Targeting AI

Informa TechTarget

Hosts Shaun Sutner, TechTarget News senior news director, and AI news writer Esther Ajao interview AI experts from the tech vendor, analyst and consultant community, academia and the arts as well as AI technology users from enterprises and advocates for data privacy and responsible use of AI. Topics are related to news events in the AI world but the episodes are intended to have a longer, more ”evergreen” run and they are in-depth and somewhat long form, aiming for 45 minutes to an hour in duration. The podcast will occasionally host guests from inside TechTarget and its Enterprise Strategy Group and Xtelligent divisions as well and also include some news-oriented episodes featuring Sutner and Ajao reviewing the news.

  1. 2D AGO

    Understanding Human Impact and Safety in AI

    In a special episode of the Targeting AI podcast from AI Business, host Esther Shittu interviews Christopher Campbell of Lenovo about the challenges and considerations surrounding AI governance, emphasizing the importance of human impact, safety, and accountability. They explore the evolving perspectives on bias and hallucinations in AI, the role of hardware in AI development, and the implications of personal AI agents. The discussion highlights the importance of selecting the right AI partners, maintaining governance in hybrid AI environments, and addressing the complexities of shadow AI and AI governance sovereignty. The episode concludes with advice for organizations on effectively adopting AI governance practices. The podcast was recorded on-site at the Gartner Data & Analytics Summit in Orlando. Featuring: Christopher Campbell, director of AI governance and global products and services security leader at Lenovo In this episode, we cover how: The human impact and safety of AI are paramount. Trust in AI systems is essential for their success. Bias and hallucination perspectives have matured over time. Accountability in AI governance lies with leadership. Choosing AI partners with aligned philosophies is crucial. Governance standards apply equally to local and cloud models. Shadow AI presents a complex challenge for organizations. Sovereignty in AI gives regions more control over their data. Understanding technology is key to effective AI adoption. There is no one-size-fits-all approach to AI governance. To learn more about AI governance, safety and sovereignty, check out AI Business from Informa TechTarget, and please subscribe to our newsletter to keep up to date on the most important AI news. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: AI data governance guidance that gets you to the finish line The AI bias playbook: Mitigation strategies for CIOs Major sovereign AI funding deals kick off India AI Impact summit

    28 min
  2. 3D AGO

    How Capital One is building an AI-ready data ecosystem with creative talent

    In this interview on the Targeting AI podcast from AI Business, Amy Lenander of financial services giant Capital One discusses the critical role of talent in building AI-ready data ecosystems. She explores how organizations can cultivate the right skills, develop foundational data platforms and use AI to drive business value. The interview was recorded on-site at the Gartner Data & Analytics Summit 2026 in Orlando. Featuring Amy Lenander, chief data officer, Capital One In this episode, we cover how: Talent agility outweighs technical experience in AI success. Organizations that develop learning agility and curiosity foster talent capable of navigating rapidly evolving AI landscapes. Instead of hiring for a specific toolset, focus on candidates who demonstrate rapid learning, problem-solving, and collaboration—traits that enable mastery of new AI methods as they emerge. Building a unified data ecosystem creates a competitive moat. A well-designed data ecosystem, prioritized over immediate AI application, provides a robust foundation that supports all future data and AI initiatives. Investing in governance, data trustworthiness, and accessibility shields organizations from fragmentation, enabling scalable innovation regardless of future technological shifts. AI adoption is a cultural shift, not just a technology implementation. Domain-specific data products enhance AI interpretability and trust. Specialized data teams responsible for understanding business nuances ensure AI systems interpret data context correctly for strategic use. To learn more about generative and agentic AI and AI-ready data ecosystems, check out AI Business from Informa TechTarget, and please subscribe to our newsletter to keep up to date on the most important AI news. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: The Shift Toward AI Data Quality as a Core Product Data Quality in AI: 9 Common Issues and Best Practices Data and AI Governance Must Team Up for AI to Succeed

    20 min
  3. MAR 3

    Navigating the generative AI landscape with two MIT profs

    In this episode of the Targeting AI podcast from AI Business, hosts Shaun Sutner and Esther Shittu engage with Abel Sanchez and John Williams from MIT to discuss the evolving landscape of generative AI. The conversation covers the motivation behind their initiative, Gen AI Global, the dynamics of their professional relationship, and the societal implications of AI technologies. They explore concepts such as "vibe living," the energy demands of AI, and contrasting perspectives on AI's future, including the debate between optimists and skeptics. The episode concludes with a discussion on the sustainability of the AI boom and the importance of human involvement in an increasingly automated world.  Featuring: Abel Sanchez, a research scientist and executive director of MIT's Geospatial Data Center; and John Williams, professor of civil and environmental engineering at MIT and director of the Geospatial Data Center and Intelligent Engineering Systems laboratory at MIT.  In this episode, we cover how:  Learning is social; community enhances educational outcomes.  Generative AI is rapidly changing industries and education.  AI's impact on society is both exciting and concerning.  The relationship between Abel and John is built on trust and differing perspectives.  Generative AI can empower non-experts to achieve expert-level results.  Energy consumption for AI is a growing concern.  The future of AI models may involve new architectures beyond transformers.  Human intuition and emotion remain valuable in AI applications.  The AI boom is characterized by rapid adoption and innovation.  Organizations must adapt to integrate AI effectively.  To learn more about generative AI, check out AI Business from Informa TechTarget, and please subscribe to our newsletter to keep up to date on the most important AI news.  To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech.  References:  Gen AI Global  How much energy do data centers consume?   Debate Rages Over AI Bubble vs. Boom

    37 min
  4. FEB 17

    Coinbase, crypto, blockchain and the outlook for digital payments

    AI is changing digital payments, and Coinbase is trying to lead that change. Last year, the cryptocurrency exchange provider partnered with Cloudflare, AWS, Anthropic and others to create the x402 protocol, a standard that enables AI agents to make transactions online. In this conversation, Coinbase’s Dan Kim talks with Targeting AI hosts Esther Shittu and Shaun Sutner AI about how generative AI is critical in creating a new class of AI agents that can autonomously engage in trading and transactions.  Featuring: Dan Kim, vice president, head of digital asset listings & services at Coinbase In this episode, we cover: Coinbase's mission is economic freedom through cryptocurrency and blockchain. AI is transforming software to be more intelligent and adaptive. The X402 Foundation aims to standardize how payments are processed over the internet. AI agents are becoming a new class of customers in the trading space. Stablecoins are crucial for secure transactions between AI agents. To learn more about generative and agentic AI and RPA, check out AI Business from Informa TechTarget, and please subscribe to our newsletter to keep up to date on the most important AI news. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: X402 Aims to Enable Agentic Payments with Digital Dollars Blockchain for businesses: The ultimate enterprise guide What is a Stablecoin?

    26 min
  5. FEB 3

    The Future of AI in Process Intelligence

    In this episode of the Targeting AI podcast from AI Business, Manuel Haug, of Germany-based process mining vendor Celonis, discusses the intricacies of process mining and its integration with AI technologies. He explains how Celonis differentiates itself in the market, the evolution of its strategy in light of generative AI, and the practical applications of AI agents in various industries. Haug emphasizes the importance of operationalizing process mining findings and preparing for the future of work as the workforce ages. He also touches on the complementary nature of AI and traditional automation methods, such as RPA, and the need to capture organizational knowledge before it is lost. Featuring: Manuel Haug, field CTO of Celonis In this episode, we cover how: Process mining connects to various IT systems to analyze business processes. AI can improve and automate manual processes in companies. AI agents can assist human teams in decision-making. Operationalizing findings from process mining is crucial for improvement. The aging workforce necessitates capturing knowledge effectively. RPA and AI can coexist and complement each other in automation. Understanding processes is foundational for effective AI implementation. AI technology is becoming more reliable and powerful. The future of work will involve a blend of AI and human oversight. To learn more about generative and agentic AI and RPA, check out AI Business from Informa TechTarget, and please subscribe to our newsletter to keep up to date on the most important AI news. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: 5 Benefits of Using Process Mining Process Mining Software Comparison: What CIOs Should Look at Top Enterprise Process Mining Challenges, Ways to Solve Them

    26 min
  6. JAN 6

    Google AI exec says data is the next phase of generative AI

    At the start of the mass popularity phase of generative AI, large language models were the star of the show. Vendors released bigger and newer models. However, the conversation has recently shifted from considering big or small models to a deep focus on data. In this episode of the Targeting AI podcast from AI Business, Yasmeen Ahmad, of Google Cloud, discusses the transformative effect of generative AI on the data landscape. She emphasizes the importance of treating data as a product, the shift toward multimodal data, and the role of AI agents in enhancing data management and decision-making processes. Featuring: Yasmeen Ahmad, managing director of product management for data and AI Cloud, Google Cloud In this episode, we cover how: The era of multimodal data is upon us, integrating various data types. Agentic AI enhances the understanding of unstructured data. Databases must evolve into cognitive reasoning engines for AI. Gemini Enterprise provides a unified platform for AI and data. Data security and responsibility are critical in AI deployment. To learn more about the role data plays in generative AI, check out AI Business from Informa TechTarget, and please subscribe to our newsletter to keep up to date on the most important AI news. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: Generative AI is the Future of Data Management Without Data There Is No AI Google Invests $40B in AI Data Centers in Texas

    39 min

Ratings & Reviews

5
out of 5
3 Ratings

About

Hosts Shaun Sutner, TechTarget News senior news director, and AI news writer Esther Ajao interview AI experts from the tech vendor, analyst and consultant community, academia and the arts as well as AI technology users from enterprises and advocates for data privacy and responsible use of AI. Topics are related to news events in the AI world but the episodes are intended to have a longer, more ”evergreen” run and they are in-depth and somewhat long form, aiming for 45 minutes to an hour in duration. The podcast will occasionally host guests from inside TechTarget and its Enterprise Strategy Group and Xtelligent divisions as well and also include some news-oriented episodes featuring Sutner and Ajao reviewing the news.

You Might Also Like