Airports can be viewed as microcosms of cities and, as such, offer important lessons to public sector entities around the world. Specifically, emulating the strategies used by airports during the pandemic can help municipalities and others become more resilient. In this Advisor, Denver International Airport CEO Phillip Washington offers a firsthand view into how airports were able to survive, rebound, and move forward after the pandemic-induced downturn.

As AI systems advance and produce increasingly sophisticated and innovative output, the question of how to treat this output under IP law becomes more pressing. The characteristics of some AI systems, including the self-improving nature of certain AI models and the difficulties associated with attributing their outputs to human creators, challenge the existing framework and necessitate a thorough rethinking of what rules will result in the greatest social value.

Women of color are equipped with tried-by-fire strengths that stem from endurance, perseverance, and survivorship. By utilizing these qualities, businesses can expand and grow to meet the diverse needs of their customer base.

In this issue of Amplify, we delve into the ways organizations are developing analytical capabilities that lead to valuable insights and create business value. We also explore the shift from being a data-driven organization to a data-centric one. The latter places data science at its core; data is a primary, permanent asset used as the starting point to determine organizational action. As we explore this shift, it becomes evident that organizations that exploit analytics (and data in general) tend to view it as more than a means to an end — they harness it to create a data-centric culture, establish synergies within and across functions, and deepen relationships with myriad stakeholders.

Bill Schmarzo opens the issue with a thought-provoking article about how companies can unleash business value and economic innovation through AI. Drawing on the seminal work of Adam Smith, Schmarzo explains that “the essence of economics is the creation, consumption, and distribution of wealth — or value” as a baseline for economic innovation. The author brilliantly balances his extensive industry experience and published works to highlight cultural empowerment as a way to foster an inclusive environment to demonstrate value. He identifies 10 critical characteristics of cultural empowerment in the context of leveraging AI and generative AI (GenAI) for economic innovation. Schmarzo also offers the “Thinking Like a Data Scientist” methodology to help business leaders maximize AI to create new sources of customer, product, service, and operational value. The article concludes with an example of integrating GenAI with the methodology to create an economic innovation force multiplier.

Hossein Sahraei, Ramila Peiris, Luc Nguyen, and Olivier Moureau describe how global healthcare company Sanofi transitioned from reactive modes of data analytics (descriptive, diagnostic) to a proactive approach through prescriptive analytics. The authors, who are part of Sanofi's process data science team, provide a refreshing account of their experiences, challenges, and successes, beginning with an acknowledgment that digital transformation goes beyond adopting new technologies to fundamentally change how organizations operate, think, and innovate. They highlight the importance of developing a growth mindset, challenging established norms, and seeing uncertainty as a catalyst for innovation. The authors also explain how the organizational strategy prioritized practicality (an approach based on business needs and limitations), scalability (a framework that can be used in different areas with minimal effort), and sustainability (manageable execution, maintenance, and updates) in product design and deployment. The article reports on the economic value of empowering decision makers, along with benefits such as increased job satisfaction and helping workers maintain a healthy work-life balance.

This Advisor explores key technologies for more accurate tracking of space objects of all sizes, monitoring software that automates collision warnings, and technology that remotely removes objects in orbit. These include two systems that cause decaying orbits, one that uses a specialized satellite to push space objects and one that moves objects into a different orbit from Earth.

Daniel J. Rees, Roderick A. Thomas, Victoria Bates, and Gareth Davies examine the transformational impact that healthcare-related technologies (e.g., AI, wearable sensors, clinical and genetic data) have on the healthcare and pharmaceutical industries. These technologies can potentially transform healthcare business processes, resulting in faster, more efficient decision-making, human-error reduction, and accelerated product development cycles that can lead to faster product launches. The authors gained insights from 48 senior managers in healthcare and pharmaceutical organizations to both identify best practices and understand the challenges related to using healthcare-related technologies and data-centric decision-making to deliver value to stakeholders. Best practices, such as governance (memorandum of understanding), incentives (monetary and nonmonetary), scalability, and collaboration between pharmaceutical makers and technology companies, are identified as key enablers. Such practices enable stakeholders to mitigate challenges like culture (trust, reputation, time, risk aversion), governance (contracts), and scalability. The article concludes with recommendations to ensure the right individuals choose tools and processes that can lead to successful partnerships and transformational initiatives for the benefit of patients, society, and the wider economy.

Antoine Harfouche explains how AI and big data analytics enable smart farming, focusing on the hydroponic forage market. With a current market value of more than US $5 billion, hydroponic systems that leverage technologies like AI, Internet of Things, satellite imagery, and data analytics can optimize environmental controls, improve resource management, and enhance crop resilience. He also outlines the advantages and disadvantages of several such technologies. By combining data, including genomic (epigenomics, transcriptomics, metabolomics), phenomic (plant height, leaf shape, angle, growth trajectory), and environmental (weather and soil, solar radiation, relative humidity), AI can enhance predictive accuracy and decision-making in breeding programs to enhance climate resilience. Harfouche explains the importance of the data value chain, which consists of data capture, data storage, data transformation, data analysis, data interpretation, and feedback. These stages are then instantiated into a framework to demonstrate how AI and big data analytics can be used to improve hydroponic cultivation and improve the sustainability of hydroponic farming. The article concludes with a call for increased collaboration among researchers, farmers, and policy makers to harness these technologies to create a sustainable and secure food production system for the future.

Enjoud Alhasawi, Denis Dennehy, Yogesh Dwivedi, Guoqing Zhao, and Sean Coffey highlight a growing concern about how supply chain disruptions negatively impact both developed and developing countries. The authors provide insights from practitioners at four companies located in Ireland and Kuwait that operate in large, complex agri-food supply chains. They focus on understanding how AI enables resilience in agri-food supply chains. Building on the four dimensions of supply chain resilience (readiness, responsiveness, recovery, and adaptability), the authors show how the companies used robotics and expert systems to mitigate the threat of supply chain disruptions. Drawing on secondary data, they acknowledge that other functions of AI (machine learning, machine vision, natural language processing, and speech recognition) can be applied to various elements of the supply chain, including forecasting, optimization of processes, supplier selection, automation, and decision support for configuration, design, and planning. Anticipating that future supply chain disruptions will threaten the global agri-food sector, the authors call for concerted efforts between industry, the public sector, and academic researchers to build more resilient supply chains.

Through a recent executive leadership roundtable, we learned that top leaders tend to construct their ESG strategies through three lenses (or frames): Games (with referees and rules), Positions (with some being deciders and some doers), or Capitals (with money overpowering other capitals). In short, as this Advisor explains, ESG strategies are neither given nor static. Rather, they evolve depending on the character dimensions of the leaders who envision and enact them.

In this Amplify Update, we first examine the principles of ESG/DEI and how each benefits the organization. Next, we explore obstacles companies face when embracing these initiatives and provide a holistic approach to overcoming challenges and mitigating backlash. By overcoming these issues and effectively integrating ESG and DEI principles into corporate responsibility strategies, companies can create long-term value for stakeholders while advancing their broader mission of responsible corporate citizenship.

With careful design and effective oversight, large language models (LLMs) can be an ally rather than a liability in securing organizations against modern technological threats. This Advisor looks at specific ways responsible LLM adoption can improve security.

Building a high-performance team takes significant effort, and it doesn't occur until all members of the team are working together like a well-oiled machine. In this Advisor, we explore a key ingredient of high-performance teams: leaders who display social intelligence when leading and putting the team together.

In this Advisor, we explore a key trend uncovered by ADL’s 2024 CEO Insights study: AI use, particularly for efficiency and effectiveness, is on the rise; however, many leaders are still on a transformation path to fully understand its impact and integrate it across their organizations.

In this Advisor, Myles Suer offers nine pieces of advice gleaned from a forthcoming book on AI-savvy leadership. Effective leaders can use this advice to propel AI in their organizations and gain real business value.

Pamela McCloskey and Byron Graham explain “why” and “how” organizations in the banking industry are developing and using big data analytics capabilities (BDAC) to derive business value. Their article highlights the importance of a socio-technical approach to analytics: technical resources (e.g., data, technical infrastructure, software tools) and human capital with the skills to use these resources combined with the right social elements to nurture a data-driven culture that ensures the correct use of data for insight and decision-making. McCloskey and Graham present examples of how organizations have drawn on BDACs to successfully respond to recent shocks in the external environment, including the pandemic and regulatory changes in the financial services industry. The authors’ proposed framework for assessing and developing the resource base for BDAC helps organizations understand their level of analytics maturity to maximize operational efficiencies and performance. The framework outlines how (1) process integration (creating a “single source of truth”), (2) process assimilation (restructuring to embed data skills,) and (3) diffusion (creating a data-driven culture) can enable organizations to develop BDACs to increase business value and gain strategic benefit.

Oteng Ntsweng, Wallace Chipidza, and Keith Barrett Carter pose a thought-provoking question: how can organizations harmonize humanistic and financial values using generative AI (GenAI) analytics? The article includes an examination of three real-world cases (PwC, Morgan Stanley, and Ørsted), exploring how GenAI is changing the analytics value chain, how data experts are preparing for the future, and what is being done to re-skill employees to enable effective collaboration between GenAI and employees. Building on insights from these cases, the authors provide frank conversations on ethical digital transformation and AI for social good. Their recommendations include alignment between GenAI tools and need, adopting an employee-inclusive GenAI adoption approach, and promoting leadership teams that are knowledgeable in AI and analytics. The authors conclude that the incorporation of GenAI in business analytics offers the potential for significant advancements in business value, but there is a need to foster collaboration between GenAI and data experts to enhance value without losing humanistic outcomes.

Maria P. Diaz Campo, Arman Ghafoori, and Manjul Gupta explain the growing trend of AI hallucinations (when GenAI generates unreasonable or inaccurate output) and how it can have detrimental consequences for organizations and individuals. The authors suggest that the degree to which such hallucinations are tolerated depends heavily on context and argue that individuals have lower tolerance levels for AI hallucination when the stakes are high (and vice versa when the stakes are low). They point out the importance of considering the contextual nuances surrounding the use of GenAI to help developers, decision makers, and academics establish best practices and manage potential sources of error. They also highlight the significance of understanding culture at the national level, as it can be instrumental in assessing societies’ tolerance levels to AI hallucinations. The authors’ suggested model provides unique insight into levels of analysis (i.e., personality, organizational culture, national culture) and how they pertain to AI hallucination. They make a compelling case that understanding context is critical for making informed decisions about strategically adopting and implementing GenAI (and emerging technologies in general). The article concludes with several key takeaways that can help balance potential value opportunities and risk tolerance.

Conn Smyth, Samuel Fosso Wamba, Murray Scott, Sean Coffey, and Denis Dennehy take a look at the important topic of resilient agri-food supply chains, an issue that affects us all. They report on the challenges facing the industry and explain how agri-food supply chain organizations are leveraging AI-based systems to plan for, respond to, and recover from supply chain disruptions efficiently and cost-effectively. The results show that AI-enabled information processing can build resilience in agri-food supply chains while reducing food waste and improving supply chain performance. The article is part of a wider doctoral research project and is informed by 147 survey responses from practitioners in the global agri-food industry. The authors propose a framework that maps six benefits of AI-based systems to three benefits of the agri-food supply chain and end with a call to action for a concerted effort between industry and academia to design, develop, and deploy AI solutions to make the world a better place.

In this issue of Amplify, we explore several ways organizations leverage business analytics to create business value. As we delve into this dynamic business environment, it becomes evident that leaders who understand their business and data and can strategically align their analytical capabilities are best positioned to derive business value.

Investing in the circular economy involves financial support of businesses and projects that embrace sustainable practices. Unfortunately, a lack of data availability and poor data quality make it difficult for investors to choose where to invest and evaluate the performance of their investments. This Advisor explores new sources of data and emerging technology that can be deployed to offer a more comprehensive understanding of circular investments and performance.

Stakeholders are demanding more than just financial results from organizations. They’re increasing the pressure on CEOs to encourage strong ethical behaviors in their organizations, address social problems, and take a stance on current events. The worldwide increase of social injustice, both inside and outside organizations, demands that CEOs establish cultures and processes that are inclusive of all people.

Effective adoption of next-generation banking technology is the road to greater customer engagement; faster product development; better operational management; and improved compliance, efficiency, and growth. It will also enrich the customer experience through stellar, hyper-personalized service.

In this Advisor, we explore two trends uncovered by ADL’s 2024 “CEO Insights” study: CEOs plan to continue existing growth strategies and are increasing their growth investments.