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AI Adoption in Business: A Comprehensive Guide to Methodologies and Approaches
Author: Dr. Anya Sharma, PhD in Data Science and AI, with 15 years of experience in consulting Fortune 500 companies on AI implementation and strategy.
Publisher: TechInsights Publishing, a leading publisher specializing in technology and business strategy, with a dedicated focus on artificial intelligence and its applications.
Editor: Mr. David Chen, MBA, with 10 years of experience in editing technical and business publications.
Keywords: AI adoption in business, AI implementation, AI strategy, AI methodologies, business transformation, digital transformation, AI benefits, AI challenges, AI risks, successful AI adoption.
Abstract: This comprehensive guide explores the multifaceted landscape of AI adoption in business, detailing various methodologies and approaches for successful implementation. We delve into strategic planning, technological considerations, change management, and risk mitigation, offering practical advice for businesses of all sizes looking to leverage the power of artificial intelligence. The article highlights crucial factors for navigating the complexities of AI adoption in business and achieving a tangible return on investment.
1. Introduction: The Rising Tide of AI Adoption in Business
The integration of artificial intelligence (AI) is no longer a futuristic concept; it's a present-day imperative for businesses striving to remain competitive. AI adoption in business spans diverse sectors, from manufacturing and finance to healthcare and retail, promising transformative advancements in efficiency, productivity, and customer experience. However, the journey from exploration to successful implementation demands a structured and strategic approach. This article provides a roadmap for businesses navigating the complexities of AI adoption in business.
2. Strategic Planning for AI Adoption in Business
Before diving into specific technologies, a robust strategic plan is essential for successful AI adoption in business. This involves:
Identifying Business Needs: Defining clear objectives and quantifiable metrics is paramount. What specific problems will AI solve? How will success be measured? This clarity guides the selection of appropriate AI solutions.
Data Assessment: AI thrives on data. Businesses must assess the availability, quality, and accessibility of their data. Data cleansing, integration, and security are critical considerations.
Skill Gap Analysis: AI adoption in business requires a skilled workforce. Assessing current capabilities and identifying training needs are crucial for successful implementation. This might involve upskilling existing employees or recruiting specialized talent.
Resource Allocation: AI projects require significant investment in infrastructure, software, and personnel. A realistic budget and resource allocation plan are essential.
Choosing the Right AI Technologies: The AI landscape is diverse. Businesses must select technologies that align with their specific needs and resources, considering options like machine learning, deep learning, natural language processing, and computer vision.
3. Methodologies for AI Implementation
Several methodologies can guide the implementation of AI in business:
Agile Development: This iterative approach allows for flexibility and adaptation throughout the project lifecycle, enabling adjustments based on feedback and evolving requirements.
Waterfall Methodology: A more traditional approach, suitable for projects with well-defined requirements and minimal anticipated changes.
DevOps: This approach focuses on collaboration between development and operations teams to streamline the deployment and maintenance of AI systems.
Minimum Viable Product (MVP): Starting with a small-scale prototype allows businesses to test and validate AI solutions before committing to larger-scale deployments. This minimizes risk and allows for early feedback.
4. Overcoming Challenges in AI Adoption in Business
Despite the potential benefits, AI adoption in business faces various challenges:
Data Quality and Availability: Insufficient, inaccurate, or incomplete data can hinder AI performance.
Lack of Expertise: A shortage of skilled AI professionals can delay or impede implementation.
Integration Challenges: Integrating AI systems with existing infrastructure can be complex and time-consuming.
Ethical Considerations: Concerns around bias, privacy, and transparency require careful attention.
Cost and ROI: The initial investment in AI can be substantial, and demonstrating a clear return on investment requires careful planning and monitoring.
5. Change Management and Organizational Culture
Successful AI adoption in business hinges on effective change management. This involves:
Communication: Keeping stakeholders informed throughout the process is essential for building buy-in and managing expectations.
Training and Development: Providing adequate training to employees ensures they can effectively utilize and manage AI systems.
Addressing Resistance to Change: Addressing concerns and fostering a culture of acceptance is vital for smooth implementation.
6. Risk Mitigation in AI Adoption in Business
Businesses must proactively mitigate potential risks associated with AI adoption:
Security Risks: Protecting AI systems and data from cyber threats is crucial.
Bias and Fairness: Addressing potential biases in algorithms is vital to ensure fairness and equity.
Explainability and Transparency: Ensuring that AI decisions are understandable and transparent builds trust and accountability.
7. Measuring Success and ROI in AI Adoption in Business
Tracking key performance indicators (KPIs) is crucial for assessing the success of AI initiatives. These metrics should align with the initial business objectives defined in the strategic plan. Examples include:
Improved efficiency: Reduction in processing time, automation of tasks.
Enhanced accuracy: Reduction in errors, improved decision-making.
Increased revenue: New revenue streams, improved sales conversion rates.
Cost savings: Reduction in operational costs, optimized resource allocation.
8. Case Studies: Real-World Examples of AI Adoption in Business
Numerous successful case studies showcase the transformative impact of AI across various industries. These examples highlight the diverse applications of AI and demonstrate the potential returns on investment. Analyzing these case studies offers valuable insights into best practices and potential pitfalls.
9. Conclusion: Embracing the Future of AI Adoption in Business
AI adoption in business is not merely a technological advancement; it's a strategic imperative for long-term success. By adopting a structured approach, addressing potential challenges proactively, and focusing on measurable outcomes, businesses can unlock the transformative power of AI and achieve significant competitive advantages. The journey requires careful planning, effective execution, and a commitment to continuous improvement. The rewards, however, are substantial, promising enhanced efficiency, innovation, and a competitive edge in the rapidly evolving digital landscape.
FAQs:
1. What are the key benefits of AI adoption in business? Increased efficiency, improved decision-making, enhanced customer experience, cost reduction, new revenue streams, and innovation.
2. What are the biggest challenges in implementing AI in a business? Data quality and availability, lack of skilled personnel, integration complexities, ethical concerns, and cost.
3. How can I choose the right AI technology for my business? Carefully analyze your business needs, data availability, resources, and expertise before selecting specific AI technologies.
4. What is the best methodology for AI implementation? The optimal methodology depends on the project’s complexity, requirements, and the organization's capabilities. Agile, Waterfall, and DevOps are common choices.
5. How can I ensure the ethical use of AI in my business? Establish clear ethical guidelines, implement bias detection mechanisms, prioritize data privacy, and foster transparency in AI decision-making.
6. How can I measure the ROI of my AI initiatives? Define clear KPIs aligned with your business objectives and track them consistently throughout the project lifecycle.
7. What role does change management play in successful AI adoption? Effective change management ensures stakeholder buy-in, addresses resistance to change, and facilitates smooth integration of AI systems.
8. What are some common mistakes to avoid in AI adoption? Underestimating the complexity of implementation, neglecting data quality, failing to address ethical concerns, and lacking a clear ROI strategy.
9. Where can I find resources and support for AI adoption? Consult industry experts, research institutions, and technology providers for guidance and support.
Related Articles:
1. "Building a Successful AI Strategy: A Step-by-Step Guide": This article provides a detailed framework for developing a comprehensive AI strategy, covering aspects from identifying business needs to implementing and measuring success.
2. "The Ethical Implications of AI in Business: A Practical Approach": This article explores the ethical considerations surrounding AI adoption, providing practical guidance on mitigating risks and promoting responsible AI practices.
3. "Overcoming Data Challenges in AI Adoption: A Guide to Data Management": This article focuses on the critical role of data in AI success, offering practical advice on data collection, cleaning, integration, and security.
4. "AI and the Future of Work: Preparing Your Workforce for the AI Revolution": This article examines the impact of AI on employment, offering strategies for reskilling and upskilling employees to thrive in an AI-driven workplace.
5. "Case Studies: Successful AI Implementations Across Industries": This article presents real-world examples of successful AI adoption across various sectors, showcasing best practices and highlighting valuable lessons learned.
6. "Measuring the ROI of AI Investments: A Guide to Key Performance Indicators": This article provides a detailed guide to selecting and tracking relevant KPIs to assess the financial return of AI initiatives.
7. "AI and Cybersecurity: Protecting Your AI Systems from Cyber Threats": This article focuses on the security challenges associated with AI, offering practical strategies for protecting AI systems and data from cyberattacks.
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| ai adoption in business: Artificial Intelligence in Practice Bernard Marr, 2019-04-15 Cyber-solutions to real-world business problems Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success. It is used in areas ranging from banking and finance to social media and marketing. This technology continues to provide innovative solutions to businesses of all sizes, sectors and industries. This engaging and topical book explores a wide range of cases illustrating how businesses use AI to boost performance, drive efficiency, analyse market preferences and many others. Best-selling author and renowned AI expert Bernard Marr reveals how machine learning technology is transforming the way companies conduct business. This detailed examination provides an overview of each company, describes the specific problem and explains how AI facilitates resolution. Each case study provides a comprehensive overview, including some technical details as well as key learning summaries: Understand how specific business problems are addressed by innovative machine learning methods Explore how current artificial intelligence applications improve performance and increase efficiency in various situations Expand your knowledge of recent AI advancements in technology Gain insight on the future of AI and its increasing role in business and industry Artificial Intelligence in Practice: How 50 Successful Companies Used Artificial Intelligence to Solve Problems is an insightful and informative exploration of the transformative power of technology in 21st century commerce. |
| ai adoption in business: Machine Learning and Data Science in the Oil and Gas Industry Patrick Bangert, 2021-03-04 Machine Learning and Data Science in the Oil and Gas Industry explains how machine learning can be specifically tailored to oil and gas use cases. Petroleum engineers will learn when to use machine learning, how it is already used in oil and gas operations, and how to manage the data stream moving forward. Practical in its approach, the book explains all aspects of a data science or machine learning project, including the managerial parts of it that are so often the cause for failure. Several real-life case studies round out the book with topics such as predictive maintenance, soft sensing, and forecasting. Viewed as a guide book, this manual will lead a practitioner through the journey of a data science project in the oil and gas industry circumventing the pitfalls and articulating the business value. - Chart an overview of the techniques and tools of machine learning including all the non-technological aspects necessary to be successful - Gain practical understanding of machine learning used in oil and gas operations through contributed case studies - Learn change management skills that will help gain confidence in pursuing the technology - Understand the workflow of a full-scale project and where machine learning benefits (and where it does not) |
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| ai adoption in business: AI-Driven Intelligent Models for Business Excellence Samala Nagaraj, Korupalli V. Rajesh Kumar, 2022 As digital technology is taking the world in a revolutionary way and business related aspects are getting smarter this book is a potential research source on the Artificial Intelligence-based Business Applications and Intelligence-- |
| ai adoption in business: Platform Strategy Tero Ojanperä, Timo O. Vuori, 2021-10-03 What do Amazon, Google, Visa and AirBnB all have in common? They are all platform businesses. They know they can go beyond their industry segments. They capitalize on wider ecosystems that strengthen their offering and expand commercial opportunities. And now your business can do the same. Welcome to the world of platform businesses. In Platform Strategy one of the world's most creative men in business according to Fast Company and a leading strategy professor at a Financial Times top 40 business school show you the ropes. They lead you through the seven steps you can take to turn your business into a successful platform. Learn to harness emerging technologies like artificial intelligence, cement your business into thriving ecosystems and go beyond industry boundaries. Uncover how business leaders at companies as diverse as John Deere, KONE, and Visa are leading their businesses to the future by reinventing their business model. Authors Tero Ojanperä and Timo Vuori distil the disrupters' methods to an actionable blueprint. In Platform Strategy they put the emphasis on what you can do as leader; harness new technologies, work with partners but also crucially, recognize the fear of change in your people and utilize that energy to drive progress. More than just about technology, this book is at the centre of the leadership agenda for the future. |
| ai adoption in business: Business Trends in Practice Bernard Marr, 2021-11-15 WINNER OF THE BUSINESS BOOK OF THE YEAR AWARD 2022! Stay one step ahead of the competition with this expert review of the most impactful and disruptive business trends coming down the pike Far from slowing down, change and transformation in business seems to come only at a more and more furious rate. The last ten years alone have seen the introduction of groundbreaking new trends that pose new opportunities and challenges for leaders in all industries. In Business Trends in Practice: The 25+ Trends That Are Redefining Organizations, best-selling business author and strategist Bernard Marr breaks down the social and technological forces underlying these rapidly advancing changes and the impact of those changes on key industries. Critical consumer trends just emerging today—or poised to emerge tomorrow—are discussed, as are strategies for rethinking your organisation’s product and service delivery. The book also explores: Crucial business operations trends that are changing the way companies conduct themselves in the 21st century The practical insights and takeaways you can glean from technological and social innovation when you cut through the hype Disruptive new technologies, including AI, robotic and business process automation, remote work, as well as social and environmental sustainability trends Business Trends in Practice: The 25+ Trends That Are Redefining Organizations is a must-read resource for executives, business leaders and managers, and business development and innovation leads trying to get – and stay – on top of changes and disruptions that are right around the corner. |
| ai adoption in business: Artificial Intelligence in Society OECD, 2019-06-11 The artificial intelligence (AI) landscape has evolved significantly from 1950 when Alan Turing first posed the question of whether machines can think. Today, AI is transforming societies and economies. It promises to generate productivity gains, improve well-being and help address global challenges, such as climate change, resource scarcity and health crises. |
| ai adoption in business: Analytical Skills for AI and Data Science Daniel Vaughan, 2020-05-21 While several market-leading companies have successfully transformed their business models by following data- and AI-driven paths, the vast majority have yet to reap the benefits. How can your business and analytics units gain a competitive advantage by capturing the full potential of this predictive revolution? This practical guide presents a battle-tested end-to-end method to help you translate business decisions into tractable prescriptive solutions using data and AI as fundamental inputs. Author Daniel Vaughan shows data scientists, analytics practitioners, and others interested in using AI to transform their businesses not only how to ask the right questions but also how to generate value using modern AI technologies and decision-making principles. You’ll explore several use cases common to many enterprises, complete with examples you can apply when working to solve your own issues. Break business decisions into stages that can be tackled using different skills from the analytical toolbox Identify and embrace uncertainty in decision making and protect against common human biases Customize optimal decisions to different customers using predictive and prescriptive methods and technologies Ask business questions that create high value through AI- and data-driven technologies |
| ai adoption in business: Knowledge Management and Industry 4.0 Marco Bettiol, Eleonora Di Maria, Stefano Micelli, 2020-06-09 The book discusses the opportunities and challenges of managing knowledge in the new reality of Industry 4.0. Addressing paradigmatic changes in value creation due to the development of digital technologies applied to manufacturing (additive manufacturing, IoT, robotics, etc.), it includes theoretical and empirical contributions on how Industry 4.0 technologies allow firms to create and exploit knowledge. The carefully selected expert contributions highlight the potential of these technologies in acquiring knowledge from a larger number of sources and examine approaches to innovation, organization of activities, and stakeholder development in the context of this next industrial revolution. |
| ai adoption in business: The AI Advantage Thomas H. Davenport, 2019-08-06 Cutting through the hype, a practical guide to using artificial intelligence for business benefits and competitive advantage. In The AI Advantage, Thomas Davenport offers a guide to using artificial intelligence in business. He describes what technologies are available and how companies can use them for business benefits and competitive advantage. He cuts through the hype of the AI craze—remember when it seemed plausible that IBM's Watson could cure cancer?—to explain how businesses can put artificial intelligence to work now, in the real world. His key recommendation: don't go for the “moonshot” (curing cancer, or synthesizing all investment knowledge); look for the “low-hanging fruit” to make your company more efficient. Davenport explains that the business value AI offers is solid rather than sexy or splashy. AI will improve products and processes and make decisions better informed—important but largely invisible tasks. AI technologies won't replace human workers but augment their capabilities, with smart machines to work alongside smart people. AI can automate structured and repetitive work; provide extensive analysis of data through machine learning (“analytics on steroids”), and engage with customers and employees via chatbots and intelligent agents. Companies should experiment with these technologies and develop their own expertise. Davenport describes the major AI technologies and explains how they are being used, reports on the AI work done by large commercial enterprises like Amazon and Google, and outlines strategies and steps to becoming a cognitive corporation. This book provides an invaluable guide to the real-world future of business AI. A book in the Management on the Cutting Edge series, published in cooperation with MIT Sloan Management Review. |
| ai adoption in business: Facebook Steven Levy, 2020-02-25 One of the Best Technology Books of 2020—Financial Times “Levy’s all-access Facebook reflects the reputational swan dive of its subject. . . . The result is evenhanded and devastating.”—San Francisco Chronicle “[Levy’s] evenhanded conclusions are still damning.”—Reason “[He] doesn’t shy from asking the tough questions.”—The Washington Post “Reminds you the HBO show Silicon Valley did not have to reach far for its satire.”—NPR.org The definitive history, packed with untold stories, of one of America’s most controversial and powerful companies: Facebook As a college sophomore, Mark Zuckerberg created a simple website to serve as a campus social network. Today, Facebook is nearly unrecognizable from its first, modest iteration. In light of recent controversies surrounding election-influencing “fake news” accounts, the handling of its users’ personal data, and growing discontent with the actions of its founder and CEO—who has enormous power over what the world sees and says—never has a company been more central to the national conversation. Millions of words have been written about Facebook, but no one has told the complete story, documenting its ascendancy and missteps. There is no denying the power and omnipresence of Facebook in American daily life, or the imperative of this book to document the unchecked power and shocking techniques of the company, from growing at all costs to outmaneuvering its biggest rivals to acquire WhatsApp and Instagram, to developing a platform so addictive even some of its own are now beginning to realize its dangers. Based on hundreds of interviews from inside and outside Facebook, Levy’s sweeping narrative of incredible entrepreneurial success and failure digs deep into the whole story of the company that has changed the world and reaped the consequences. |
| ai adoption in business: Trustworthy AI Beena Ammanath, 2022-03-15 An essential resource on artificial intelligence ethics for business leaders In Trustworthy AI, award-winning executive Beena Ammanath offers a practical approach for enterprise leaders to manage business risk in a world where AI is everywhere by understanding the qualities of trustworthy AI and the essential considerations for its ethical use within the organization and in the marketplace. The author draws from her extensive experience across different industries and sectors in data, analytics and AI, the latest research and case studies, and the pressing questions and concerns business leaders have about the ethics of AI. Filled with deep insights and actionable steps for enabling trust across the entire AI lifecycle, the book presents: In-depth investigations of the key characteristics of trustworthy AI, including transparency, fairness, reliability, privacy, safety, robustness, and more A close look at the potential pitfalls, challenges, and stakeholder concerns that impact trust in AI application Best practices, mechanisms, and governance considerations for embedding AI ethics in business processes and decision making Written to inform executives, managers, and other business leaders, Trustworthy AI breaks new ground as an essential resource for all organizations using AI. |
| ai adoption in business: Applications of Artificial Intelligence in Business, Education and Healthcare Allam Hamdan, Aboul Ella Hassanien, Reem Khamis, Bahaaeddin Alareeni, Anjum Razzaque, Bahaa Awwad, 2021-07-12 This book focuses on the implementation of Artificial Intelligence in Business, Education and Healthcare, It includes research articles and expository papers on the applications of Artificial Intelligence on Decision Making, Entrepreneurship, Social Media, Healthcare, Education, Public Sector, FinTech, and RegTech. It also discusses the role of Artificial Intelligence in the current COVID-19 pandemic, in the health sector, education, and others. It also discusses the impact of Artificial Intelligence on decision-making in vital sectors of the economy. |
| ai adoption in business: Knowledge Management in Organizations Lorna Uden, I-Hsien Ting, Juan Manuel Corchado, 2019-06-11 This book contains the refereed proceedings of the 14th International Conference on Knowledge Management in Organizations, KMO 2019, held in Zamora, Spain, in July 2019. The 46 papers accepted for KMO 2019 were selected from 109 submissions and are organized in topical sections on: knowledge management models and analysis; knowledge transfer and learning; knowledge and service innovation; knowledge creation; knowledge and organization; information systems and information science; data mining and intelligent science; social networks and social aspects of KM; big data and IoT; and new trends in IT. |
| ai adoption in business: Deploying Machine Learning Robbie Allen, 2019-05 Increasingly, business leaders and managers recognize that machine learning offers their companies immense opportunities for competitive advantage. But most discussions of machine learning are intensely technical or academic, and don't offer practical information leaders can use to identify, evaluate, plan, or manage projects. Deploying Machine Learning fills that gap, helping them clarify exactly how machine learning can help them, and collaborate with technologists to actually apply it successfully. You'll learn: What machine learning is, how it compares to big data and artificial intelligence, and why it's suddenly so important What machine learning can do for you: solutions for computer vision, natural language processing, prediction, and more How to use machine learning to solve real business problems -- from reducing costs through improving decision-making and introducing new products Separating hype from reality: identifying pitfalls, limitations, and misconceptions upfront Knowing enough about the technology to work effectively with your technical team Getting the data right: sourcing, collection, governance, security, and culture Solving harder problems: exploring deep learning and other advanced techniques Understanding today's machine learning software and hardware ecosystem Evaluating potential projects, and addressing workforce concerns Staffing your project, acquiring the right tools, and building a workable project plan Interpreting results -- and building an organization that can increasingly learn from data Using machine learning responsibly and ethically Preparing for tomorrow's advances The authors conclude with five chapter-length case studies: image, text, and video analysis, chatbots, and prediction applications. For each, they don't just present results: they also illuminate the process the company undertook, and the pitfalls it overcame along the way. |
| ai adoption in business: Using Artificial Intelligence in Marketing Katie King, 2019-02-03 Artificial intelligence (AI) is paving the way for the future of marketing and business transformation, yet many organizations struggle to know exactly how and where to integrate it. This book is the ultimate guide to embracing the opportunity that AI can bring for your marketing. With AI forecasted to boost global GDP by 14% by 2030, an efficient and sustainable AI marketing strategy is now essential to avoid losing the competitive edge. Using Artificial Intelligence in Marketing provides the definitive, practical framework needed for marketers to identify, apply and embrace the opportunity to maximize the results and business advancement that AI can bring. Streamlining efficiencies into every business practice, AI automates simpler, repetitive tasks with unrivalled accuracy, allowing sales and marketing teams to return their attention to where human interaction is most valuable: strategy, creativity and personal connection. Using Artificial Intelligence in Marketing outlines key marketing benefits such as accurate market research samples, immediate big data insights and brand-safe content creation, right through to the on-demand customer service that is now expected 24/7. It also explores the inevitable myths, concerns and ethical questions that can arise from the large-scale adoption of AI. This book is an essential read for every 21st century marketer. |
| ai adoption in business: Artificial Intelligence in Healthcare Adam Bohr, Kaveh Memarzadeh, 2020-06-21 Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data |
| ai adoption in business: Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance El Bachir Boukherouaa, Mr. Ghiath Shabsigh, Khaled AlAjmi, Jose Deodoro, Aquiles Farias, Ebru S Iskender, Mr. Alin T Mirestean, Rangachary Ravikumar, 2021-10-22 This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight. |
| ai adoption in business: A Human's Guide to Machine Intelligence Kartik Hosanagar, 2020-03-10 A Wharton professor and tech entrepreneur examines how algorithms and artificial intelligence are starting to run every aspect of our lives, and how we can shape the way they impact us Through the technology embedded in almost every major tech platform and every web-enabled device, algorithms and the artificial intelligence that underlies them make a staggering number of everyday decisions for us, from what products we buy, to where we decide to eat, to how we consume our news, to whom we date, and how we find a job. We've even delegated life-and-death decisions to algorithms--decisions once made by doctors, pilots, and judges. In his new book, Kartik Hosanagar surveys the brave new world of algorithmic decision-making and reveals the potentially dangerous biases they can give rise to as they increasingly run our lives. He makes the compelling case that we need to arm ourselves with a better, deeper, more nuanced understanding of the phenomenon of algorithmic thinking. And he gives us a route in, pointing out that algorithms often think a lot like their creators--that is, like you and me. Hosanagar draws on his experiences designing algorithms professionally--as well as on history, computer science, and psychology--to explore how algorithms work and why they occasionally go rogue, what drives our trust in them, and the many ramifications of algorithmic decision-making. He examines episodes like Microsoft's chatbot Tay, which was designed to converse on social media like a teenage girl, but instead turned sexist and racist; the fatal accidents of self-driving cars; and even our own common, and often frustrating, experiences on services like Netflix and Amazon. A Human's Guide to Machine Intelligence is an entertaining and provocative look at one of the most important developments of our time and a practical user's guide to this first wave of practical artificial intelligence. |
| ai adoption in business: Competing in the Age of AI Marco Iansiti, Karim R. Lakhani, 2020-01-07 a provocative new book — The New York Times AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value. Now with a new preface that explores how the coronavirus crisis compelled organizations such as Massachusetts General Hospital, Verizon, and IKEA to transform themselves with remarkable speed, Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have restricted business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, allow massive scope increase, enabling companies to straddle industry boundaries, and create powerful opportunities for learning—to drive ever more accurate, complex, and sophisticated predictions. When traditional operating constraints are removed, strategy becomes a whole new game, one whose rules and likely outcomes this book will make clear. Iansiti and Lakhani: Present a framework for rethinking business and operating models Explain how collisions between AI-driven/digital and traditional/analog firms are reshaping competition, altering the structure of our economy, and forcing traditional companies to rearchitect their operating models Explain the opportunities and risks created by digital firms Describe the new challenges and responsibilities for the leaders of both digital and traditional firms Packed with examples—including many from the most powerful and innovative global, AI-driven competitors—and based on research in hundreds of firms across many sectors, this is your essential guide for rethinking how your firm competes and operates in the era of AI. |
| ai adoption in business: Re-imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation Sujeet K. Sharma, Yogesh K. Dwivedi, Bhimaraya Metri, Nripendra P. Rana, 2020-12-15 This two-volume set of IFIP AICT 617 and 618 constitutes the refereed proceedings of the IFIP WG 8.6 International Working Conference Re-imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation on Transfer and Diffusion of IT, TDIT 2020, held in Tiruchirappalli, India, in December 2020. The 86 revised full papers and 36 short papers presented were carefully reviewed and selected from 224 submissions. The papers focus on the re-imagination of diffusion and adoption of emerging technologies. They are organized in the following parts: Part I: artificial intelligence and autonomous systems; big data and analytics; blockchain; diffusion and adoption technology; emerging technologies in e-Governance; emerging technologies in consumer decision making and choice; fin-tech applications; healthcare information technology; and Internet of Things Part II: information technology and disaster management; adoption of mobile and platform-based applications; smart cities and digital government; social media; and diffusion of information technology and systems |
| ai adoption in business: INTELLIGENT AUTOMATION PASCAL. BARKIN BORNET (IAN. WIRTZ, JOCHEN.), 2020 |
| ai adoption in business: The Fourth Industrial Revolution Klaus Schwab, 2017-01-03 World-renowned economist Klaus Schwab, Founder and Executive Chairman of the World Economic Forum, explains that we have an opportunity to shape the fourth industrial revolution, which will fundamentally alter how we live and work. Schwab argues that this revolution is different in scale, scope and complexity from any that have come before. Characterized by a range of new technologies that are fusing the physical, digital and biological worlds, the developments are affecting all disciplines, economies, industries and governments, and even challenging ideas about what it means to be human. Artificial intelligence is already all around us, from supercomputers, drones and virtual assistants to 3D printing, DNA sequencing, smart thermostats, wearable sensors and microchips smaller than a grain of sand. But this is just the beginning: nanomaterials 200 times stronger than steel and a million times thinner than a strand of hair and the first transplant of a 3D printed liver are already in development. Imagine “smart factories” in which global systems of manufacturing are coordinated virtually, or implantable mobile phones made of biosynthetic materials. The fourth industrial revolution, says Schwab, is more significant, and its ramifications more profound, than in any prior period of human history. He outlines the key technologies driving this revolution and discusses the major impacts expected on government, business, civil society and individuals. Schwab also offers bold ideas on how to harness these changes and shape a better future—one in which technology empowers people rather than replaces them; progress serves society rather than disrupts it; and in which innovators respect moral and ethical boundaries rather than cross them. We all have the opportunity to contribute to developing new frameworks that advance progress. |
| ai adoption in business: Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry Chkoniya, Valentina, 2021-06-25 The contemporary world lives on the data produced at an unprecedented speed through social networks and the internet of things (IoT). Data has been called the new global currency, and its rise is transforming entire industries, providing a wealth of opportunities. Applied data science research is necessary to derive useful information from big data for the effective and efficient utilization to solve real-world problems. A broad analytical set allied with strong business logic is fundamental in today’s corporations. Organizations work to obtain competitive advantage by analyzing the data produced within and outside their organizational limits to support their decision-making processes. This book aims to provide an overview of the concepts, tools, and techniques behind the fields of data science and artificial intelligence (AI) applied to business and industries. The Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry discusses all stages of data science to AI and their application to real problems across industries—from science and engineering to academia and commerce. This book brings together practice and science to build successful data solutions, showing how to uncover hidden patterns and leverage them to improve all aspects of business performance by making sense of data from both web and offline environments. Covering topics including applied AI, consumer behavior analytics, and machine learning, this text is essential for data scientists, IT specialists, managers, executives, software and computer engineers, researchers, practitioners, academicians, and students. |
| ai adoption in business: Human + Machine Paul R. Daugherty, H. James Wilson, 2018-03-20 AI is radically transforming business. Are you ready? Look around you. Artificial intelligence is no longer just a futuristic notion. It's here right now--in software that senses what we need, supply chains that think in real time, and robots that respond to changes in their environment. Twenty-first-century pioneer companies are already using AI to innovate and grow fast. The bottom line is this: Businesses that understand how to harness AI can surge ahead. Those that neglect it will fall behind. Which side are you on? In Human + Machine, Accenture leaders Paul R. Daugherty and H. James (Jim) Wilson show that the essence of the AI paradigm shift is the transformation of all business processes within an organization--whether related to breakthrough innovation, everyday customer service, or personal productivity habits. As humans and smart machines collaborate ever more closely, work processes become more fluid and adaptive, enabling companies to change them on the fly--or to completely reimagine them. AI is changing all the rules of how companies operate. Based on the authors' experience and research with 1,500 organizations, the book reveals how companies are using the new rules of AI to leap ahead on innovation and profitability, as well as what you can do to achieve similar results. It describes six entirely new types of hybrid human + machine roles that every company must develop, and it includes a leader’s guide with the five crucial principles required to become an AI-fueled business. Human + Machine provides the missing and much-needed management playbook for success in our new age of AI. BOOK PROCEEDS FOR THE AI GENERATION The authors' goal in publishing Human + Machine is to help executives, workers, students and others navigate the changes that AI is making to business and the economy. They believe AI will bring innovations that truly improve the way the world works and lives. However, AI will cause disruption, and many people will need education, training and support to prepare for the newly created jobs. To support this need, the authors are donating the royalties received from the sale of this book to fund education and retraining programs focused on developing fusion skills for the age of artificial intelligence. |
| ai adoption in business: Customer Relationship Management Jagdish N. Sheth, 2001 Papers presented at an international conference. |
| ai adoption in business: ADKAR Jeff Hiatt, 2006 In his first complete text on the ADKAR model, Jeff Hiatt explains the origin of the model and explores what drives each building block of ADKAR. Learn how to build awareness, create desire, develop knowledge, foster ability and reinforce changes in your organization. The ADKAR Model is changing how we think about managing the people side of change, and provides a powerful foundation to help you succeed at change. |
| ai adoption in business: Intelligent Connectivity Abdulrahman Yarali, 2021-11-01 INTELLIGENT CONNECTIVITY AI, IOT, AND 5G Explore the economics and technology of AI, IOT, and 5G integration Intelligent Connectivity: AI, IoT, and 5G delivers a comprehensive technological and economic analysis of intelligent connectivity and the integration of artificial intelligence, Internet of Things (IoT), and 5G. It covers a broad range of topics, including Machine-to-Machine (M2M) architectures, edge computing, cybersecurity, privacy, risk management, IoT architectures, and more. The book offers readers robust statistical data in the form of tables, schematic diagrams, and figures that provide a clear understanding of the topic, along with real-world examples of applications and services of intelligent connectivity in different sectors of the economy. Intelligent Connectivity describes key aspects of the digital transformation coming with the 4th industrial revolution that will touch on industries as disparate as transportation, education, healthcare, logistics, entertainment, security, and manufacturing. Readers will also get access to: A thorough introduction to technology adoption and emerging trends in technology, including business trends and disruptive new applications Comprehensive explorations of telecommunications transformation and intelligent connectivity, including learning algorithms, machine learning, and deep learning Practical discussions of the Internet of Things, including its potential for disruption and future trends for technological development In-depth examinations of 5G wireless technology, including discussions of the first five generations of wireless tech Ideal for telecom and information technology managers, directors, and engineers, Intelligent Connectivity: AI, IoT, and 5G is also an indispensable resource for senior undergraduate and graduate students in telecom and computer science programs. |
| ai adoption in business: Artificial Intelligence in Banking Introbooks, 2020-04-07 In these highly competitive times and with so many technological advancements, it is impossible for any industry to remain isolated and untouched by innovations. In this era of digital economy, the banking sector cannot exist and operate without the various digital tools offered by the ever new innovations happening in the field of Artificial Intelligence (AI) and its sub-set technologies. New technologies have enabled incredible progression in the finance industry. Artificial Intelligence (AI) and Machine Learning (ML) have provided the investors and customers with more innovative tools, new types of financial products and a new potential for growth.According to Cathy Bessant (the Chief Operations and Technology Officer, Bank of America), AI is not just a technology discussion. It is also a discussion about data and how it is used and protected. She says, In a world focused on using AI in new ways, we're focused on using it wisely and responsibly. |
| ai adoption in business: The AI-Powered Enterprise Seth Earley, 2020-04-28 Learn how to develop and employ an ontology, the secret weapon for successfully using artificial intelligence to create a powerful competitive advantage in your business. The AI-Powered Enterprise examines two fundamental questions: First, how will the future be different as a result of artificial intelligence? And second, what must companies do to stake their claim on that future? When the Web came along in the mid-90s, it transformed the behavior of customers and remade whole industries. Now, as part of its promise to bring revolutionary change in untold ways to human activity, artificial intelligence--AI--is about to create another complete transformation in how companies create and deliver value to customers. But despite the billions spent so far on bots and other tools, AI continues to stumble. Why can't it magically use all the data organizations generate to make them run faster and better? Because something is missing. AI works only when it understands the soul of the business. An ontology is a holistic digital model of every piece of information that matters to the business, from processes to products to people, and it's what makes the difference between the promise of AI and delivering on that promise. Business leaders who want to catch the AI wave--rather than be crushed by it--need to read The AI-Powered Enterprise. The book is the first to combine a sophisticated explanation of how AI works with a practical approach to applying AI to the problems of business, from customer experience to business operations to product development. |
| ai adoption in business: Digital Revolutions in Public Finance Mr.Sanjeev Gupta, Mr.Michael Keen, Ms.Alpa Shah, Ms.Genevieve Verdier, 2017-11-01 Digitization promises to reshape fiscal policy by transforming how governments collect, process, share, and act on information. More and higher-quality information can improve not only policy design for tax and spending, but also systems for their management, including tax administration and compliance, delivery of public services, administration of social programs, public financial management, and more. Countries must chart their own paths to effectively balance the potential benefits against the risks and challenges, including institutional and capacity constraints, privacy concerns, and new avenues for fraud and evasion. Support for this book and the conference on which it is based was provided by the Bill and Melinda Gates Foundation “Click Download on the top right corner for your free copy... |
| ai adoption in business: AI Acceleration: A Comprehensive Guide to Adopting Artificial Intelligence in Your Business Darren G. Burton, 2023-06-28 In a rapidly evolving digital landscape, businesses must adapt to stay competitive. AI Empowered: Unlocking Success through Artificial Intelligence is a comprehensive guide that demystifies the process of adopting AI into your organization. From understanding the fundamentals of AI to developing a robust strategy, managing data, and ensuring ethical practices, this book equips business leaders with the knowledge and tools needed to harness the transformative power of AI. With real-world examples, practical advice, and insights into future trends, this book empowers readers to navigate the complexities of AI adoption, drive innovation, and secure a prosperous future in the AI-driven business world. |
| ai adoption in business: Demystifying AI for the Enterprise Prashant Natarajan, Bob Rogers, Edward Dixon, Jonas Christensen, Kirk Borne, Leland Wilkinson, Shantha Mohan, 2021-12-30 Artificial intelligence (AI) in its various forms –– machine learning, chatbots, robots, agents, etc. –– is increasingly being seen as a core component of enterprise business workflow and information management systems. The current promise and hype around AI are being driven by software vendors, academic research projects, and startups. However, we posit that the greatest promise and potential for AI lies in the enterprise with its applications touching all organizational facets. With increasing business process and workflow maturity, coupled with recent trends in cloud computing, datafication, IoT, cybersecurity, and advanced analytics, there is an understanding that the challenges of tomorrow cannot be solely addressed by today’s people, processes, and products. There is still considerable mystery, hype, and fear about AI in today’s world. A considerable amount of current discourse focuses on a dystopian future that could adversely affect humanity. Such opinions, with understandable fear of the unknown, don’t consider the history of human innovation, the current state of business and technology, or the primarily augmentative nature of tomorrow’s AI. This book demystifies AI for the enterprise. It takes readers from the basics (definitions, state-of-the-art, etc.) to a multi-industry journey, and concludes with expert advice on everything an organization must do to succeed. Along the way, we debunk myths, provide practical pointers, and include best practices with applicable vignettes. AI brings to enterprise the capabilities that promise new ways by which professionals can address both mundane and interesting challenges more efficiently, effectively, and collaboratively (with humans). The opportunity for tomorrow’s enterprise is to augment existing teams and resources with the power of AI in order to gain competitive advantage, discover new business models, establish or optimize new revenues, and achieve better customer and user satisfaction. |
| ai adoption in business: Tech Trends in Practice Bernard Marr, 2020-04-09 ***BUSINESS BOOK AWARDS - FINALIST 2021*** Discover how 25 powerful technology trends are transforming 21st century businesses How will the latest technologies transform your business? Future Tech Trends in Practice will give you the knowledge of today’s most important technology trends, and how to take full advantage of them to grow your business. The book presents25 real-world technology trends along with their potential contributions to organisational success. You’ll learn how to integrate existing advancements and plan for those that are on the way. In this book, best-selling author, strategic business advisor, and respected futurist Bernard Marr explains the role of technology in providing innovative businesses solutions for companies of varying sizes and across different industries. He covers wide-ranging trends and provides an overview of how companies are using these new and emerging technologies in practice. You, too, can prepare your company for the potential and power of trending technology by examining these and other areas of innovation described in Future Tech Trends in Practice: Artificial intelligence, including machine and deep learning The Internet of Things and the rise of smart devices Self-driving cars and autonomous drones 3D printing and additive manufacturing Blockchain technology Genomics and gene editing Augmented, virtual and mixed reality When you understand the technology trends that are driving success, now and into the future, you’ll be better positioned to address and solve problems within your organisation. |
| ai adoption in business: AI Adoption Paul Hankin, 2024-02-24 Are you a business leader looking to stay ahead of the curve and harness the power of AI? Look no further than AI Adoption: A Practical Guide for Business. This comprehensive guide is designed to demystify AI for business, empowering you to make informed decisions and leverage AI to drive growth and success. In this book, you'll learn how to speak AI like a pro, understand the different types of AI tools and their applications, and see real-world examples of how AI is already transforming industries. You'll also discover how to evaluate AI solutions strategically, ensuring they align with your business needs and deliver real value. But that's not all. AI Adoption: A Practical Guide for Business also covers the ethical considerations surrounding AI, helping you navigate the complex landscape of AI and avoid falling victim to hype and bad choices. With expert advice, independent research, and comparison tools at your fingertips, you'll be equipped to make data-driven, objective, and critical decisions about AI adoption. So don't get left behind - read AI Adoption: A Practical Guide for Business today and take the first step towards dominating the AI landscape in your business. |
| ai adoption in business: Working Effectively with Legacy Code Michael Feathers, 2004-09-22 Get more out of your legacy systems: more performance, functionality, reliability, and manageability Is your code easy to change? Can you get nearly instantaneous feedback when you do change it? Do you understand it? If the answer to any of these questions is no, you have legacy code, and it is draining time and money away from your development efforts. In this book, Michael Feathers offers start-to-finish strategies for working more effectively with large, untested legacy code bases. This book draws on material Michael created for his renowned Object Mentor seminars: techniques Michael has used in mentoring to help hundreds of developers, technical managers, and testers bring their legacy systems under control. The topics covered include Understanding the mechanics of software change: adding features, fixing bugs, improving design, optimizing performance Getting legacy code into a test harness Writing tests that protect you against introducing new problems Techniques that can be used with any language or platform—with examples in Java, C++, C, and C# Accurately identifying where code changes need to be made Coping with legacy systems that aren't object-oriented Handling applications that don't seem to have any structure This book also includes a catalog of twenty-four dependency-breaking techniques that help you work with program elements in isolation and make safer changes. |
| ai adoption in business: Artificial Intelligence and Machine Learning in Business Management Sandeep Kumar Panda, Vaibhav Mishra, R. Balamurali, Ahmed A. Elngar, 2021-11-04 Artificial Intelligence and Machine Learning in Business Management The focus of this book is to introduce artificial intelligence (AI) and machine learning (ML) technologies into the context of business management. The book gives insights into the implementation and impact of AI and ML to business leaders, managers, technology developers, and implementers. With the maturing use of AI or ML in the field of business intelligence, this book examines several projects with innovative uses of AI beyond data organization and access. It follows the Predictive Modeling Toolkit for providing new insight on how to use improved AI tools in the field of business. It explores cultural heritage values and risk assessments for mitigation and conservation and discusses on-shore and off-shore technological capabilities with spatial tools for addressing marketing and retail strategies, and insurance and healthcare systems. Taking a multidisciplinary approach for using AI, this book provides a single comprehensive reference resource for undergraduate, graduate, business professionals, and related disciplines. |
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