With a background in building enterprise platforms for organizations, including Oracle and Walmart, Wayfair CTO Fiona Tan oversees all of the technology initiatives for the Boston-based e-commerce company. As the home furnishings retailer begins to open brick-and-mortar stores, it's taking lessons learned from the digital space to inform how it markets its home products to customers in physical locations. On this episode of the Me, Myself, and AI podcast, Fiona joins Sam Ransbotham and Shervin Khodabandeh to discuss how artificial intelligence fuels nearly everything the retailer does, from ad purchasing to product pricing, and where human decision makers fit in. She also describes how AI enables Wayfair's marketing automation technology, as well as some innovative new programs underway to help customers experience the company's products virtually. Fiona Tan is the chief technology officer at Wayfair, where she oversees a global innovation team responsible for creating market-leading experiences through the home furnishings retailer's world-class e-commerce platform. Before joining Wayfair, Tan served as senior vice president of U.S. technology at Walmart, where she was responsible for innovation and engineering execution spanning its site, mobile app, and all associate and merchant-facing technology across its e-commerce business and retail stores in the United States. If you're enjoying the Me, Myself, and AI podcast, continue the conversation with us on LinkedIn. Read more about our show and follow along with the series at https://sloanreview.mit.edu/aipodcast. Give your feedback in this two-question survey.

MIT Sloan Management Review and BCG have assembled an international panel of AI experts that includes academics and practitioners to help us gain insights into how responsible artificial intelligence (RAI) is being implemented in organizations worldwide. This month's question for our panelists: Should RAI be a top management agenda item at organizations across industries and geographies?1 Eighty-six percent of them (18 out of 21) agree or strongly agree that it should be. In aggregate, their replies offer a compelling rationale for top management to oversee RAI efforts. We distill and explain this rationale below. We also conducted a global survey of more than 1,000 executives that generated similar findings: Eighty-two percent of managers in companies with at least $100 million in annual revenues agree or strongly agree that RAI should be part of their company's top management agenda.

MIT Sloan Management Review and BCG have assembled an international panel of AI experts that includes academics and practitioners to help us gain insights into how responsible artificial intelligence (RAI) is being implemented in organizations worldwide. This month, we asked our expert panelists for reactions to the following provocation: Executives usually think of RAI as a technology issue. The results were wide-ranging, with 40% (8 out of 20) of our panelists either agreeing or strongly agreeing with the statement; 15% (3 out of 20) disagreeing or strongly disagreeing with it; and 45% (9 out of 20) expressing ambivalence, neither agreeing nor disagreeing. While our panelists differ on whether this sentiment is widely held among executives, a sizable fraction argue that it depends on which executives you ask. Our experts also contend that views are changing, with some offering ideas on how to accelerate this change.

As chief data officer of payroll and benefits management company ADP, Jack Berkowitz has three primary responsibilities. One is to oversee the organization's data overall, ensuring that functions like data governance, security, and analytics, are running well. Another is to build ADP's data products, such as people analytics and benchmark tools. But the responsibility that's of most interest to Me, Myself, and AI hosts Sam Ransbotham and Shervin Khodabandeh is Jack's oversight of the organization's use of artificial intelligence. In this episode of the podcast, Jack describes how focusing on the outcomes the organization wants to achieve leads to better processes and results. He also dives into the topic of AI ethics and outlines how other organizations might consider assembling an AI ethics board. Jack Berkowitz is chief data officer at ADP, where he leads the company's data security and governance, data platforms, and analytics/machine learning operations. His role also involves partnering with stakeholders to develop new data initiatives to improve clients' experience and ADP's competitive position. Berkowitz joined ADP in 2018 as the senior vice president of product development for the DataCloud people analytics and compensation benchmarking solution.

As artificial intelligence matures and expands within enterprises, leaders across industries are struggling to get everyone on board. At the same time, they must manage customer and employee relationships amid shifting expectations in an era of digital transformation. The latest ideas from MIT Sloan Management Review consider how to overcome the barriers of AI implementation and go all in on putting AI tools into production. Leaders will also learn how to know what customers want, how to avoid a toxic workplace, and how to run effective brainstorming sessions. AI-powered decision-making tools have the potential to increase efficiency, improve service quality, reduce costs, and boost revenue.

Dr. Altman's research focuses on strategy, innovation, platforms, ecosystems, and the future of work. Her work has been published in Harvard Business Review (HBR), MIT Sloan Management Review, Academy of Management Annals, Advances in Strategic Management, Journal of Management Studies, and elsewhere. She was shortlisted for the "2021 Thinkers50 Distinguished Achievement Award for Breakthrough Idea" for research on ecosystems in businesses and organizations. Her 2017 HBR article on product-to-platform transitions has been honored with inclusion in three books in the "HBR 10 Must Reads" series. Before academia, Altman was a vice president at Motorola.

MIT Sloan Management Review and Boston Consulting Group (BCG) have assembled an international panel of AI experts that includes academics and practitioners to help us gain insights into how responsible artificial intelligence (RAI) is being implemented in organizations worldwide. This month's question for our panelists: Should an organization tie its RAI efforts to its overall corporate social responsibility (CSR) efforts? The results present a mixed picture. While 52% of panelists (11 out of 21) believe that an organization's RAI and CSR efforts should be linked, 24% do not (5 out of 21 disagree or strongly disagree), and an equal percentage expressed ambivalence (5 out of 21 neither agree nor disagree). Despite the lack of consensus, there are some common characteristics among those who agree that organizations should link their RAI and CSR efforts, as well as some concerns shared among the remaining panelists.

Many of today's business challenges revolve around two core topics: navigating digital transformation and retaining talent. The latest insights from MIT Sloan Management Review focus on looking past common misconceptions about digital initiatives, setting the right KPIs for digital transformation success, and changing corporate culture and business operations so employees are more likely to stay. Just as today's business leaders should rethink common assumptions about the world of work and re-examine customer expectations, they may also need a new mindset about driving change. MIT Sloan senior lecturer George Westerman identifies four managerial assumptions about digital transformation that prevent enterprises from reaching their true potential. This emphasizes digital but not transformation -- the more difficult (and more important) element to address.

Over the course of her nine-year tenure at LinkedIn, Ya Xu has held technology roles with increasing responsibility. Today, she heads the data function for the online professional networking platform. Ya Xu has been a driving force in transforming LinkedIn into a data-first company since she first joined the organization in 2013. As head of data, she leads a global team of about 1,000 data scientists and AI engineers whose work is at the core of delivering economic opportunities to LinkedIn's members and customers. Xu's emphasis on responsible AI and data science ensures that LinkedIn's AI systems put people first and enables the company to empower its members, better serve its customers, and benefit society. In addition to her work at LinkedIn, Xu has coauthored the book Trustworthy Online Controlled Experiments (Cambridge University Press, 2020), has been named to Fortune's 40 under 40 in tech, and was nominated for VentureBeat's Women in AI Awards. She has delivered countless speeches, including a commencement speech to Stanford's class of 2019 in mathematics, statistics, and mathematical and computational science. Previously, Xu worked at Microsoft and earned a Ph.D. in statistics from Stanford University. Ya joins hosts Sam Ransbotham and Shervin Khodabandeh in this episode of the Me, Myself, and AI podcast, where she discusses AI's essential role in helping LinkedIn create the best "matches" -- content creators with content consumers, job seekers with employers, and buyers with sellers -- within its three key marketplaces. Ya also describes how the company has fostered a data-first culture from the top down, and how its vast amount of economic activity data is helping governments and policy makers worldwide.

With the right technology solutions, companies can aim to relieve rising levels of burnout among health care workers. More than two years into the pandemic, depleted health care workers have been pushed to their limits. In the U.S., we're experiencing what Becker's Hospital Review has described as "an unprecedented nursing shortage." Overworked and risking their own health -- both physical and mental -- to provide care throughout multiple surges of COVID-19, nurses are in crisis. Many are leaving the profession -- and the problem is global.