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Artificial intelligence seems to be on the brink of a boom. It's now guiding decisions on everything from crop harvests to bank loans, and uses like totally automated customer service are on the horizon. Indeed, McKinsey estimates that AI will add $13 trillion to the global economy in the next decade. Yet companies are struggling to scale up their AI efforts. Most have run only ad hoc projects or applied AI in just a single business process. In surveys of thousands of executives and work with hundreds of clients, McKinsey has identified how firms can capture the full AI opportunity. The key is to understand the organizational and cultural barriers AI initiatives face and work to lower them. That means shifting workers away from traditional mindsets, like relying on top-down decision making, which often run counter to those needed for AI. Leaders can also set up AI projects for success by conveying their urgency and benefits; investing heavily in AI education and adoption; and accounting for the company's AI maturity, business complexity, and innovation pace when deciding how work should be organized.

In July 2016, in Philadelphia, a group of aspiring entrepreneurs had developed a proof-of-concept prototype for the Drinks-Up! mobile drinks-ordering app, a digital innovation designed to provide a better bar experience. The team had received an investment proposal that included a plan for app development and a partnership opportunity from the potential investor's company, and they were facing an investment decision: Was an agreement that would see the investor develop the app the right option to develop Drinks-Up!? If not, how much time and sweat equity was this really going to take? Was Drinks-Up! truly a disruptive innovation that was worth the risk?

This case highlights the design, process changes and implementation challenges in an e-governance project designed for property registration in the Indian state of Madhya Pradesh (MP). It identifies the critical success factors and the linkages between a good design and acceptance (adoption) both by users of the systems (officials) and citizens. The outdated legal and largely manual processes of the government, the intricacies of public procurement, lack of in-house capabilities and the requirement to interface with citizens make e-governance projects some of the most challenging projects to implement. Computerisation of such systems also leads to a review of underlying processes, changes of roles of employees and organisational restructuring. Adding to this difficulty is the environment of public procurement characterised by poor quality specifications and complex¬¬ regulations. Lack of in-house capabilities often means reliance on vendors and consultants without having the ability to effectively oversee the outputs that often leads to tremendous costs on training and deployment. Designing systems with an interface to citizens involves ensuring proper blueprint and flow of processes that facilitate their usage and contextual user experience, especially as government services may cater to wide variations in citizen profiles. The case highlights the implementation process adopted in developing and executing a web-based solution for property registration in 2015, namely, the Stamps and Management of Property and Documents Application (SAMPADA), under the initiative and leadership of the then Inspector General, Registration and Superintendent of Stamps (IGRS). It highlights the role of the top management, in this case the IGRS, formation of a multifunctional core team, extensive training, focus on an end-to-end solution, web enablement, bringing about the required legal changes, thorough review of existing processes, organisational restructuring and partnership

Alfie.fit (Alfie) was a Montreal-based consumer software technology start-up that offered a virtual fitness concierge service for time-strapped people who wanted to keep fit, no matter their busy schedule. The Alfie platform helped personal trainers and trainees connect and interact with each other and supported the management of the transaction between them. However, Alfie faced several challenges, including the common chicken-or-egg problem of value-added intermediaries in their entry phase. As Alfie celebrated its one-year anniversary of being officially available to the public, the founders needed to make strategic decisions regarding the platform's design, scope, and future direction.

This case describes the genesis and development of a Chinese data analytics startup, TalkingData, from 2012 to 2017. It highlights the strategies pursued and capabilities that the company had built over time in order to secure its position as one of the top data analytics providers in the country. This case also identifies the main challenges that TalkingData needs to address as it continues to grow and expand its businesses and operations. This case is suitable as a standalone in digital innovation and strategy classes to illustrate an emerging breed of firms that rode the waves of Big Data analytics and artificial intelligence (AI), which swept through the technology world in the early 2010s. It highlights these new firms' growth strategies and markets, both new and old. This case can also be employed in business analytics courses to illustrate how companies can build their data analytics and technology infrastructure as a business offering or strategic support for decision-making.

For legacy companies, culture change is often the biggest challenge of digital transformation. How can they become more agile and innovative without alienating their best employees or wrecking their best existing practices? This article provides a framework for leaders in any industry. The process begins with understanding four key values of digital culture: impact, speed, openness, and autonomy. It then involves adopting or refining a set of digital-ready practices, grounded in these values.

Blockchain technologies are benefiting from significant interest in both societal and business contexts. Cryptocurrencies like bitcoin have grown rapidly in user adoption over the past 8 years. However, blockchain technologies, which fuel cryptocurrencies, have the potential to extend to other business applications even more profoundly. Blockchain can be leveraged to drive innovation and increase efficiencies in new domains-including digital arts management, supply chains, and healthcare-but there remain technical, organizational, and regulatory headwinds that must be overcome before mass adoption can occur. In this article, we provide a brief history of blockchain and identify some of the key features that have enabled its popular uptake in the world of cryptocurrencies. We discuss how blockchain technologies have evolved from traditional software and web technologies and then examine their underlying strengths and evaluate new, noncryptocurrency use cases. We conclude with a look at the limitations of blockchain and present several important factors for managers considering blockchain implementation within their organizations.

In a global marketplace, customers are often unaware of the exact sources of the products they purchase and consume. To address this lack of awareness, blockchain technology can be implemented in supply chains to increase customers' knowledge of products' provenance. Provenance knowledge-information about products' origin, production, modifications, and custody-enables customers to be assured of their purchasing decisions. This assurance comes from information on the origin, authenticity, custody, and integrity of the product that helps reduce risk perceptions. We develop a provenance knowledge framework and show how its application can enhance assurances and reduce perceived risks via the application of blockchain. We present a guide on how to implement blockchain to establish provenance knowledge and close with a kind warning on the importance of demonstrating the value of blockchain to customers.

Much of the attention surrounding blockchain today has focused on financial services, with very little discussion about nonfinancial services firms and how blockchain technology may affect organizations, their business models, and how they create and deliver value. In addition, some confusion remains between Blockchain (capital letters) and blockchain (lower case), distributed ledger technologies, and their applications. Our article offers a primer on blockchain technology aimed at general managers and executives. The key contributions of this article lie in providing an explanation of blockchain, including how a blockchain transaction works and a clarification of terms, and outlining different types of blockchain technologies. We also discuss how different types of blockchain impact business models. Building on the well-established business model framework by Osterwalder and Pigneur, we outline the effect that blockchain technologies can have on each element of the business model, along with illustrations from firms developing blockchain technology.

The ongoing discussion on blockchain technologies is mainly focused on cryptocurrencies, but blockchain features and functionalities have developed beyond financial instruments. As the technologies provide new functionalities, the associated value proposition changes as well. This study explores the relationship between blockchain technologies and their underlying value drivers. Four identified distinct blockchain stages of increased maturity are analyzed and discussed. This covers the evolutionary technology types focused on transactions, smart contracts, decentralized applications, and the introduction of artificial intelligence supporting decentralized decision making. In addition, we address management issues around appropriate blockchain adoption through the use of a blockchain value driver driver-focused framework that gives decision makers actionable questions and recommendations. We provide practitioners with a method for assessing suitable blockchain adoption that addresses the specific value creation associated with a given organizational strategy. For academics, we critically identify and assess the characteristics of the blockchain stages and their strategy implications and provide a structured approach conceptualizing blockchain technology evolution.

AI-driven text mining, a relatively new business analytics tool, allows users to unlock troves of information contained in documents and make them searchable by content and metadata. The ability to analyze documents requires a number of intricate steps. First, optical character recognition must be used to convert a document image into machine-readable text. The text must then be converted to a format in which it can be analyzed. Finally, information must be extracted from the documents. This case takes students through some of the theory behind and examples of text analysis. This case is a companion to Evisort: An AI-Powered Start-up Uses Text Mining to Become Google for Contracts (Case ID: CU251)

MDSC is a 501(c)(3) organization, professionally staffed with a mission to ensure individuals with Down syndrome are valued, included, and given opportunities to pursue fulfilling lives. Though dedicated to the families of Massachusetts, MDSC is gaining recognition as an innovator and being called upon to train and support organizations in other parts of the US and world. When the case opens, MDSC's executive director, Maureen Gallagher, is departing a strategic planning retreat. She and her Board members have come up with an exciting list of strategic initiatives, including areas for potential service expansion. However, current initiatives and needs of its steadily expanding community were beginning to overwhelm the current operational model. MDSC had the know-how, the ideas, and the drive to do more, but this operational reality would constrain further service expansion. In addition to specifying three overarching directives and four specific strategic initiatives to support these directives, the board also determined that MDSC would move to a state-of-the-art approach to support its growing list of state-of-the-art services. The approach would include a revamped operational model built upon an updated digital platform. With these changes, MDSC would be able to scale its services to families, increase its donations, and win more grants to help sustain the organization's good work. Though there is consensus in the vision, there are questions regarding the steps this small, resource-constrained organization should take to make this vision.

"Arizona Medical Doctors" (disguised) seeks a cost-effective solution to improve its medical claims coding quality. The new Vice President of Revenue Cycle Management learns that a contract was signed with a software firm to develop and implement, for the first time, an artificial intelligence (AI) solution that will combine natural language interpretation and machine learning for Evaluation & Management (E&M) medical coding. If it works, the new system will improve E&M coding quality at a very low cost compared with the company's current human quality control process. The VP needs to decide whether to go forward and if so, how to mitigate the significant project and business risks. The case introduces students to two branches of artificial intelligence: natural language interpretation (newer, riskier technology than speech recognition) and machine learning. Students are challenged to recognize the relationship between IT project risks and business risks, spot high-level IT project risks and consider how to mitigate them, and to consider implications for managing rapidly-evolving emerging technologies in health care and other contexts.

In 2016, Toronto entrepreneur Andy Hoang was working to launch a new business, Aviron Interactive Inc., a developer and marketer of interactive rowing machines that would use gamification to allow users to work out with others through a virtual connection and an innovative, remotely-activated resistance adjustor. Hoang wanted to create the new business by wrapping an outsourced services model around a central core that included the key business insight, key differentiating product and technology features, and the leadership of a founding team. The other elements required of a startup-engineering, product design, product development, software coding, testing, quality assurance, marketing, sales, and so on-would be outsourced to various niche suppliers, and the central core would oversee the governance of the supplier portfolio. Hoang knew the company would be competing with similar video-based rowing machines as well as indoor rowing apps. He had a limited budget and wanted to design, develop, and launch the product quickly, to stay ahead of his competition. Would a traditional business model or a lean, agile model be best for this project?

In an era of increasing technological transformation, the lines among industries, competitors, and companies are blurring as firms and platforms combine to create unique methods for engagement. Survival and growth in a rapidly changing marketplace requires incumbent companies to divest themselves of legacy thinking and to embrace internal innovation that adds value for both channel members and customers. This entails understanding the mechanisms of process digitalization, communications digitalization, and buyer digitalization. It requires incumbent firms to build and innovate on strengths currently possessed in-house and to identify and cover resource gaps. Incumbents also must work to overcome organizational inertia and effectively implement an agile approach for digitalization across the company, channels, and customer triumvirate. In sum, incumbents must: (1) consider and embrace gains from the digitalization of process, communications, and buyer; (2) respect the core business while recognizing that elements of the existing business model must adapt to changing channels and customer expectations; and (3) recognize that digitalization comes in many forms with multiple applications.

I@NS was intended to mimic the experience of founding a start-up, getting it funded, building a product, and taking it to market, with all the potential risk and reward this entailed. Except, of course, this particular start-up experience would occur within Nokia Corporation, a 150-year-old global company with 103,000 employees working in more than 100 countries-a company that described its mission as "creat[ing] the technology to connect the world." Given this rather unusual "start-up" environment, the creators of the program had no idea how it would all unfold. But, they went ahead and established it, evangelized it to Nokia Software employees around the world, judged the first round, and then launched a second round, which was still underway at the time this case was written. In the process of creating I@NS, its founders learned many important lessons about encouraging and supporting innovation and a start-up mentality within an established corporation. The case covers many elements of the design and implementation of an innovation program including: Strategic objectives of innovation processes; Defining success; Determining the scale and scope of new ventures; The staging of the innovation process; The gating and funding decision making process; The definition of the strategic objectives behind the innovation process; Communicating the process to the wide organization; Communicating (the go/no go) gating decisions; Identifying and allocation resources; Recruiting evangelists and mentors; Team formation and composition; How the process interacts with and impacts the culture in the organization; Incentives for innovation; Career development paths for innovators; Attitudes to risk.

I@NS was intended to mimic the experience of founding a start-up, getting it funded, building a product, and taking it to market, with all the potential risk and reward this entailed. Except, of course, this particular start-up experience would occur within Nokia Corporation, a 150-year-old global company with 103,000 employees working in more than 100 countries-a company that described its mission as "creat[ing] the technology to connect the world." Given this rather unusual "start-up" environment, the creators of the program had no idea how it would all unfold. But, they went ahead and established it, evangelized it to Nokia Software employees around the world, judged the first round, and then launched a second round, which was still underway at the time this case was written. In the process of creating I@NS, its founders learned many important lessons about encouraging and supporting innovation and a start-up mentality within an established corporation. The case covers many elements of the design and implementation of an innovation program including: Strategic objectives of innovation processes; Defining success; Determining the scale and scope of new ventures; The staging of the innovation process; The gating and funding decision making process; The definition of the strategic objectives behind the innovation process; Communicating the process to the wide organization; Communicating (the go/no go) gating decisions; Identifying and allocation resources; Recruiting evangelists and mentors; Team formation and composition; How the process interacts with and impacts the culture in the organization; Incentives for innovation; Career development paths for innovators; Attitudes to risk.

In 2017, Cathay Pacific Airways Limited (Cathay Pacific) began its largest transformation program in 20 years in response to business hardships the airline had been experiencing since 2016. The program used digital enablement and insight orientation to realign the company's newly defined business focuses and to establish supporting pillars for further development. Information technology (IT) not only played a lead role in this corporate transformation, but it also became increasingly vital to Cathay Pacific's future growth. In 2018, this transformation seemed successful, but important questions remained regarding the development of Cathay Pacific's IT strategy over the previous decade, the company's focus for its IT investments, and the factors that led the company into hardship. As it moved forward, how far could Cathay Pacific go with its digital transformation? How could IT influence the company's future business strategy: could it help Cathay Pacific avoid further turbulence?