Work you'll do Key Responsibilities Will Include At Deloitte you will manage and deliver components of client engagements that identify, design, and implement technology and creative business solutions for large companies. Architect, Position, Design, Develop and Deploy enterprise solutions which include components across the Artificial Intelligence spectrum such as Chatbots, Virtual Assistants, Machine Learning, and Cognitive Services Manage teams in the identification of business requirements, functional design, process design (including scenario design, flow mapping), prototyping, testing, training, defining support procedures. Develop statements of work and/or client proposals. Identify business opportunities to increase usability and profitability of information architecture. Develop and manage vendor relationships.

Machine learning is a subset of artificial intelligence (AI) that utilizes algorithms and computer power to sharpen the judgments organizations make about voluminous and disparate data. Simply put, it allows machines to learn how to perform certain tasks without being explicitly programmed to do so. Machine learning already permeates virtually every facet of our lives--it is used every day for image and speech recognition, digital assistants, cyber protection, consumer marketing, medical diagnoses, ferreting out proscribed content on social media platforms, ride-sharing apps, law enforcement, and in countless other applications. Machines could learn how to detect fraud simply by being provided with examples of previously seen fraud cases, and without the need for manually coded business rules. Machine learning helps optimize the mix between humans and machines in an intelligent, accretive process that "learns" as it goes along.

DUBLIN--(BUSINESS WIRE)--Public-service executives in Europe are optimistic and enthusiastic about the impact of artificial intelligence (AI) on government operations and services but face challenges implementing the technology, according to a study issued today by Accenture (NYSE: ACN). The study -- based on a survey of 300 government leaders and senior information technology (IT) decision-makers in Finland, France Germany, Norway and the U.K.-- found that the vast majority (90%) of respondents believe that AI will have a high impact on their organizations over the coming years. In addition, nearly the same number (86%) said that their organization plans to increase its spending on AI next year. Customer service and fraud & risk management are the two operational areas favored most for public service AI deployments, cited by 25% and 23% of respondents, respectively. In addition, respondents most often cited increased efficiencies, cost or time savings, and enhanced productivity as the greatest anticipated benefits from their AI investments.

The world of artificial intelligence is beset by hype and hubris. But make no mistake: AI has the potential to make businesses more efficient and faster. Yet, as transformative technologies keep getting smarter and cheaper, businesses' return on innovation investment has declined by 27 per cent over the last five years, according to a report from Accenture. To Ray Eitel-Porter, who heads up Accenture Applied Intelligence in the UK, the evidence points to one problem: companies don't know how to make the most of AI and data analytics, and how they can apply to business problems. AI is a transformative technology, so businesses should be ambitious and think about solutions that would yield ten times the impact of traditional investments – not just a ten per cent improvement.

Deloitte US has deployed a technology-enabled solution -- CognitiveTax Insight (CogTax) -- to provide a more efficient analysis of clients' indirect tax data set. CogTax has the ability to analyse the full population, if desired, of clients' accounts payable transactions compared to a traditional, sampled approach. The solution can help companies to proactively avoid overpaying their indirect tax liabilities. CogTax leverages optical character recognition (OCR), along with advanced machine learning algorithms and analytics, to analyse a full population of data and documents to assist clients with indirect tax overpayment recovery and reduce the potential for future over or underpayments. "CogTax moves tax analysis from a manual, administrative process to an automated, machine learning process that brings with it accuracy and scale previously not achievable," said Deval Reddy, indirect tax principal in the multistate tax services practice, Deloitte Tax LLP.

European Government Organizations Are Enthusiastic About Artificial Intelligence but Face Challenges Adopting It, According to Accenture Study DUBLIN; Oct. 23, 2019 – Public-service executives in Europe are optimistic and enthusiastic about the impact of artificial intelligence (AI) on government operations and services but face challenges implementing the technology, according to a study issued today by Accenture (NYSE: ACN). The study -- based on a survey of 300 government leaders and senior information technology (IT) decision-makers in Finland, France Germany, Norway and the U.K.-- found that the vast majority (90%) of respondents believe that AI will have a high impact on their organizations over the coming years. In addition, nearly the same number (86%) said that their organization plans to increase its spending on AI next year. Customer service and fraud & risk management are the two operational areas favored most for public service AI deployments, cited by 25% and 23% of respondents, respectively. In addition, respondents most often cited increased efficiencies, cost or time savings, and enhanced productivity as the greatest anticipated benefits from their AI investments.

Across all sectors, businesses are investing in and pursuing automation and smart technologies. But while companies are kicking the tires on automation--and achieving value, in pockets--many are yet to achieve its truly transformative power. Progressing from pilots and proofs of concepts to implement automation at scale, and unleashing the true value of human machine collaboration. In the era of human-machine collaboration, automation should be approached as a cultural change that brings people, process and technology together to build a sustainable enterprise model. What's more, successfully automating key processes and functions can free up investment capacity.

BENGALURU: The decrease in demand for manpower owing to Artificial Intelligence (AI) and allied technology resulting in job cuts, has been an area of concern. In India alone, jobs loss in the IT sector is reported to have touched 1,000 over the past year, particularly due to incorporating of advanced technologies such as AI and machine learning. According to sources, various global firms who have their major centres in Bengaluru (such as Cognizant, Accenture and IBM) have either cut or redeployed their employees. As per a survey by the All India Management Association and consulting firm, Pricewaterhouse Coopers (PWC), 36% of decision-makers said that overall advancements in automation and technology had not displaced jobs. However, 46% of them indicated that they would have a severe impact on employment in India. Further, nearly half of the participants surveyed felt that job automation was reasonably probable; however, it was likely to be partial, with humans retained for specific expertise.

Accenture is spending $1 billion in re-training training its employees every year as the company sees its customers are increasingly demanding newer technology-led services. The tech services major said it has trained nearly 80% of its technology services employees in technologies such as data analytics, artificial intelligence, machine learning, cloud computing - broadly referred as digital technologies. Digital currently contributes more than 60% of Accenture's $43.2 billion revenue. Nearly 55% of Accenture's employees are in technology services roles globally. "We had (nearly) 200000 people across 180 countries and we pitched that as our strength. One of the clients once asked me it is your strength or weakness, do you really need so many people in future. It was a big question at that point of time we took decision to rotate to new. So our investment in talent is close to a billion dollar globally and nearly 80% of tech services talent are trained in new," said Bhaskar Ghosh, group chief executive, Accenture Technology Services.

Most early adopters face AI skill gaps and are looking for expertise to boost their capabilities. According to Deloitte's global study of AI early adopters, 68 percent report a moderate-to-extreme AI skills gap.1 What are the "most wanted" roles to fill these gaps? According to AI early adopters, the top four most-needed positions are "AI builders" who are involved in creating AI solutions: Beyond these AI builders, adopters are seeking "AI translators" who bridge the divide between the business and technical staff--both at the front and back end of building AI solutions: When we compare companies with relatively little AI experience (they've built five or fewer production systems) with those possessing extensive AI experience (they've built 20 or more production systems), we observe an interesting shift in "most wanted" roles (see chart). Early on, AI researchers are the most sought-after, with about a third of the less-experienced rating them a top-two needed role. Business leaders rank near the bottom.