Generative AI and agentic AI tools are only as good as the problem that they are used to solve. In some cases, using generic AI tools can help with non-specific issues. However, Raj Shukla, of enterprise AI platform vendor Symphony AI, says the future of AI technology will focus on vertical applications and open models. In this Targeting AI episode from AI Business, he emphasizes that open source models provide flexibility and the ability to fine-tune for specific use cases. Featuring: Raj Shukla, CTO, Symphony AI In this episode, we cover: Symphony's AI mission of bringing AI technology to legacy industries that may struggle with adoption. A vertical approach combines predictive, generative and agentic AI to address specific challenges. The move in vertical areas from a traditional rule-based approach to a more dynamic, non-deterministic tool. AI applications in these verticals can significantly improve operational efficiencies and strategic decision-making. To learn more about vertical AI applications, 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: Small Language Models Gaining Ground at Enterprises Vertical AI agents explained: The future of enterprise tech AI21 releases open source tiny language model

President Donald Trump signed an executive order last week that looks to override AI state laws in favor of a national policy. Titled "Ensuring a National Policy Framework for Artificial Intelligence," it directs the Department of Justice to establish an AI Litigation Task Force and challenge "cumbersome" state laws. It also asks the Secretary of Commerce to consider withholding federal funds from states found to have restrictive AI laws. In this podcast, Michael Bennett discusses what the EO means for states like New York and California, which already have established laws in place, and how they might respond.  Featuring: Michael Bennett, Associate Vice Chancellor for Data Science and Artificial Intelligence Strategy, University of Illinois Chicago  In this episode, we cover how:  The EO aims to prevent conflicting state laws on AI.  States with existing AI regulations are likely prepared to resist the EO.  The U.S. has a more laissez-faire approach to AI regulation compared with the EU and China.  The order could lead to significant political battles leading up to the midterm elections.  The effectiveness of minimal regulation in winning the AI race is uncertain.  To learn more about AI regulations, check out AI Business, 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:  Navigating Big Tech’s Influence on the AI Regulatory Landscape in 2025  Big Tech Firms Ask for AI Regulation but Quietly Hedge Their Bets  US State Attorneys General Demand Greater AI Safety From Tech Giants

In this episode of the Targeting AI podcast from AI Business, host Esther Shittu interviews Oren Michels, of 2024 startup Barndoor.ai, an AI data and access management vendor, about how to effectively secure enterprise agentic and generative AI systems. The approach is different from traditional cybersecurity paradigms designed to prevent outside intruders from doing harm within an organization's IT system, according to Michels. With agents, security procedures need to focus on the agents themselves to ensure they are performing as their human counterparts intend. The podcast was recorded at the AI Summit conference in New York City on Dec. 10. Featuring Oren Michels, founder and CEO of Barndoor.ai In this episode, we cover: How enterprises can secure agentic and generative AI systems. What mistakes businesses make that make them vulnerable to security threats to AI systems. Some of the biggest security threats to large-scale business users of generative and agentic AI technology. How to use the Model Context Protocol standard with cybersecurity measures to protect and govern AI agents. To learn more about security for generative and agentic AI systems, check out AI Business, 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 Agent Security: Whose Responsibility Is It? Governance Is Top Priority for Companies Using Agentic AI: Survey What Agentic AI Means for Cybersecurity  

In this special news analysis edition of the Targeting AI podcast from AI Business, Esther Shittu and Shaun Sutter interview R "Ray" Wang of Constellation Research, with Wang live from the AWS re:Invent 2025 conference in Las Vegas. Wang says AWS's new frontier AI agents represent a major step in the development of agentic AI, and other AI vendors are likely to follow AWS's lead. He also notes that AWS's new Trainium AI chips position AWS to be less reliant on AI chips from Nvidia, though the AI hardware giant continues to be a major chip provider to AWS. Wang also notes that AWS's new "AI factories" are crucial for the growing sovereign AI movement, as countries and regions worldwide are establishing their own AI industries and are less dependent on the U.S. and China. Featuring R "Ray" Wang, founder and analyst at Constellation Research In this episode, we cover how: The demand for AI chips is growing rapidly. AWS's Trainium AI chips offer cost-effective options for developers. Pre-built models are essential for speeding up development. AWS is focusing on providing choices for developers. The integration of AI into existing systems is crucial for businesses. AWS is catching up in AI capabilities compared to competitors. The importance of governance and security in AI deployment. Startups are increasingly building on AWS infrastructure. The future of AI will involve multi-agent systems across platforms. To learn more about AWS, generative AI, agentic AI and sovereign 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: AWS Launches Frontier Agents AWS Opens First Innovation Hub for APAC AWS Developing High-Performance Autonomous AI Agents    

It’s no secret that generative AI  has led to exponential growth in AI technology. However, one area continues to seem to be lacking. Years ago, Asha Saxena, of the World Leaders in Data and AI (WLDA) organization, attempted to shift the landscape by creating an organization that emphasizes the importance of diversity in AI and the ethical challenges organizations face when implementing AI systems. In this Targeting AI podcast from AI Business, she emphasizes the need for women to have a bigger role in the AI community and the role of men as allies in this mission. Featuring: Asha Saxena, CEO of World Leaders in Data and AI In this episode, we cover how: Diversity is essential for innovation and excellence. Men must be included in the conversation about women in leadership. AI can help detect and rectify bias in data. Organizations face challenges in obtaining diverse data sets. Lifelong learning is crucial in the rapidly evolving AI landscape. Personalization in AI applications is a significant trend. To learn more about generative AI and diversity, 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.

In this episode of the Targeting AI podcast from AI Business, Esther Shittu and Shaun Sutner interview Justin Liu of B2B platform Alibaba.com., discussing his extensive experience in e-commerce and the evolution of B2B sourcing in the age of AI. Liu shares insights on the complexities of B2B transactions, the innovative AI tools being implemented to enhance buyer and seller experiences, and the rapid adoption of these technologies by small businesses. He also highlights the importance of supplier verification and security in B2B commerce, and how AI is transforming traditional roles in the industry. The conversation concludes with a look at Alibaba's global expansion efforts and the future of AI in the e-commerce sector. Featuring: Just Liu, general manager, Alibaba.com U.S In this episode, we cover how: B2B sourcing is more complex than B2C transactions. AI can simplify the tedious processes in B2B sourcing. Alibaba.com focuses on helping buyers and sellers with AI. AI adoption is growing rapidly among professional buyers. AI enhances supplier verification and transaction security. AI is transforming traditional sales roles in B2B. AI helps lower the entry barrier for small businesses. To learn more about generative AI and agentic 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: Alibaba, Nvidia Unite for AI Development and Cloud Growth Alibaba Cloud targets full-stack AI dominance Alibaba unveils Accio Agent for global trade  

Some think AI is just a trend and that we are on the verge of a bubble. That is not the case for Arun Subramaniyan, of Articul8. This enterprise AI vendor offers customers a platform for developing and deploying customized generative AI applications. In this Targeting AI podcast, Subramaniyan discusses some of the misconceptions enterprises have about implementing AI technology and the significance of measuring ROI. Featuring: Arun Subramaniyan, CEO and founder of Articul8 In this episode, we cover how: AI is a necessity for solving complex problems, not just a trend. Enterprises struggle with data synthesis and knowledge discovery. Customer data remains secure within its environment. Open source is crucial for the evolution of AI technology Many enterprises misunderstand the complexities of AI implementation. 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: How business leaders are measuring generative AI's ROI AI regulation and the open source community Intel-Backed Generative AI Company Launches Aerospace Platform at Paris Air Show  

In this special news analysis edition of the Targeting AI podcast from AI Business, Esther Shittu and Shaun Sutner discuss Nvidia's historic achievement on Oct. 29 of becoming the first company to reach a $5 trillion market valuation with R "Ray" Wang of Constellation Research. The conversation explores the implications of this milestone for enterprise AI technology, the current AI boom, and the potential for a bubble in the market. They also touch on Nvidia's market position and the concerns surrounding monopoly in the context of the ongoing U.S.-China AI war. Featuring R "Ray" Wang, founder and analyst at Constellation Research In this episode, we cover how: Nvidia's valuation reflects the growing importance of AI technology. The AI market is expected to continue expanding significantly. There is a potential for an AI bubble if job creation does not keep pace with AI advancements. Entrepreneurship in AI is thriving, with small companies achieving significant revenue. The emergence of AI exponentials is disrupting traditional business models. Nvidia's dominance is partly due to geopolitical factors, particularly the U.S.-China AI war. Concerns about monopolistic practices exist but are complicated by the competitive landscape. The future of AI jobs remains uncertain as automation replaces traditional roles. To learn more about Nvidia, generative AI and agentic 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: Nvidia unveils new AI hardware-software approach for industrial AI Nvidia's deal with rival AI chipmaker Intel The AI chip giant becomes first company to cross $5 trillion threshold    

In this breaking news analysis episode of the Targeting AI podcast from Informa TechTarget's AI Business, Esther Shittu and Shaun Sutner discuss the recent AWS outage that disrupted numerous websites and services, including AI applications such as widely used generative AI models from OpenAI and Anthropic. Tech analyst David Nicholson provides insights into the causes of the outage, emphasizing the importance of multi-site redundancy for enterprises relying on cloud services. The discussion also touches on the implications for AI applications and the need for businesses to consider redundancy options to prevent future disruptions. Featuring: David Nicholson, analyst, The Futurum Group In this episode, we cover how: AWS experienced a major outage due to DNS problems. The outage affected several large language models. Multi-site redundancy is a way to prevent future disruptions. Enterprises need to invest in redundancy for cloud services. AI applications are not the cause of outages but are affected by them. Cloud services have become more resilient over time. Companies must be proactive in ensuring service continuity. The cost of redundancy can be high, but it is necessary. Smaller cloud providers may not offer the same level of resilience. To learn more about generative AI, agentic AI and AI cloud services, check out AI Business from Informa TechTarget. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: Prepare for a cloud outage with these preventive steps Beware of over-reliance on U.S.-based cloud giants Generative AI models from Anthropic and OpenAI

In this episode of the Targeting AI podcast from AI Business, Shaun Sutner and Esther Shittu interview Sean Falconer of streaming data platform vendor Confluent. They discuss Confluent's AI strategy, the importance of real-time data management, and the integration of generative AI and multi-agent systems into business processes. Falconer emphasizes the need for high-quality data and the advantages of open source technologies like Apache Kafka and Flink. The conversation also touches on the challenges of implementing AI systems and the future direction of AI technology at Confluent. Featuring: Sean Falconer, senior director of AI Strategy at Confluent. In today's episode, we cover how: Confluent focuses on real-time data processing and management. Generative AI requires fresh, relevant data to be effective. Data quality should be enforced at the source, not downstream. Multi-agent systems can operate continuously and autonomously. Confluent partners with major AI model providers for integration. Reliability and testing are critical challenges in AI development. The future of AI at Confluent includes building support for ambient agent experiences. To learn more about AI, open source and agentic systems AI, check out AI Business. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech.  References:  Confluent, streaming data and agentic AI Confluent and Databricks work together to simplify AI development What is data streaming?    

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