intelligence (AI) is no longer on the horizon. It's here now, and it's already having a profound impact on how we live, work, and do business. Companies, governments, and organizations must embrace the idea of going places they simply cannot get to using current technologies and processes. AI can and will transform organizational decision-making, drive efficiencies, build new capabilities and businesses, and power sustainable, value-driving activities. But like all revolutions in technology, capturing maximum value while simultaneously minimizing risk will require a strategic understanding of both what AI is, and how it aligns with your core business.

It has been more than six decades since the concept of Artificial Intelligence has transformed from imagination to an academic discipline. Influencers, especially those active on social media help give direction to the policymakers and academicians. They keep common men updated on the trends and'what is what' in AI, Machine Learning and associated concepts like Big Data and BlockChain. AiThority introduces you to the 50 most popular AI-influencers of North America. A PhD in industrial-organizational psychology, his interests lies in Data Science, CX, Statistics and Machine Learning.

The role of a data analyst is evolving in the era of emerging artificial intelligence (AI). So much so, we might need to relabel this role as Analyst 2.0. Here's a look at what Analyst 2.0 means for the next-gen data guru helping organizations use data for better decision-making. We are all swamped with data. Analysts have a hard time keeping pace with demands for intel that can only be gleaned through analytics.

Is artificial intelligence finally starting to take on a recognizable shape, after its history of being sometimes overhyped, often misunderstood, and always intriguing (but in a tantalizingly futuristic sort of way)? To better understand the state of AI development, the firm this year conducted deep interviews with executives at 30 of the world's largest companies, as well as three of largest providers of AI solutions and services. Out of this work, eight trends came into view. Rapid shift from experimental to applied technology. "Less than three years ago, many leaders in large organizations were asking themselves if AI could support their productivity and growth objectives, and many were just beginning to pilot and test AI applications," KPMG said. Since then, AI has quickly moved from a "technology to watch" to a "technology to deploy," according to the report.

Leaders need to rapidly realize the potential of artificial intelligence (AI) to accomplish their missions. Yet today, deployments rely on custom-built models and "one-off" integrations. Despite massive investments, organizations struggle to move AI from the lab to production at scale. Booz Allen is applying lessons learned from some of today's most complex AI engagements to replace costly, cumbersome deployments with open standards and plug-and-play interoperability. Discover – Access proven, pre-trained, explainable models.

Two years ago artificial intelligence (AI) reached the peak of absurd expectations, as I tried to capture in this post. Well, reality seems to have crept in, something that shows in how companies have been approaching AI, which has been to focus on low-hanging fruit, rather than moonshots. This is according to Deloitte's State of AI in the Enterprise, 2nd Edition, which unveils a world increasingly serious about AI. That said, there are still some head-scratchers in the data. Let's dive into the report.