We crafted a scalable, cost-effective approach for a new era of learning that puts the spotlight on --learning anytime, anywhere-- through digital technologies.-- With the Accenture Future Talent Platform, the client can now launch new services on its ecommerce site 75--percent faster than previously possible. The program will identify new roles and skills and build a training plan for a pilot, followed by a 40,000-person rollout. Accenture will also develop a curated, interactive curriculum for bank employees. Combining unmatched experience and specialized skills across more than 40 industries and all business functions -- underpinned by the world--s largest delivery network -- Accenture works at the intersection of business and technology to help clients improve their performance and create sustainable value for their stakeholders.

CFOs have an opportunity to cut costs, build for the future, and increase data-driven decision making. I've always been surprised at how finance functions treat their own technology spend. Maybe finance executives are more conservative with their own wallets, or maybe they hold themselves to too high a standard. Either way, they tend to invest less in technology than their counterparts in other functions invest--on average, just 13 percent of tech budgets go toward enterprise functions like finance, risk, and compliance, while IT garners 28 percent and sales and marketing gets 24 percent, according to PwC's 2017 Global Digital IQ Survey. Some CFOs, however, are rethinking the digital investment in their own function--especially the investment in emerging tech, such as robotic process automation (RPA), artificial intelligence (AI), and blockchain.

Among the findings pertaining to the enterprise, this year's report indicates that business organizations will likely double their use of machine learning technology by the end of 2018. TMT Predictions highlights five key areas that Deloitte believes will unlock more intensive use of machine learning in the enterprise by making it easier, cheaper and faster. The most important key area is the growth in new semiconductor chips that will increase the use of machine learning, enabling applications to use less power, and at the same time become more responsive, flexible and capable."

Organizations that successfully apply AI innovate and compete more effectively. Those who fail to implement AI successfully will fall behind. The AI Conference in New York will give you a solid understanding of the the latest breakthroughs and best practices in AI for business. You'll get insider information on any aspect of AI you may be working on including: You'll discover how the world's most innovative companies are using AI--and how to implement their successes in your products and enterprise. And you'll meet some of the most interesting people in AI: Xerox PARC CEO Tolga Kurtoglu, Intuit CDO Ashok Srivastava, Princeton Professor Olga Russakovsky, Deloitte Chief Data Scientist James Guszcza, FICO Chief Analytics Officer Scott Zoldi, Emma Kinnucan of Booz Allen Hamilton, and more.

There is not one but many definitions of Artificial Intelligence (AI), and its scope remains fluid and evolving. Some people even state that AI is everything that has not yet been done, referring to the observation that as the tools we use daily become increasingly sophisticated, tasks previously considered as requiring'intelligence' are now considered routine and get excluded from the AI definition. Think for example of a good spam filter, spell check or optical character recognition, all of which used to be considered revolutionary, but today don't impress people anymore. 'A constellation of technologies that extend human capabilities by sensing, comprehending, acting and learning – allowing people to do much more.' In other words, we put the focus on the ability of AI to complement and empower people instead of replace them. Therein lies the key: If you only look at AI from the perspective of a technology that'can do it all', it will fail and create problems within organizations and society.

To realise data's full potential, Deloitte Data Analytics is demystifying data science through impactful initiatives. In February 2018, the Deloitte School of Analytics will host its three-day annual education event, where they break down this data phenomenon and help clients use data science to drive their organisation forward. The annual education event is a three-day training programme that focuses on enhancing Analytics capabilities across Africa. Deloitte Analytics SMEs and TDWI lecturers will be engaging with the delegates through hands on and classroom based training, structured case study discussions, presentations and practical examples. The education journey will include modules such as Practical Application of Machine Learning and Artificial Intelligence, Data Architecting for the Future and Demystifying Data Science.

Accenture Uses Artificial Intelligence to Help the Elderly Better Navigate Their Care and Improve Their Well-Being LAS VEGAS and LONDON; Nov. 28, 2017 – Accenture (NYSE: ACN) has completed a pilot program that uses artificial intelligence (AI) and the ease of voice to help older people manage the daunting challenges of navigating their care delivery and well-being. The Accenture Liquid Studio in London developed an AI-powered platform (the Accenture Platform) that can learn user behaviors and preferences and suggest activities to support the overall physical and mental health of individuals ages 70 and older. The Accenture platform, which runs on the Amazon Web Services (AWS) cloud, includes a'Family and Carer' portal that lets family and caregivers check on the individual's daily activities, such as whether they have taken their medication or made new requests for caregivers. The Accenture platform can also spot abnormalities in behavior and alert family or friends, based on user defined permissions. Elder Care Pilot: Accenture Uses AI to Help Navigate Elder Care Other services provided by the Accenture platform helped participants find local events as well as potential new friends, encouraging them to become more active and social.

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For those not native to the programming world, it can get pretty confusing knowing which terms means what when it comes to artificial intelligence (in other words, which one to use in a meeting to sound like you know what you're talking about). Machine learning is probably the term that most of us think of when we imagine artificial intelligence, whether we realise it or not. It isn't the same as AI, though the terms are often used interchangeably, and really just refers to a certain way in which a machine can use large amounts of data to do things we think of as smart. A basic computer program's intelligence comes from the programmer who wrote the instructions. It is simply code that a computer runs from start to finish.

Background After existing mostly in the realm of science fiction for decades, artificial intelligence is increasingly becoming science fact in our everyday lives. Products like IBM's Watson, which bested humans on the game show "Jeopardy!" a few years ago, have given way to electronic home assistants like Amazon's Alexa and smartphone-based aides like Apple's Siri and Google Assistant. AI and machine learning aren't yet all the way there -- and tech industry giant Elon Musk has been among those saying there's real reason to be worried about these technologies getting beyond human control -- but there's more than enough to the industry at this point to interest investors and governments around the world, and AI's effect on the economy is likely to only get bigger in the coming years. Through early October, 2017 merger-and-acquisition activity in AI totaled $2.39 billion over 141 deals. That compares with 89 deals for $1.87 billion in all of 2016, and 35 deals worth $371.8 million in 2015.