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Should AI Be Part of Your Digital Transformation Strategy? - InformationWeek

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AI is seeping into enterprises from all directions. It's being embedded in applications, software tools, devices and equipment. Yet, some organizations still don't have an AI strategy. "The journey to AI having an impact at a firm is challenging and sometimes long," said Nigel Duffy, global artificial intelligence leader at professional services firm EY. "To have an impact with AI you must solve a lot of problems, many of which have nothing to do directly with AI, [such as] how do you deploy solutions? How do you get them into your infrastructure? How do you get people to use them? What are the workforce and change management considerations? What kind of training is required? AI is too disruptive to ignore. If your company lacks an AI strategy by design, then it has one by default. A default strategy is a Wild, Wild West scenario in which AI is popping up in various places within an organization, without orchestration and alignment. The lack of cohesion and direction can result in several issues including governance and security. "[S]ome of those risks may not be well characterized, so they have not been addressed by the appropriate level of governance and review," said Duffy. "Most AI is going to come through procurement or it's going to come through the backdoor or technology you've deployed." Should an AI strategy be part of a digital transformation strategy? One reason some people think an AI strategy should be part of a digital transformation strategy is because the digital transformation strategy is viewed as the overarching business initiative that's facilitated by modern technologies. "If an organization's digital transformation strategy does not already include AI, then there is a real need to revisit the overall approach to transformation, said David Homa, director of the Digital Initiative at Harvard Business School.


Professionalization of Artificial Intelligence (AI)

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As organizations invest more in their AI and data capabilities, employees understand the growing influence of these technologies on their companies and careers. But despite their best efforts, many of these employees will not have the right training and qualifications to work effectively with AI. It's important for organizations to establish education and training requirements for their AI practitioners. Data scientists have varying qualifications, and not all have sufficient training in mathematics or computer science for AI projects. Even an employee with a Ph.D. might have studied a narrow field that isn't relevant to a particular company's needs.


Raising the Bar on Contract Management With AI

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Contract life cycle management systems have been around for decades, but the latest generation of AI-enabled tools can help elevate the contracting function. In recent years, organizations that have struggled to understand and manage the entirety of their obligations to customers and suppliers have shown increasing interest in their company's contract life cycle management (CLM). Specifically, organizations seem to be focused on CLM operating models, processes, and enabling technologies to manage these critical obligations. That appetite has increased in the wake of COVID-19, as many companies wrestle with a lack of visibility into their contracts across the enterprise. In the past, some organizations have standardized their processes within certain silos or even implemented CLM technology.


AI's Growing Cyber Role in the Virtual World

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By aggregating vast quantities of data and uncovering subtle patterns, AI can reduce the cognitive burden on human cyber professionals and help create more resilient organizations. Cyber threats have long tested the resilience of organizations around the world, but the growing shift to virtual ways of working is dramatically altering the threat landscape, with the potential for greater risks than ever. Increasingly, AI can provide valuable assistance, not only in the race to detect new threats or the spread of new diseases, but also to uncover threat actors and criminal groups taking maximum advantage of the situation to target cyber vulnerabilities, according to Deborah Golden, U.S. cyber practice leader at Deloitte & Touche LLP. "Cyber is everywhere, and the gap in cyber talent remains a challenge," Golden said. "Adversaries can try thousands of times to attack any one cyber vulnerability, but they only need to be right once; in the fight against these threats, organizations need to be right every single time. Now, with so many people working remotely, many for the first time, the risks to data, systems, and networks are further compounded."


Why Most Organizations' Investments in AI Fall Flat - SPONSOR CONTENT FROM PWC

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With how pervasive artificial intelligence (AI) is these days, executives--up to 85% of executives, in fact--know AI can fundamentally change their businesses. Organizations can look to use AI for everything from automating back-office processes to improving customer experience. In today's COVID-19 era, companies are adopting automation technologies to help compensate for disruption of core operations. Despite this enthusiasm, 76% of organizations surveyed barely broke even with their investments in AI capabilities. Only 6% had AI initiatives scaled across the enterprise, according to the Analytics Maturity Model (AMM) survey, developed jointly with Carnegie Mellon University through the Digital Transformation and Innovation Center sponsored by PwC.


ROI for artificial intelligence

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Elite athletes know that in order to perform on the field, they first have to put in the prep work--proper nutrition and sleep, building strength and endurance in the gym. As more and more companies adopt AI technologies, they are quickly learning this same lesson: To get a big return from AI, they must first put in the preparation. As the adage goes, "Failing to prepare is preparing to fail." The research firm ESI ThoughtLab recently published a benchmarking study (cosponsored by Deloitte) exploring how companies are approaching their AI implementations, what value they are seeking, and what they are achieving.1 Today, companies are generally seeing a positive ROI from their AI implementations.


AI Comes in Many Flavours

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Artificial Intelligence has become a nearly ubiquitous term nowadays. A Deloitte survey revealed that most companies -- a staggering 90 percent of those approached by the research and consultancy firm -- consider cognitive technologies to be of crucial strategic importance, and over 80 percent of those were either already using it on some level or planning to implement it in the near future. That is hardly surprising considering the dramatic efficiency savings that adoption can bring. According to Bill Eggers, executive director of Deloitte's Center for Government Insights, in the U.S. alone, federal employees spend about 4.3 billion hours per year on a variety of mundane tasks such as recording information and handling. He estimates that currently available AI and robotic process automation could free up about 1.3 billion of those hours by automating such tasks, effectively enabling quantum leaps in productivity as AI allows institutions to anticipate rather than merely react to problems after they occur.


Deloitte Launches CortexAI Platform – Press release

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NEW YORK, Oct. 13, 2020--According to Deloitte's "2020 State of AI in the Enterprise, 3rd Edition" study, 83% of respondents believe that artificial intelligence (AI) will be very or critically important to their business success in the next two years, but only 47% feel they have a high level of skill in selecting AI technologies and suppliers. As AI becomes more widely available and crucial to market leadership, organizations need to swiftly apply AI within their businesses. To help solve for rapid AI integration, Deloitte today announced its CortexAI platform. An award-winning solution already in market and proven in client engagements by Deloitte audit and tax clients, CortexAI is now being expanded to Deloitte consulting and risk and financial advisory clients. CortexAI brings together Deloitte's unique expertise with the power of an AI platform to rapidly develop and deploy scalable, applied AI solutions that drive impact and enable companies to garner fast results and return on investment.


CFO Insights: Why CFOs Should Have Artificial Intelligence on Their Minds

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Smart CFOs now have to give serious thought to artificial intelligence (AI). The technology, which enables computers to be taught to analyze data, identify patterns, and predict outcomes, has evolved from aspirational to mainstream, opening a potential knowledge gap among some finance leaders. In fact, "AI's'early adopter' phase is ending," according to the recently published third edition of Deloitte's State of AI in the Enterprise report.1 The survey, which collected responses from nearly 2,750 executives at companies that have adopted AI, found that about half of respondents (47%) were "skilled" in their AI efforts, meaning that their companies had launched multiple AI systems, but lagged in terms of their number of implementations or their AI expertise--or both. Another 26% were categorized as "seasoned," given that they had already built multiple AI systems and shown a high level of maturity in selecting, managing, and integrating AI technologies.


What Can You Do With Unstructured Text Data

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The health & safety of our attendees & speakers is our primary concern. While this currently proves to be a tricky time for public gatherings, Dataiku is still committed to providing great tech content & facilitating discussions in the data science space. As such, weve decided to pivot towards online webinars via our partner platform, BrightTalk. IMPORTANT - RSVP HERE: https://www.brighttalk.com/webcast/17108/445121?utm_source Dataiku&utm_medium brighttalk&utm_campaign 445121 Tentative Schedule: (EST) 2:00pm: Intro 2:05pm: What Can You Do With Unstructured Text Data? w/ PwC 2:45pm: Q&A Talk Abstract: In this talk we will explore the opportunities that arise from unstructured text data. Then we will take a deep dive into a few concepts that are used in applying Machine Learning to text data & discuss how can they be leveraged using deep learning & other methods Speaker Bio: Abdallah Musmar is a Manager at PricewaterhouseCoopers.