Targeting AI

In this episode of the Targeting AI podcast from AI Business, hosts Esther Shittu and Shaun Sutner discuss the role of AI in healthcare with Madhav Thattai of Salesforce and John Oberg of Precina Health. They explore the concept of being AI-first, the integration of AI in patient care, and the impact of agentic systems on healthcare outcomes. The conversation highlights how AI can enhance clinical practices, improve patient interactions, and streamline business processes, ultimately leading to better health outcomes and operational efficiency. In this episode, the conversation revolves around the transformative role of AI in healthcare, particularly focusing on patient experience, the integration of Salesforce Health Cloud, and the balance between AI automation and human clinical judgment. The speakers discuss the supportive role of AI in clinical decisions, innovative applications in mental health, and the importance of trust and ROI in AI deployments. They emphasize the need for clear KPIs and the potential for AI to unlock efficiencies in healthcare delivery. Featuring: Madhav Thattai, SVP & COO of Agentforce product management at Salesforce, and John Oberg, founder and CEO of Precina Health In this episode, we cover how: AI is used extensively in healthcare to enhance patient-provider interactions. Being AI-first can lead to improved clinical and financial outcomes. Salesforce's agentic technology is being used for customer support and marketing. AI can automate routine tasks, allowing healthcare providers to focus on patient care. The integration of AI in diabetes management has shown significant success. AI can personalize patient care through meal planning and recipe suggestions. The future of healthcare involves a collaborative approach between technology and human providers. AI is not the focus; it's a catalyst for patient experience. AI supports clinicians without replacing their judgment. To learn more about agentic AI and generative AI, check out AI Business.  To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech.  References:  Salesforce Agentforce   Applications for AI in healthcare AI and type 2 diabetes risk   

In this breaking news analysis episode of the Targeting AI podcast from Informa TechTarget's AI Business, hosts Esther Shittu and Shaun Sutner discuss the latest innovations in agentic AI technology unveiled at Salesforce's Dreamforce conference in October with guest Madhav Thattai of CRM and CX giant Salesforce. The conversation covers the new Agentforce 360 platform, including hybrid reasoning, enhanced control and context for agents, and the importance of the user experience and data privacy. Thattai emphasizes the need for a balance between creativity and control in enterprise AI applications. Featuring: Madhav Thattai, SVP and COO of Agentforce product management at Salesforce In today's episode, we cover how: Hybrid reasoning combines LLMs with structured processes. Control and context are essential for agent functionality. UX features are being enhanced for agents. Data privacy is important to Salesforce. AI agents must respect user permissions and access. Salesforce aims to democratize agent development. Context indexing improves agent accuracy. To learn more about agentic AI, generative AI and Salesforce, check out AI Business. To watch videos of our podcasts, subscribe to our YouTube channel, @EyeonTech.

In this podcast, Mark Geene of robotic process automation (RPA) vendor UiPath discusses the evolution of RPA and the emergence of agentic AI. He explains how these technologies are transforming business processes, the importance of governance and compliance, and the future of work with digital workers. Geene also highlights the role of data in enabling effective AI agents and shares insights on the competitive landscape of RPA vendors. The discussion concludes with predictions about the future of AI in business. In the episode, we cover how: RPA automates repetitive tasks and is limited to deterministic workflows Agentic AI combines deterministic and ad hoc processes for greater flexibility Governance and compliance are critical for successful automation Orchestration allows for effective collaboration between agents, robots, and humans Data is essential for providing context to AI agents Narrowly scoped agents can operate with more autonomy The future of work will see agents supervising business processes Featuring: Mark Greene, senior vice president and general manager of AI products and platform at UiPath To learn more about agentic AI, RPA and generative AI, check out AI Business from Informa TechTarget. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: UiPath AI agents blend with RPA amid industry hype, doubts Governance Is Top Priority for Companies Using Agentic AI: Survey Startup aims to upend old-school RPA with large action model | TechTarget          

In this special breaking news analysis edition of the Targeting AI podcast from AI Business, hosts Shaun Sutner and Esther Shittu dive into the latest developments in the AI industry with Torsten Volk, an analyst with Omdia. Both AI Business and Omdia are owned by Informa TechTarget. This episode covers AI cloud computing vendor CoreWeave's groundbreaking $14 billion AI compute deal with Meta Platforms, exploring its implications for enterprise AI and the future of data center services. Join us as we unravel the complexities of AI infrastructure, the race for GPU power, and the strategic moves shaping the tech landscape. Don't miss this discussion on the forces driving innovation and competition in AI.  Takeaways: CoreWeave's partnership with Meta underscores the growing need for specialized AI infrastructure. Efficient GPU utilization is crucial for AI companies to maintain competitiveness. The AI sector is rapidly evolving, with significant investments in infrastructure and talent. Meta's strategy involves collaborating with various vendors to enhance its AI capabilities. The deal may signal the emergence of a new sector within the AI industry, focusing on data center services.  

As one of the biggest financial institutions in the U.S., Capital One isn’t running away from generative AI and agentic AI. Instead, the $490 billion company is using the technology to enhance both internal operations and customer experience. In this Targeting AI episode, the chief scientist and executive vice president at Capital One discusses some of the challenges and opportunities the financial giant is facing in customizing LLMs, and how the company continues to prioritize risk management and safety. Featuring: Prem Natarajan, executive vice president, head of enterprise AI and chief scientist, Capital One In today's episode, we cover: Capital One's enterprise AI strategy is focused on creating customizable platforms using open source or open weight models Capital One uses its proprietary data to customize AI models The company uses GenAI and agentic AI for internal operations, such as with agent assist tools for customer service and customer-facing experiences like chat concierge The enterprise has a focus on long-term transformation and not short-term ROI To learn more about AI, open source and agentic AI, check out AI Business and SearchEnterpriseAI from Informa TechTarget. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: Capital One AI partnerships aim to build trust and grow talent Compare proprietary vs. open source for enterprise AI The importance and limitations of open source AI models

As a legacy organization, IBM has long been a champion for open source, especially in the age of GenAI. In this episode of Targeting AI from Informa TechTarget, Bruno Aziza, vice president of data, AI and analytics at IBM, discusses how the vendor has had to rebrand and shift in the age of GenAI and agentic AI. Aziza shares insights on talent challenges, IBM's data strategy with Watson X, and the significance of customer-centric AI solutions.  Featuring: Bruno Aziza, vice president of data, AI and analytics at IBM  In today’s episode, we cover how:  The shift to agentic AI is crucial for modern enterprises.  Open source plays a vital role in AI development.  IBM focuses on enterprise AI, rather than consumer-facing solutions.  Talent scarcity is a significant challenge in AI innovation.  99% of enterprise data remains untouched by AI.  To learn more about AI, open source, agentic AI, check out SearchEnterpriseAI.  To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech.  References:  IBM customers assess the performance of AI agents  IBM to buy open source data platform and AI vendor DataStax  IBM targets agentic AI orchestration 

When it comes to diversity, AI systems often fail. In this episode of the Targeting AI podcast, Christina Mancini, CEO of Black Girls Code, discusses the importance of inclusion in tech, the strategies Black Girls Code employs to empower girls of color, and the need for ethical considerations in AI education. Christina emphasizes the role of communities of color as creators in AI and the necessity for equitable development in technology. She also outlines the future goals of Black Girls Code and how organizations can support their mission. Featuring: Christina Mancini, CEO of Black Girls Code In today’s episode, we cover: Communities of color are often super users of technology but need to be creators too. AI technologies must be built by diverse teams to avoid bias. Organizations should pause to consider the impact of their products on all communities. Collaboration with tech partners is essential for achieving their mission. To learn more about AI, bias and diversity check out SearchEnterpriseAI. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: Generative AI will force diversity in AI systems Federal report focuses on AI diversity and ethics Diverse data, ethical use key to responsible AI engineering

In a market dominated by Nvidia H100 GPUs, Cerebras Systems seeks to develop the world's largest AI chip, the Wafer Scale Engine. In this episode of Targeting AI from Informa TechTarget, James Wang, the vendor's director of product marketing, discusses the importance of the inference market for AI technology and how the company's strategic partnerships are essential for growth. He elaborates on the evolving landscape of AI, including the significance of agentic AI and touches on Cerebras' future direction as a cloud and API company. Featuring: James Wang, director of product marketing at Cerebras Systems In this episode, we cover how: Cerebras approaches competing against Nvidia. Cerebras approaches differentiating itself from other AI inference vendors The company is evolving into a cloud and API product company to meet market demands. Agentic AI represents a new frontier in AI applications, enabling complex tasks through multiple requests. To learn more about AI and Cerebras Systems and other hardware news, check out SearchEnterpriseAI.  To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech.  References:  Cerebras launches Alibaba model, forms key AI partnerships Cerebras' inference AI tool challenges Nvidia, but faces hurdles Microsoft, AWS and Cerebras launch DeepSeek-R1 model  

In this two-year anniversary episode of Targeting AI from Informa TechTarget, Michael Bennett discusses the rapid evolution of generative AI technology, and its implications for society, legal frameworks and creative industries. He highlights the public's growing awareness and understanding of AI, the legal challenges surrounding copyright and fair use, and the moral questions that arise from the use of AI in creative fields.  Featuring: Michael Bennett, associate vice chancellor for data science and artificial intelligence strategy at University of Illinois Chicago  In this episode, we cover:  The public's awareness of AI technology has significantly increased since the release of ChatGPT.  Legal challenges surrounding generative AI focus on copyright and fair use, creating uncertainty for the industry.  The disparity in AI infrastructure may lead to unequal benefits and negative consequences globally.  The future of AI, including AGI (artificial general intelligence), is uncertain and requires careful consideration.  To learn more about AI and the other regulation and governance news, check out SearchEnterpriseAI.  To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech.  References:  AI regulation: What businesses need to know in 2025  XAI releases Grok 4 amid furor over antisemitic comments  Anthropic’s early lawsuit win pushes courts forward on fair use 

In this special news edition of Targeting AI from Informa TechTarget, government reporter Makenzie Holland discusses President Trump's AI action plan and executive orders aimed at promoting AI development and ensuring U.S. dominance in the AI race. Featuring: Makenzie Holland, Informa TechTarget senior news writer In today’s episode, senior new director Shaun Sutner and AI news writer Esther Shittu cover these topics: President Trump’s new executive order and its intent How the executive orders differ from the president’s previous orders and President Biden’s 2023 executive order Woke AI and political bias concerns To learn more about AI and the other regulation and governance news, check out SearchEnterprise AI and SearchCIO To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: White House AI plan places scrutiny on state AI laws Senate’s ‘One Big, Beautiful Bill’ affects AI, U.S. energy S. policy moves reflect big tech issues with state AI laws