Today, we're at an inflection point in how we engage with customers to better meet their needs. According to a PwC report, 73% of all people point to customer experience as an important factor in their purchasing decisions. Yet only half of the U.S. consumers say companies are meeting their expectations. In this experience-driven economy, companies who understand the meaning behind customers' needs, listen and learn in every interaction, and consistently create engaging and personal experiences, will win. Companies should adopt AI to get the desired success.

Accenture (NYSE:ACN) has opened a new innovation hub for mining and energy in Perth, Australia. The hub gives mining and energy companies access to "technology innovations including cloud computing, artificial intelligence, the internet of things, virtual and augmented reality, quantum computing, blockchain and drones". Ann Burns, who leads Accenture's Resources sector in Australia and New Zealand, commented: "With this new innovation hub, we are helping raise the innovation profile of Western Australia and Australia overall. We believe that the Western Australian energy and mining sectors can become world leaders in digitalization. Crucial to this is a focus on what we refer to as'triple zero': ideas, design and technologies that help achieve zero harm to workers and machines, zero loss across the value chain, and zero waste for sustainability."

Artificial Intelligence (AI) is having a transformative impact on the financial markets. While delivering enormous efficiencies and lowering barriers to entry, the technology also brings challenges and risks with it – and particularly so when it comes to the overall stability of the market. Distilling insights from the 15 sources including Accenture, Deloitte, HFS Research, McKinsey, Thomson Reuters & PWC, this Impact Brief provides time-poor professionals with insights that are easy-to-read and digest, and can be read in less than 10 minutes.

We spoke to Maria Axente, AI Programme Driver, PwC United Kingdom in the context of this event about how AI and big data can be used to drive enterprise using ethical principles. AI and big data are making big changes in enterprise. It is worth considering how we got to the stage we are at today, and the fact that AI as a discipline is around 56 years old but it has suddenly started to be implemented at a much larger scale. I think there are three main causes of this more recent widespread adoption of AI. One is the huge volume of data that is being collected via smart devices; mainly smartphones, but increasingly IoT devices.

Many companies are stuck in dead-end pilots while an elite few have figured out how to make artificial intelligence (AI) work at scale, according to a new Accenture report. "AI: Built to Scale" shows how difficult this transformation is as well as what it takes to do it successfully. "In a nutshell, what our report found is that the majority of companies are really struggling to scale AI," said Bob Berkey, MD, Accenture Applied Intelligence. "They're stuck in the Proof of Concept Factory, conducting AI experiments and pilots but achieving a low scaling success rate and a low return on their AI investments." Accenture surveyed 1,500 C-level executives across 16 industries to determine what makes AI projects successful.

One day in 1975, a Kodak engineer decided not to embrace a prospective new digital technology, thereby sealing the fate of the world's leading photography company. As insurance executives consider artificial intelligence (AI) and the question of whether to use this technology, they would do well to remember this decisive strategic mistake. AI could be one of the biggest game changers in insurance history and undoubtedly constitutes a paradigm shift. It offers a wide range of opportunities: faster and more efficient claims management and application processes, better prospective healthcare advisory services, and a variety of on-demand insurance services. This boosts customer and stakeholder expectations and generates innovation pressure.

Loughborough University and the Willis Research Network (WRN) would like to invite you to another conference bringing together a range of perspectives on the business application of Artificial Intelligence (AI) and its role in the ongoing digital transformation of the insurance industry. The goal is to look beyond the day to day business decision-making and examine the broader challenges of employing AI, the implication for business models and to address some of the organisational and public policy challenges to effective use of these new technologies. We will have a mix of top university researchers and industry practitioners participating as both presenters and panellists to enhance our depth of knowledge around AI and the use of AI in our industry. We look forward to welcoming you to a stimulating day of open debate and insightful discussion. The conference is the first major event organised by the TECHNGI research project, hosted by Loughborough University and Willis Towers Watson and funded from the UK Government Industry Challenge Fund's Next Generation Services program.

The bigger your company, the more important it is that every team member is on the same page. When you're as big as Genpact, with 90,000 employees and twice as many partners, then collaboration is a top priority. Sanjay Srivastava is well aware of the challenges. As Genpact's Chief Digital Officer, he is front and center at the effort to make sure the disparate teams and employees within the company are working successfully in a collaborative organizational culture, as well as offering a satisfying customer experience. For Sanjay, there are three main factors that need a strong collaboration platform within a company. It starts with the idea of the business as a connected ecosystem that drives a collective intelligence. Then there's the concept of continuous learning and innovation that requires a collaborative framework to be successful. Finally, there's the convergence of domains, the ability to pull people together from different disciplines, with different experiences, and across ...

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Failure to Scale Artificial Intelligence Could Put 75% of Organizations Out of Business, Accenture Study Shows Companies that shift from AI experimentation to execution achieve lasting ROI and competitive agility NEW YORK; Nov. 14, 2019 – Three-quarters of C-level executives believe if they don't move beyond experimentation to aggressively deploy artificial intelligence (AI) across their organizations they risk going out of business by 2025, according to a newly released study from Accenture (NYSE: ACN). The report, titled "AI: Built to Scale" and produced by Accenture Strategy and Accenture Applied Intelligence, is based on a global survey of 1,500 C-level executives across 16 industries designed to understand how companies are implementing AI across their organizations. The research found 84% of C-level executives believe they won't achieve their business strategy without scaling AI, yet only 16% have made the shift from mere experimentation to creating an organization powered by robust AI capabilities. As a result, this small group of top performers is achieving nearly three times the return from AI investments as their lower-performing counterparts. The report reveals the secret to success for these top performers centers around three key elements: a strong data foundation; multiple dedicated AI teams; and a C-suite-led commitment to strategic, organization-wide AI deployment.