Data stewardship has become a critical component of modern data governance, especially with the growing use of artificial intelligence (AI). Despite its increasing importance, the concept of data stewardship remains ambiguous and varies in its application. This paper explores four distinct manifestations of data stewardship to clarify its emerging position in the data governance landscape. These manifestations include a) data stewardship as a set of competencies and skills, b) a function or role within organizations, c) an intermediary organization facilitating collaborations, and d) a set of guiding principles. The paper subsequently outlines the core competencies required for effective data stewardship, explains the distinction between data stewards and Chief Data Officers (CDOs), and details the intermediary role of stewards in bridging gaps between data holders and external stakeholders. It also explores key principles aligned with the FAIR framework (Findable, Accessible, Interoperable, Reusable) and introduces the emerging principle of AI readiness to ensure data meets the ethical and technical requirements of AI systems. The paper emphasizes the importance of data stewardship in enhancing data collaboration, fostering public value, and managing data reuse responsibly, particularly in the era of AI. It concludes by identifying challenges and opportunities for advancing data stewardship, including the need for standardized definitions, capacity building efforts, and the creation of a professional association for data stewardship.

No matter the sport, every team is trying to get an edge over the competition. The front office of any organization is always looking for innovative ways to make sure the product on the field reaches its peak. That's why Sevilla FC, one of La Liga's top soccer clubs, has teamed with IBM and its watsonx generative AI to develop a new way of evaluating players in the scouting department. Sevilla FC introduced Scout Advisor Tuesday. It's an innovative tool built by IBM's watsonx to revamp its recruitment process.

"At every major inflection point, there has to be an evolution," says Humera Shahid, chief diversity, equity, and inclusion officer and head of talent development at Intuit. "That means the way that we're organized is different, [and] the skill sets that we need are rapidly changing, especially in technology," Shahid says. Intuit has undergone many iterations since its inception in 1983 as a digital checkbook to help people pay bills, later known as Quicken. Over the past four decades, the $13 billion software firm has repeatedly reinvented itself, notably selling Quicken in 2016, then pivoting from operating solely as a tax and accounting platform to a more holistic financial platform for individuals and small businesses. It recently made two big acquisitions in Credit Karma ($8.1 billion) and MailChimp ($12 billion) as part of its data play.

It's time for Fortune 1000 companies to rethink their investments in data, analytics, and AI. Of course, companies should be investing in these critical business capabilities and differentiators. What they need to take a hard look at is how they're investing, and whether these investments are leading to the kinds of gains and the levels of business value that companies are aspiring to achieve. Responses to a recently released survey of Fortune 1000 and global data and business leaders show that data, analytics, and AI efforts have stalled -- or even backslid. Since 2012, when I launched the survey to investigate organizations' investments in data initiatives, the survey has expanded into related topics such as analytics, AI and machine learning, the role of the Chief Data Officer, and data ethics.

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.

I operated some of the most challenging data analytics landscapes, and I am grateful for those experiences. Namely, early on in my career, I saw exceptional chief information officers struggle landing on their feet, trying to pioneer novelties in how to capture value across the data use cases. At the time I began working in information technology in 2011, the formal implementation of a data officer did not exist in the federal government. Again, we are talking about the U.S. federal government, not the private sector and other industries. Even prior to 2019 (when the data officer function really accelerated for adoption and implementation), the role itself had always existed, whether it be through leadership cells embedded across information officers, information security officers, governance specialists, even cloud architects.

Throughout my career as an unwavering advocate of AI and AI for good, I've had the pleasure of meeting, connecting with, and absorbing wisdom from a variety of individuals. As part of my 10-Part Series of The 9 Inspirational Women Leaders In AI Shaping The 21st Century, I was honored to converse with Linda Avery. Linda is the strategic voice, and visionary for data and analytics at Verizon, focused on using the power of data and AI across the enterprise. Linda joined Verizon in September 2019 and has grown the AI & Data organization to approaching 1,000 contributors by the end of 2021, including teams dedicated to Data Governance, Data Architecture and Engineering, and an AI Center, covering a broad range of disciplines from AI Ethics to Industrialization and Digital Twins. NEW YORK, UNITED STATES - 2020/10/15: Verizon store front displays the 5G network near Grand Central ... [ ] Terminal.

AI is increasingly becoming a business imperative. Nine in 10 Fortune 1000 companies are not only investing in AI, but are increasing those investments, with 92% reporting measurable business benefits from their current AI use -- up from 72% in 2020 and just 28% in 2018, according to a 2022 NewVantage Partners executive survey. Still, only 26% of companies say their AI initiatives have actually moved into widespread production. Cultural barriers, with executives 11 times more likely to say culture is the greatest impediment to AI success than to cite technology limitations as the biggest barrier. And the cultural challenges have actually gotten worse, with 92% of executives citing cultural factors this year vs. 81% in 2018.

The Defense Department's Chief Digital and Artificial Intelligence Office, a new hub to align disparate AI-centered pursuits across the vast enterprise, officially reached initial operating capacity this week--but much must still be puzzled out before it's totally realized this summer. John Sherman, DOD's recently Senate-confirmed chief information officer, will play a major role in seeing it through. He's taking the office's lead as acting chief digital and AI officer until the department completes its search for the right person to fill this first-of-a-kind position. "In addition to getting the OCDAO up and running for [full operational capacity], rest assured we'll remain laser-focused on our CIO duties--cybersecurity, digital modernization and other areas the department relies on us for," Sherman told reporters during a press call on Wednesday. He and two other senior defense officials shared fresh details about the new unit's establishment and what it's ultimately meant to accomplish.

Some organizations may feel that acquiring AI capabilities is a race, and if a company starts late, it can never catch up. That notion is belied by Scotiabank (officially the Bank of Nova Scotia), which has pursued a results-oriented approach to artificial intelligence over the past two years. While some of its resources are devoted to exploring how new technologies -- including blockchain and quantum computing -- might drive fresh business models and products, the great majority of its data and AI work is focused on improving operations today rather than incubating for the future. As a result, Scotiabank -- one of the Big Five banks based in Canada -- has caught up to competitors in some crucial areas. It has done so by more closely integrating its data and analytics work; taking a pragmatic approach to AI; and focusing on reusable data sets, which help with both speed and return on investment.