If there's one big thing that might thwart companies' headlong rush to adopt artificial intelligence for their businesses, it's data. AI generally requires lots of data. But it needs to be the right kind of data, in very particular kinds of formats. And it often needs it to be "clean," including only the kind of information it needs and none of what it doesn't. "The biggest challenge most organizations face when they start thinking about AI is their data," said Paul Daugherty, the chief technology and innovation officer of consulting firm Accenture, in an interview earlier this month.

Emerton, a consulting firm with offices in Paris, New York and Dubai, has launched Emerton Data, a new arm dedicated to helping clients embrace emerging technologies that are set to disrupt their strategies and operating models. Aimé Lachapelle, who is based in France, has been brought on board to lead the new offering. As global consulting firms bid to capitalise on a booming market to mine vast amounts of data to help shape strategy, Emerton has launched a new service to meet client requests for leveraging their data gluts. Emerton Data will serve clients globally, offering data analytics and artificial intelligence advice to businesses around the world. Emerton Data will be steered from Paris, where the competence hub is based.

For the second straight year, Deloitte surveyed executives knowledgeable about cognitive technologies and artificial intelligence,1 representing companies that are testing and implementing them today. We found that these early adopters2 remain bullish on cognitive technologies' value. As in last year's survey, the level of support for AI is truly extraordinary. These findings illustrate that cognitive technologies hold enticing promise, some of which is being fulfilled today. However, AI technologies may deliver their best returns when companies balance excitement over their potential with the ability to execute. To obtain a cross-industry view of how organizations are adopting and benefiting from cognitive computing/AI, Deloitte surveyed 1,100 IT and line-of-business executives from US-based companies in Q3 2018. All respondents were required to be knowledgeable about their company's use of cognitive technologies/artificial intelligence, and 90 percent have direct involvement with their company's AI strategy, spending, implementation, and/or decision-making. The respondents represent 10 industries, with 17 percent coming from the technology industry. Fifty-four percent are line-of-business executives, with the rest IT executives. Sixty-four percent are C-level executives--including CEOs, presidents, and owners (30 percent), along with CIOs and CTOs (27 percent)--and 36 percent are executives below the C-level.3 A year later, and the thrill isn't gone. In Deloitte's 2017 cognitive survey, we were struck by early adopters' enthusiasm for cognitive technologies.4 That excitement owed much to the returns they said cognitive technologies were generating: 83 percent stated they were seeing either "moderate" or "substantial" benefits.

The world seems to be going Artificial Intelligence (AI) crazy! So in this post i thought i would cover the 10 Artificial Intelligence AI Trends highlighted by PwC for 2018. Its about 6 months old now, but the themes are relevant and i wanted to capture (for my own notes) the AI trends in layman terms. This is where a neural network has the ability to learn by engaging with the environment through observations, actions and rewards. DRL is popular type of AI, often used in business applications and gaming – e.g.

From cost center to profit center: Institutions will turn AI-enabled back-office operations into external services, both accelerating the rate at which these capabilities improve and necessitating others to become consumers of those capabilities to avoid falling behind A new battlefield for customer loyalty: As past methods of differentiation erode, AI presents an opportunity for institutions to escape a "race to the bottom" in price competition by introducing new ways to distinguish themselves to customers Self-driving finance: Future customer experiences will be centered around AI, which automates much of customers' financial lives and improves their financial outcomes Collective solutions for shared problems: Collaborative solutions built on shared datasets will radically increase the accuracy, timeliness, and performance of non-competitive functions, creating mutual efficiencies in operations and improving the safety of the financial system Bifurcation of market structure: As AI ...

Companies are ramping up investments in artificial intelligence (AI) technologies. That's the biggest takeaway from Deloitte's second "State of the AI in the Enterprise" report, a survey of more than 1,100 IT workers and executives from U.S.-based companies that was conducted in the third quarter of 2018. "Companies are excited about the potential of AI to improve performance and competitiveness -- and for good reason," said Dr. Jeff Loucks, executive director at Deloitte's Center for Technology, Media, and Telecommunications. "But to reach this potential, companies must engage risk, address talent shortfalls, and execute well. While AI's upside is significant, haste can leave companies with bridges to nowhere -- pilots that don't scale or projects with no business benefit."

Chat to anyone with an interest in accounting tech and you're sure to hear the terms, 'machine learning' and'artificial intelligence' (AI), come up. So what do these terms mean for you, and are they relevant for you and your practice? Generally speaking, AI covers any intelligence demonstrated by machines. Machine learning is a specific branch of AI, relating to the ability for a machine to learn from data, identify patterns and make decisions based on a predetermined set of rules. This ability to apply rules to data sets is especially relevant when it comes to accounting.

In my blog series on how to boost your Artificial Intelligence Quotient, I looked at different ways to apply AI along the insurance value chain across the entire enterprise. In this post, I'll look at the role the future workforce will play in creating AI-driven companies, using insights gleaned from our Future Workforce Survey for Insurance . Accenture research suggests, by the year 2035, AI will grow productivity in key economies by up to 40 percent. AI offers its greatest value by augmenting the work that people do and improving the way they consume and interact with their communities. AI also presents the opportunity for business transformation by creating intelligent processes in the value chain and intelligent products and services in the market.

What do a studio partnered with a French banking group, a consultant from a major British auditing firm and a Quebec AI conglomerate all have in common? In order to help you keep up with the latest in chatbots and artificial intelligence, here are 10 influencers--both French- and English-speaking--that you should definitely be following! An expert in new technologies, digital tools, and Information and Communication Sciences, Maria Johnsen offers you numerous tips to improve your business through innovations in AI and chatbots. A Business Development Leader & Management Consultant in the auditing division of PricewaterhouseCoopers, he posts tweets chock-full of figures, infographics and charts on all topics related to artificial intelligence. Her expertise in Customer Relations and Big Data is well-established: Tamara has been named one of the Top 25 Influencers in the fields of AI and machine learning.

In various categories, it's beginning to deliver on its promise. Financial services companies are using such technologies in ways that range from chatbots that answer basic customer questions to AI-powered platforms that help prevent fraud and money laundering. Human resources (HR) applications help companies sort through resumes, find talent, and even conduct initial interviews. It can be used for maintenance alerts and prevent equipment and vehicle failure in automotive fleets. Purchasing algorithms can help sort through data to make better procurement decisions.