Women in AI experts will explore the definition of fringe as it applies to humans and societies, and how we can find joy in and around the boundaries. Energy complexities and heavy regulations demand bold transformations that are sustainable and responsible. The panelists will share personal reflections and industry innovations where reactivating lost and misinformed stories are valuable (for example, across sociology, ethnography, space technologies, and investments). Adoption of modern frameworks is critical to expand enterprises beyond the legacy, and towards the uncharted.

Technical Debt is entropy applied to technology. Systems age, standards change, mistakes occur, and updates happen. The moment you buy any technology, you have to maintain it—but since technical failure is often hard to detect until something catastrophic occurs, systems begin to drift away from their initial operating state.

The faster an industry changes, the more quickly technical debt accrues. A farm tractor in the 1960s might still be in service today, because relatively little variance has happened; but a modern, GPS-guided piece of farm equipment needs constant software updates. And IT is changing much more quickly than tractors.

But constant support means rising costs in an organization asked to do more with less. Invest in maintenance and you'll be reliant on outdated systems amidst spiraling expenses; neglect them, and you'll constantly be chasing the new thing while scrambling to repair outages on legacy systems.

What's a savvy CIO to do? In this panel discussion, DM Radion's Eric Kavanagh hathers a panel of experts on digital transformation, AI-infused metamorphosis, and the role emerging technology plays in clearing the clutter of outdated IT stacks.

AI is not only a disruptor but an enabler for delivering faster, leaner, and smarter solutions. In this session, Austin Vance, CEO and Founder of Focused Labs, explores how balanced cross-functional teams can harness the power of AI to optimize workflows, streamline collaboration, and mitigate risks while ensuring quality delivery.

Our discussion will center on reframing the narrative around AI, emphasizing its role in accelerating existing processes rather than replacing human expertise. We will delve into practical examples of AI-enabled initiatives for AI-driven design and development.

Furthermore, we will examine the implications of AI-driven development and how it can revolutionize traditional software engineering practices. By automating tedious tasks, augmenting decision-making capabilities, and enhancing information retrieval, AI has the potential to redefine the dynamics of software development teams.

Women in AI experts will provide a unique perspective on why it is important to start with the data for algorithms to be ethical, be it for new transformations or for enterprise transitions towards the Generative AI era. Data governance along with regulatory audits are not sufficient anymore, and the multifaceted responsibilities towards an accessible and inclusive future for all humans requires a comprehensive data strategy. The panelists will share industry perspectives from finance and sustainability that emphasize privacy, security, synthetic data, and maturity scores to scale ethical models.

Artificial intelligence (AI) is rapidly transforming the corporate world, with documented benefits such as improving efficiency and decision-making. However, the use of AI also raises several ethical concerns.

In this presentation, Dr. Serena Huang will discuss the double-edged sword of AI in the corporate world, including the key opportunities and risks. She will share lessons learned from implementing AI-based solutions on employees and offer practical guidance on addressing ethical concerns. Attendees will learn how to set up ethical "data councils" in F100 corporations, and provide actionable tips for organizations to unlock the full potential benefits of AI. 

Data-informed organizations outperform those who shoot from the hip. But while data is transforming front-office business and optimizing back-office productivity, applying it to talent still lags. Can we re-think how we find and nurture talent in the workplace?

In this session, Woxsen University's Raul Rodriguez explores how to apply machine learning, data harvesting, and algorithmic tools to identify your best talent, personalize their growth, and create a path forward for your best-performing team members.

AI fever has infected enterprises across the world. But hasty implementation, unrealistic expectations and poorly defined goals have often led to floundering or failure. The problem? Most leaders simply don’t know the right questions to ask to unlock the potential of both their AI and organizations. In this session, Domo's Chief Design Officer and Futurist Chris Willis will reveal how to address the four critical questions needed to unlock AI's true potential: 1. Is AI the right solution? 2. Can your data deliver? 3. Do you have the right talent? 4. Are there ethical risks? Leave this session armed with a checklist and confidence to begin getting more AI-powered success at your organization.

Customer Lifetime Value (CLV) is the cornerstone of any recurring-revenue or service business. It's one of the most important metric in contemporary business analytics, showing the long-term profitability and sustainability of customer relationships.

In this session, Ranjeeta Bha will explore the significance of CLV, how it's calculated, and the many factors that influence it such as customer acquisition costs, retention strategies, and revenue forecasting. We'll explore what makes customers quit—and how to predict it. Attendees will understand how to gain a comprehensive understanding of their customer base, as well as how emerging statistical and AI approaches can be used to estimate CLV.

There's no problem more existentially fundamental than climate collapse. Nations and businesses worldwide are scrambling to adapt, anticipate, and mitigate while dramatically reducing the impact they have on the planet. In this session, data and AI expert Navdeep Martin looks at how three organizations were already tackling these monumental changes—and how generative AI is changing their transformations.

Women in AI experts will discuss why data matters for inclusion to be effective in the models being trained. Understanding not only the outputs for individuals, rather how outcomes impact broader communities is a key consideration. Continuously iterating and testing the models is critical to address gender inequities, and the panelists will explore industry use cases from the financial services sector, as well as disinformation in news and media.

In a rapidly evolving professional landscape, the integration of Artificial Intelligence and other disruptive technologies is reshaping the way we work. This talk by Sadie explores the seismic shifts in work culture, expectations, and roles for leaders, managers, and employees alike. In navigating these changes, the emphasis is on the necessity for a mindset of perpetual learning and curiosity. Sadie will provide actionable insights and recommendations to not just adapt, but thrive, in the next era of work. C-Suite Executives, Entrepreneurs, and Decision-Makers will come away better equipped to lead their organizations into a future that's already here. 

In the fast-paced world of data driven decision making, organizations are grappling with the challenge of realizing insights as quickly and efficiently as possible. While data products have been quite a steady architectural pillar within data ecosystems, AI has recently taken the world by storm - helping to accelerate insights at a pace previously unimaginable. In this session hear from Fahad Ahmad, data science leader at Halliburton, about their strategy to transform Halliburton’s previous data swamp into a decentralized data mesh architecture utilizing open AI and data products to deliver real-time insights. Fahad will discuss eliminating fragile data pipelines, fast data-driven decision making on curated datasets, and the innovative usage of ChatGPT to expedite the creation of data products.

Discover the hidden power of feature engineering in revolutionizing machine learning performance. This talk explores how crafting informative features transforms model outcomes, offering practical techniques and real-world examples. From understanding data intricacies to optimizing model efficacy, learn why feature engineering is the ultimate key to enhancing machine learning success. 

Data virtualization had been held back by complexity for decades until recent advances in cloud technology, data lakes, networking hardware, and machine learning transformed the dream into reality. In this fireside chat, hear from authors of the new O’Reilly book Data Virtualization in the Cloud, Dr. Daniel Abadi and Andrew Mott, as they discuss in detail what data virtualization is and the trends in technology that are making data virtualization increasingly useful. Moderated by Starburst’s Field CDO Adrian Estala, the trio will explore the architecture of modern data virtualization systems and learn how these systems differ from one another at technical and practical levels.

While everyone's talking about AI, far fewer have deployed it successfully or turned technology into business outcomes. This panel changes that, bringing together Generative AI experts for a deep dive into the practical application of generative AI. From building new customer offerings to refreshing internal processes, the panellists will reflect on the importance of data quality, data security, the responsible use of data as well as change management when it comes to embedding generative AI into the business strategy.

Step into the dynamic world of data governance, business operations, and artificial intelligence (AI), where the unsung hero—metadata—takes center stage. Just like the perfect sandwich relies on clear definitions of its ingredients, this talk unveils the indispensable role of metadata in defining and organizing data.

George will share captivating real-life stories and examples on how clarity in definitions and metadata not only streamlines operations but also empowers decision-makers with invaluable insights.

Explore the backbone of AI advancement through essential data management tools: the Business Glossary, Data Dictionary, Data Catalog, and Machine Learning Metadata Store. Let's embark on a journey where unified interpretations pave the way for accuracy, efficiency, and success in the data-driven era.

The emergence of pre-trained deep learning models – e.g., Foundation and generative AI models – such as GPT-4, represents a paradigm shift in the utilization of AI. This keynote, rooted in the insights from "AI iQ™ for a Human-Focused Future," explores the profound differences between implementing these state-of-the-art pre-trained models and traditional machine learning/AI approaches. Find out why the ‘xOps’ paradigm is a fallacy, why the unique technical and operational challenges necessitate sophisticated data and model observability and the imperative for advanced and specialized computational infrastructure to support the intensive demands of these models.

We delve into the strategic considerations surrounding data governance, ethical AI use, and the integration of AI into business processes, underscoring the need for a comprehensive framework that encompasses technological implementation and alignment with organizational goals and values. The discussion extends to the critical role of having a single leader for AI – the Chief AI Officer.

Through a blend of strategic insights and practical examples, this presentation offers a roadmap for businesses looking to navigate the complexities of integrating these models. It provides actionable strategies for building the infrastructure, culture, and processes necessary to harness the transformative potential of these technologies, driving innovation, efficiency, and growth in the digital era. Join us to explore how your organization can transition from traditional AI methodologies to leveraging the power of generative models and observability ensuring a competitive edge in the rapidly evolving corporate landscape. 

Following the explosion of ChatGPT onto the market in late 2022, LexisNexis Legal & Professional quickly saw the massive opportunity for large language models (LLMs) to transform how its customers do legal work. Within weeks, the company pivoted to begin innovating, delivering, and now expanding generative AI solutions for its customers. Across legal and tech industries, the company was recognized as a generative AI leader.

LexisNexis EVP & CTO Jeff Reihl will detail how the company rapidly innovated, delivered, and expanded generative AI solutions. Reihl will share insights into how the company considers its customers’ key challenges and its multi-model approach, prioritizing the best LLM to solve each customer use case. He’ll also share how the company integrates its data assets with LLM technology to improve model output and how the company’s Retrieval Augmented Generation (RAG) platform creates flexibility for the company to adopt new LLM technologies as they change. 

Attendees will learn strategies for deploying generative AI in their organizations to impact products, customers, and internal tools. Reihl will share how attendees should think about deploying generative AI in their organization, how to hire for it, and how to organize teams around it.

In today's data-driven landscape, optimizing AI data processes isn’t a nice-to-have—it’s a strategic imperative. Despite mounting pressure for enterprises to leverage and derive business value from AI, data scientists and engineers are bogged down in data preparation and deployment, reducing their ability to scale AI model development. In this session, discover valuable insights and practical hands-on use cases that show how enterprises can overcome their data-related challenges and help their data scientists and engineers harness the full potential of AI.

As organizations are exploring and expanding on their AI capabilities, Chief Data Officers are now responsible for governing the data for responsible and trustworthy AI. This session will cover 5 key principles to ensure successful adoption and scaling of AI initiatives that align with their company’s business strategy. From data quality to advocating for ethical AI practices, the Chief Data Officer’s mandate has expanded to compliance of new AI regulations. 

Peggy Tsai, Chief Data Officer at BigID and adjunct faculty member at Carnegie Mellon University for the Chief Data Officer executive program, will provide insights into the AI governance strategies and outcomes crucial for cultivating an AI-first organization. Drawing on her extensive experience in data governance and AI, this session will be an invaluable guidance for all participants aiming to adopt industry-leading practices.

We're in the a Cambrian Explosion of data architectures. In the last two years, dozens of vendors have each championed their own version of ‘the modern data architecture solution’, all claiming to be the future of IT in a data-driven enterprise. The sheer volume of architectures is daunting: Streaming data platforms, data lakes, structured/semi-structured/unstructured data, cloud data warehouses supporting external tables and federated query processing, lakehouses, data fabric, and layers of federated query platforms that offer virtual views of data. All claim to support the building of data products.

No surprise that customers are confused as to which option to choose. 

However, key changes have emerged including much broader support for open table formats such as Apache Iceberg, Apache Hudi and Delta Lake in many other vendor data platforms. In addition, we have seen significant new milestones in extending the ISO SQL Standard to support new kinds of analytics in general purpose SQL. Also, AI has also advanced to work across any type of data. 

What does this all mean for data management? What is the impact of this on analytical data platforms and what does it mean for customers? What opportunities does this evolution open up for tools vendors whose data foundation is reliant on other vendor database management systems and data platforms? This session looks at this evolution, helping vendors and IT professionals alike realise the potential of what’s now possible and how they can exploit it for competitive advantage.

Join Anthony Bussanich, Executive Director, Data & Intelligent Automation at JPMorgan Chase as he joins Fiona Sweeney, Partnerships Director at Women in Data® in this essential fireside chat. They will discuss his career to date and explore the importance of a robust data strategy to support businesses as they harness intelligent automation technologies in order to drive improvements in operational efficiency. Anthony will also give us his views of what needs to happen from a people perspective to ensure that organizations optimize resources to harness the opportunity that intelligent automation can bring.

Advanced Analytics, AI, ML, Blockchains, and Platforms are improving human well-being. It is valuable when Advanced Analytics predicts market fluctuations or optimizes customer portfolios. It is convenient when AI and ML improve operational efficiency or recommend the next customer purchase. It is comforting when Blockchains transparently record and preserve incorruptible information. It is commendable when Platforms create multiplier effects for good. It is priceless when these tools work to rescue a life. Could businesses somehow eradicate modern day slavery in their global supply chains with these tools? This task is daunting with thousands of suppliers behind popular products, but businesses are using analytics to find patterns, increase supply chain transparency, reduce reputational risk, and prevent lost revenue, in addition to rescuing lives. In this session, Kendra Taylor of KEYfficiencies, reviews how some businesses use analytics to end human trafficking in global supply chains and what the future might hold.

How do you craft a robust AI-focused data governance strategy that addresses not just technical issues, but also legal, ethical, and organizational angles? Any workable strategy must be able to adapt to an AI landscape that's changing almost any day, and will enforce responsible use of data.

In this session, Kristy Wedel will discuss the unique governance needs of AI, the critical importance of high-quality data, and policies that can evolve alongside learning algorithms through continuous assessment approaches. She will inclde data privacy and compliance—with a focus on GDPR and HIPAA—as well as ethical considerations, anonymization, and privacy. Attendees will leave with a practical understanding of documentation and how to equip stakeholders for success. Kristy will also offer practical guidelines for bias mitigation, fairness, and transparency in AI solutions.

This panel of DataVengers looks at the hot topics and emerging technology trends in data, analytics, and AI. Bringing together an enthusiastic team with a diverse background, they'll share tips on putting passion into your job and building your personal brand. Come with questions—not just about where data is headed, but also about standing out from a digital crowd.