Targeting AI

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.