Professional Services


Most businesses say their future will be shaped by AI - but they aren't investing in it

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IRISH BUSINESSES ARE lagging behind when it comes to investment in artificial intelligence, according to a new report by one of the Big Four professional services firms. A survey by PwC highlights a lack of clarity among businesses on how to plan for an AI future and the challenges with accessing and re-training talent. Conducted with the Analytics Institute, PwC surveyed 100 executives and high-ranking employees at companies of mixed sizes, including firms with revenues of less than €10 million and those with revenues of more than €5 billion. This relatively small sample size covered various industries but more than 93% were outside of IT with the replies benchmarked against US data. PwC has put together six priorities that need to be addressed by industry and government in Ireland: clarity, strategy, data, skills, trust and convergence, or how AI integrates with other technologies.


Deloitte and Signal A.I. collaborate to digitize tax regulation monitoring with artificial intelligence

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Deloitte Global announced that Deloitte firms are now offering clients an artificial intelligence (AI) platform. The platform can monitor, measure, and analyze changes in tax regulation in real-time to give Deloitte clients the edge in monitoring and responding to regulatory updates across the world. The AI platform is the result of a collaboration between Deloitte firms and Signal A.I. Signal's proprietary AI technology was trained by Deloitte tax experts to understand key regulatory changes in over 100 jurisdictions from over 100 regulators, tax authorities and government bodies. "Tax professionals are being asked to do more with fewer resources--to stay ahead of more risks, draw insights from more data, track more regulations across more jurisdictions. To address these challenges, they are transforming how they operate and manage processes by implementing new technologies, such as AI, robotic process automation and natural language processing," says Conrad Young, Deloitte Global Tax & Legal, Chief Digital Officer.


3 Ways To Transform The Supply Chain With AI (Artificial Intelligence)

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JDA Software and KPMG LLP recently published a wide-ranging survey regarding supply-chain technology. The main takeaway: end-to-end visibility is the No. 1 priority. But in order to make this a reality, the survey also notes that AI (Artificial Intelligence), machine learning (ML) and cognitive analytics will be critical. Yet pulling this off is far from easy and fraught with risks. Well, I recently had a chance to talk to Dr. Michael Feindt.


5 Strategic Steps for Choosing Your Data Labeling Tool

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A growing number of businesses are seeking to apply artificial intelligence (AI) to innovate customer experience and launch disruptive products. If your company is among them, you will need to label massive amounts of text, images, and/or videos to create production-grade training data for your machine learning (ML) models. That means you'll need smart machines and skilled humans in the loop. "Firms achieve the most significant performance improvements when humans and machines work together," wrote Paul Daugherty and Jim Wilson in Harvard Business Review, about their research at Accenture involving 1,500 companies. "Through such collaborative intelligence, humans and AI actively enhance each other's complementary strengths: the leadership, teamwork, creativity, and social skills of the former, and the speed, scalability, and quantitative capabilities of the latter."


AI not gaining ground in HR functions: Arvind Gupta of KPMG explains - ET CIO

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Arvind Gupta, Partner and Head, Management Consulting, KPMG in India, explains why HR functions are still reluctant to use AI, the co-effect of workplace culture and digital transformation on each other and the CIO's role in all of this. Edited excerpts: What factors are causing reluctance in adopting AI in HR functions? One of the main challenges that see's reluctance is the fact that employees' data are not present in one single location. In most cases, the data is distributed over many different data sets; and often the absence of one set in the analytics could lead to a totally wrong estimation. Another challenge is that the world of HR is not one where black and white decisions work.


Artificial Intelligence: Connected Intelligence

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A bigger issue to overcome is the building of trust and confidence in AI. Executives interviewed as part of our 2019 AI Predictions report suggested that ensuring AI systems are trustworthy is their top challenge for the year ahead. And according to our 22nd PwC CEO Survey, 82% of business leaders agree AI-based decisions need to be explainable in order to be trusted. While the overall feeling is that it will create opportunity, opinions vary when it comes to the impact of AI on job figures. In'How will automation impact jobs?' PwC reports that the net impact will be roughly flat, with significant variation by sector.


How To Prep Your Employees For AI Disruption

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In 1888, the London-based accounting firm that became PricewaterhouseCoopers (PwC) faced a major technological upheaval thanks to the Burroughs adding machine. The first-ever mechanized calculator, an invention by William Seward Burroughs, cut the time to perform accounting tasks in half, and PwC's hundreds of workers had to quickly master the new system, or get left in the dust. Today, PwC isn't simply an accounting firm--now it's a global consultancy with 250,930 employees in 158 countries, raking in $43.1 billion in revenue in 2018--but once again it, along with thousands of other companies, faces a seismic technological shakeup with the advent of AI and other advanced technologies. It's rising to meet the challenge by preparing its workers to use digital technologies at all levels, from entry-level staff to C-suite executives. And it's not alone in its reskilling push--AT&T, IBM, Walmart and other forward-leaning companies also have major retraining programs underway.


3 Ways To Transform The Supply Chain With AI (Artificial Intelligence)

#artificialintelligence

JDA Software and KPMG LLP recently published a wide-ranging survey regarding supply-chain technology. The main takeaway: end-to-end visibility is the No. 1 priority. But in order to make this a reality, the survey also notes that AI (Artificial Intelligence), machine learning (ML) and cognitive analytics will be critical. Yet pulling this off is far from easy and fraught with risks. Well, I recently had a chance to talk to Dr. Michael Feindt.


Workforce For the Future

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For forward looking executives and organizations, planning for a digital workforce needs to be a top priority. By working to address future skills needs and talent instability leaders can prepare now to operate effectively in the business environment of tomorrow. Our combined, unique perspective on the Workforce For The Future provides a holistic and integrated view, enabling organizations of all sizes to transition to a technology-enhanced environment, while ensuring that their workforce thrives. As companies transform their business models and strategies to realize the opportunities of the digital revolution, they are challenged with defining their workforce for the future. Given the anticipated scarcity of skills and the need to make workforce management an integral part of business strategy, Mercer, the leading company in HR consulting, and Oliver Wyman, a premier management consulting company, have partnered to support business leaders and HR functions with an integrated talent, digital and skills strategy approach.


Ready. Set. Go! Data Readiness for Artificial Intelligence (AI) GovLoop

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Where does your organization stand? This is the second blog in a four-part series detailing the components necessary for AI success. You can read my earlier post about cultural willingness, which must be prioritized ahead of data and infrastructure readiness (this blog), workforce skilling, and plans for ethics, risk and compliance. Combining the computational power of artificial intelligence (AI) with the critical thinking ability of humans is the ideal solution for organizations looking to accelerate the discovery of actionable insights from their data assets. Even with the human expert in the loop, to achieve valid results with as little bias as possible, AI relies on large volumes of historical data and sophisticated mathematics to generate insights.