CUTTER BUSINESS TECHNOLOGY JOURNAL VOL. 31, NO. 2
Old is new again — for good reasons. Artificial intelligence (AI) is now 62 years old; the term was coined in 1956 at a Dartmouth College workshop. Despite intense initial interest, AI developments never quite took off back then and failed to permeate into practice. However, artificial intelligence has now seen a resurgence and has yielded success in practice on several fronts. It has received a facelift, promoting a fresh new look. AI’s renaissance is driven by recent complementary developments, including major advances in the AI arena, realistic expectations, and proven success in its application in various domains, such as finance, healthcare, manufacturing, and agriculture, particularly to address some complex, challenging problems.
Artificial intelligence is no longer just the theme of science fiction essays and movies; it is real and is transforming the way we live, work, and do business. AI encompasses several related technologies, including machine learning (ML), deep learning (DL), natural language processing and translation, and chatbots.
Along with developments in big data, cloud computing, analytics, and the Internet of Things (IoT), artificial intelligence is driving rapid change across all industries. Its impact on individuals and on business and industry will be profound. Some predict that its impacts will surpass those of electricity and industrialization. Indeed, large investments are being poured into research, development, and marketing of AI products, tools, and services. There is also greater awareness among stakeholders than ever before of the advances in AI and of the promises, limitations, and concerns around it. Technology professionals, executives, and businesses need to be aware of ongoing developments in the emerging AI landscape and should harness AI’s potential — both known and hidden — while addressing its risks and concerns.
This scenario raises a few pertinent questions among business executives and technology professionals: Where is AI headed? What new applications and innovations will emerge? What are the real and perceived risks, limitations, and concerns, if any? How will AI transform businesses and industry sectors? What is an appropriate AI strategy? What will evolve as the “new normal”? What new opportunities will arise for the IT industry and technology professionals, and how should they prepare now for excelling in a new age of AI?
In this issue, we examine some of these questions along with the drivers of AI global trends and their implications — now and in the future. Our contributing authors provide insights on key opportunities, strategies, and approaches for realizing AI’s potential and discuss emerging issues and concerns, including how AI may impact jobs and businesses.
The AI Renaissance
Artificial intelligence is creating a lot of excitement and hype — much more than any other new technology — among professionals and across all kinds of business and industry, as well as among individuals. It is a new, innovative approach for solving some of the challenging problems that we encounter in practice, as well as an enabler of disruptive innovations. In the past five years, there have been significant developments in AI, particularly in ML, DL, and chatbots. These developments facilitate autonomous decision making and operations and enable AI applications to learn to perform better from their interactions with us and their environments, to reason with purpose, and to interact more naturally with humans and other smart systems. Helpful applications of AI are emerging in areas such as research and discovery, decision support and advisory, customer engagement, customer experience management, healthcare, the IoT, and cybersecurity. We are also beginning to examine how AI-based systems and humans work together and complement each other’s capabilities. And companies across industries are seriously examining how they can benefit from applying AI in their organizations.
Like any new technology, AI offers promises but also has limitations and presents some risks and concerns. Concerns include its social implications, potential bias in AI systems, the ethics of some of its applications, and its lack of empathy. To benefit from AI’s potential, AI applications must be seen as trustworthy and dependable to gain the acceptance of users.
Advances in artificial intelligence and judicious applications of the advances to address real-life problems have the potential to bring innovations that truly improve business operations and customer engagement, change the nature of work, and boost socioeconomic development in the developed and developing worlds. They also have the potential for better human-machine fusion, complementing and exploiting each other’s unique strengths and capabilities. These innovations will result in disruption so we must acknowledge the new challenges AI will present — not only technical and organizational challenges, but also social, legal, and regulatory hurdles.
IT professionals need to prepare for the new age of AI with education and (re)training. We also need to create new platforms and tools for development, testing, and deployment, and, perhaps more important, a new mindset among developers, users, and regulators. While AI seems to offer huge opportunities, researchers, developers, and businesses alike should focus on addressing meaningful and purpose-driven problems that confront business and society, rather than attempting to address hypothetical or toy problems and coming up with useless or fanciful applications.
While the new age of AI seems real, how it will transform what we currently do and how we address as-yet-unresolved problems and the extent of its impact and penetration — not only in business and industry but also in common use by people of different profiles and needs — will depend upon how we collectively harness its potential, understanding its limitations and addressing the challenges. Let’s prepare ourselves — and the society we are expected to serve — for a better future shaped by AI and other supporting technologies.
This issue aims to reveal some of the emerging AI landscape and serve as inspiration. We present seven thoughtfully selected articles written by established practitioners, consultants, and researchers in AI.
In This Issue
Artificial intelligence can be viewed from many angles and through multiple lenses, and depending how you view it, you will come up with different perspectives on the technology. As a starting point for this issue, Cutter Fellow Steve Andriole presents a brief, multifaceted overview of AI — “the good, the disruptive, and the scary” — and sets the backdrop for further exploration. He outlines some recent advances in and key limitations of AI and explores how AI could disrupt several domains, such as insurance, banking, law, real estate, and education. He then discusses the impact that the deployment of intelligent systems will have on jobs and the professional opportunities that will arise.
AI comprises different technologies and approaches. To exploit its full potential in a given context or application, it is important to connect and embrace those “dots” collectively. In our second article, Cutter Senior Consultant Borys Stokalski, Bogumił Kamiński, and Przemysław Szufel emphasize the need to connect and collectively harness advances in different elements of AI and outline autonomous business entities as examples of convergence of AI. The authors discuss the application of AI, not only to improve business operations, but also for product adaptation and to enable and support business model innovations, thereby making the entire business “smart.” They also explore “data labs” and “data factories,” which facilitate business model innovation. Finally, the authors argue that while AI-driven, radical automation of businesses will replace human work in some areas, humans will remain relevant in others.
Next, we draw your attention to the design, development, deployment, and refinement of cognitive computing systems (CCSs). While CCSs are deployed in a variety of fields yielding benefits exceeding expectations, there are also major failures. According to authors Kevin Desouza, Lena Waizenegger, and Gregory Dawson, lack of appreciation for the differences inherent in developing a CCS versus a traditional software system is key to these failures. To assist in developing successful CCSs and to derive benefits from them, the authors offer a set of nine key recommendations based on their examination of over two dozen systems. They conclude that CCSs will be a dominant technology that will permeate all business operations for the foreseeable future.
The next three articles showcase how AI is being deployed in three major sectors: banking, government, and insurance. First up, Hemamalini Kumaran, Prema Sankaran, and Raj Gururajan discuss how AI is transforming the banking sector. They outline how Indian and US banks are using AI to gain significant benefits and offer an enhanced customer experience. The authors examine the key drivers that inspire banks to embrace AI, the challenges involved in implementing it, and what needs to be considered in applying AI to best serve customers.
Perhaps surprisingly, AI is gaining interest from the government sector, too. In their article, Vipin Jain and Seema Jain discuss the opportunities emerging from artificial intelligence and how cognitive technologies will fundamentally change the way government works. They outline how the US public sector is currently adopting and planning to embrace AI and ML in various applications. They also highlight priorities for federally funded research in the US. To help developers in conceiving and developing AI applications, the authors present an AI adoption framework and briefly discuss the categories of AI-branded services available from leading cloud service providers. They finish with a consideration of whether AI is a job creator or a job destroyer.
Artificial intelligence will compel the adoption of new business models. In his article, Raj Ramesh discusses business model transformation with a focus on the insurance sector. He covers the potential of AI in insurance and then expands his discussion to the ingredients necessary for AI to provide good value to the business in any sector.
Finally, we draw your attention to a key barrier to wider adoption of AI and ML: trust. Researchers Keng Siau and Weiyu Wang examine prevailing concepts of trust in general and in the context of AI applications and human-computer interaction in particular. They discuss the three types of characteristics that determine trust in this area: human, environment, and technology. They emphasize that trust building is a dynamic process and outline how to build trust in AI systems in two stages: initial trust formation and continuous trust development.
Imagining New Realities of AI
Artificial intelligence is driving rapid change across all industry sectors. We are entering new territory and hoping to benefit from the opportunities that AI and ML present. On one hand, ongoing developments and the resulting possibilities are impressive and likely to further transform the world. On the other hand, there are concerns regarding the ethical implications and potential harmful effects of AI applications on society. Moreover, to gain dominance in the AI landscape, there is fierce competition among technology giants as well as startups.
We hope the articles in this issue present perspectives and ideas on fulfilling the promise of artificial intelligence and that you’ll find them interesting, insightful, and practical. We also hope this issue of Cutter Business Technology Journal will help you “imagine the new possible” and inspire and encourage you to harness advances in AI in your domain of interest, addressing any concerns and limitations, for good.
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- Artificial Intelligence: Fear It, Face It, or Embrace It — An Introduction
- The Next Frontier in Automation: Opportunities, Challenges, and Impact — Opening Statement
- Cognitive Computing, Part II: Commercial Cognitive Platforms and Services — Executive Summary
- Cognitive Computing, Part II: Commercial Cognitive Platforms and Services
- Cognitive Technologies in Banking and Finance, Part II