AI Realized Podcast
Tim Crawford
Tim Crawford is a globally recognized CIO Strategic Advisor and the Founder of AVOA, where he helps enterprise technology leaders navigate digital transformation and emerging technologies like AI. With decades of experience advising Fortune 1000 companies, Tim is known for his pragmatic insights, deep IT expertise, and forward-thinking perspective. He also hosts the CIO in the Know and CXO in the Know podcasts, where he explores the evolving role of technology in driving business innovation.
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Episode Summary
In this episode of AI Realized, Tim Crawford, founder and CIO of Avoa, joins the show to unpack the realities of enterprise AI deployment. Tim dives into the rise of AI agent sprawl, clears up common misconceptions between chatbots and AI agents, and underscores the critical role of governance frameworks in managing AI at scale. He explores the cultural, technical, and strategic shifts required for organizations to adopt agentic AI effectively—and shares why the next 1–3 years will be pivotal in shaping how humans and AI agents collaborate. From orchestration layers to digital agents, this conversation offers a forward-looking roadmap for enterprise leaders navigating the agentic era.
Matthew Swanson
Matthew Swanson is the Co-Founder and CEO of Motion Enterprise, where he leads the development of agentic AI solutions for enterprise knowledge and contract intelligence. With a background in building large-scale platforms and deep expertise in AI, NLP, and agentic architectures, Matthew is focused on transforming how organizations unlock and apply knowledge. He is a passionate innovator at the intersection of machine learning and enterprise operations.
Episode Summary
In this episode of AI Realized, we dive into the future of AI-powered enterprise operations with Matthew Swanson, CEO of Motion Enterprises. Swanson shares how his company is redefining customer lifecycle management by deploying AI agents as conversational interfaces, replacing the need for traditional, click-heavy software. These agents sit on top of platforms like Salesforce, automating workflows and delivering real business outcomes—measured and monetized
Kris Bondi
Kris Bondi is the CEO and Co-Founder of Mimoto, a cutting-edge cybersecurity company focused on protecting identity and data in AI-driven environments. With over two decades of experience in technology leadership, Kris has led go-to-market and product strategy at innovative companies like Mulesoft, LogDNA, and Cloudmark. She is a recognized voice in security, privacy, and AI, and is passionate about helping organizations stay ahead of evolving digital threats through smarter, adaptive protection.
Episode Summary
In this episode of AI Realized, hosts Christina Ellwood and David Yakovich interview Kris Bondi, CEO of Mimoto. The discussion revolves around the challenges and opportunities in AI-driven security. Kris explains how AI can exacerbate security issues by enabling bad actors to innovate and automate attacks. He also highlights the benefits of AI in security, such as anomaly detection and advanced pattern matching. They discuss the use of AI for internal security measures, including red and blue team simulations, and the identification of deep fakes. Kris shares insights into Mi Moto's unique approach to security, which uses AI and machine learning to create a 'digital double' for more precise identification and anomaly detection. The episode concludes with advice for executives on innovating their security posture and ensuring adaptive, real-time security measures.
Domenic Ravita
Domenic Ravita is a go-to-market leader in Data and AI infrastructure, with a proven track record scaling high-growth technology companies—including two unicorns. As an advisor, investor, and strategist, Domenic brings deep expertise in bridging cutting-edge innovation with enterprise needs. He’s passionate about enabling organizations to unlock the full potential of their data through scalable AI platforms and next-gen infrastructure.
Episode Summary
In this episode of AI Realized, Domenic Ravita, VP of Marketing at Plotly, discusses the transformative impact of AI on data science workflows and operational efficiency. Domenic highlights exciting developments in generative AI, the convergence of traditional and generative AI teams, and the use of open-source tools like Python and Plotly's Dash for creating flexible, custom data applications. He shares real-world examples from industries like financial services and pharmaceuticals, illustrating how companies are driving ROI through AI-enhanced data products and clinical trial operations. The conversation also explores the future of AI, the commoditization of large language models, and the growing importance of local AI for maintaining data privacy and security.
Randy Friedman
Randy Friedman is a seasoned executive and growth strategist with deep expertise in AI, machine learning, and enterprise transformation. Having served as CRO, CCO, COO, and CEO across multiple technology ventures, Randy brings a unique blend of commercial leadership and operational insight. He’s known for driving innovation at the intersection of AI and business, helping organizations unlock value through intelligent systems and data-driven strategy.
Episode Summary
In this episode of AI Realized, host Christina Ellwood talks with Randy Friedman, Chief Commercial Officer at Cognizer AI, about how AI is now being used to build AI. They explore the evolution from traditional machine learning models to agentic AI workflows, where AI agents autonomously create specialized models. The discussion covers AI’s impact on contract intelligence, cross-organizational collaboration, and the need for decentralized data governance. Learn how enterprises can leverage AI to optimize operations, enhance decision-making, and unlock new efficiencies in the data-driven economy.
Maher Hanafi
Maher Hanafi is Senior Vice President of Engineering at Betterworks, where he leads product development and engineering strategy at scale. With a strong background in building enterprise SaaS platforms, Maher specializes in creating secure, scalable, and AI-driven solutions. He’s passionate about fostering high-performing teams, driving innovation, and delivering technology that empowers modern workplaces.
Episode Summary
In this episode, Maher Hanafi, VP of Engineering at BetterWorks, discusses the critical role of trust in AI adoption. He highlights the importance of gaining internal stakeholders' and customers' trust by understanding AI concepts and risks, creating transparent AI privacy policies, and implementing responsible AI frameworks. Maher addresses challenges specific to enterprise and HR technology, detailing the necessity of adapting to rapid AI advancements while maintaining compliance and governance. He also explores the future potential of agent-based AI systems and offers advice for executives on effectively deploying AI technologies.
Steve Jones
Steve Jones is Executive Vice President at Capgemini, where he leads global initiatives in data-driven transformation and Generative AI strategy. With over two decades of experience advising Fortune 500 companies, Steve is a trusted authority on aligning emerging technologies with business outcomes. He’s a frequent speaker and thought leader on enterprise innovation, AI adoption, and the future of digital strategy.
Episode Summary
Steve Jones, Executive Vice President of Data Driven Business and Generative AI at Capgemini, discusses the challenges and opportunities of deploying AI in enterprises. He explains that moving from proof-of-concept to production is a significant hurdle, with the focus needed on operational maturity. Jones warns that while agentic systems can enhance processes, they require stringent governance to avoid risks. He highlights that AI should be perceived as a tool within the business, not just an IT backend, and predicts a substantial increase in production-level AI deployments by 2025. Additionally, Jones talks about potential use cases for agents, emphasizing the importance of decomposing problems to manage risks effectively.
Allan McLennan
Allan McLennan is a globally recognized leader in digital transformation, AI strategy, and IP-driven innovation. As a founder, president, and board member, he has guided next-stage growth for companies across media, streaming, and data intelligence. A Wall Street Journal best-selling author and international speaker, Allan brings deep expertise in shaping the future of connected experiences through advanced technologies and global business strategy.
Episode Summary
In this episode of AI Realized, Allan McLennan, founder and chief executive of PADEM Media Group, discusses the impact of generative AI on the media and entertainment industry. He highlights efficiency improvements, potential economic impacts, and challenges such as layoffs and legal implications. Mclennan touches on the integration of AI in metadata management, which is critical for content authenticity and security. He also describes the collaborative effort at the IBC accelerator to identify and manage fake content using AI. Moreover, Mclennan forecasts advancements in personalized advertising through AI, allowing for more engaging and less intrusive ads. He stresses the importance of staying informed about AI developments and recommends resources like Paul Beyer's GAI Insights and Substack for those in the media and entertainment sector.
Kenn So
Kenn So is a seasoned leader in corporate development and strategy, with deep expertise in scaling innovation across AI, SaaS, and enterprise technology. With a background in investment banking and venture capital, Kenn has worked with high-growth startups and global enterprises to shape strategic partnerships, drive M&A, and unlock long-term value. He brings a sharp lens to the evolving AI landscape and how businesses can turn disruption into opportunity.
Episode Summary
Kenn So, Director of Corporate Development and Strategy at Smartsheet, discusses AI adoption trends and strategies. He highlights the importance of unique acquisition structures like licensing and acquisitions (L&A) to acquire talent and technology. Kenn talks about using AI tools to enhance productivity, especially among software engineers, and the need for companies to explore multiple areas for AI application. He advises enterprise executives to establish AI committees with diverse representation to champion AI adoption and manage risks. Executives should actively use AI tools to understand their benefits and model their use for others. Kenn also recommends learning from workshops, AI-focused law firms, and other executives to stay updated on the risks and benefits of AI deployment.
Chris Butler
Chris Butler is a self-described “Chaotic Good” Product Manager and a leading voice in human-centered AI and product strategy. With experience at GitHub, Chris brings a provocative and systems-thinking approach to building ethical, resilient, and user-focused technologies. He’s known for challenging conventional frameworks and driving conversations at the intersection of AI, design, and complexity.
Episode Summary
Chris Butler, staff product operations manager at GitHub, discusses his role in enhancing product management effectiveness and driving innovation. He distinguishes between product managers, who focus on delivering innovation, and product operations managers, who streamline processes and ensure effective team dynamics. Chris introduces his unique approach as a 'chaotic good product manager,' advocating for challenging established norms to foster innovation and resilience. He highlights the importance of recognizing different stages of tech adoption—explore, expand, and extract—and tailoring strategies accordingly. Furthermore, Chris emphasizes the significance of leveraging AI as a thought partner in decision-making and process optimization. He envisions a future where tools like language models assist in cross-functional collaboration within development teams, promoting better understanding and efficiency. He urges organizations to create safe environments for experimenting with AI technologies, addressing the need for supportive IT, HR, and legal frameworks.
Sean White
Sean White is the CEO of Inflection AI, a pioneering company at the forefront of human-AI interaction. With a background in innovation leadership, Sean has held executive roles at Mozilla, BrightSky Labs, and other technology ventures. He brings a unique blend of creative vision and technical depth, focused on building AI systems that are intuitive, ethical, and deeply human-centered.
Episode Summary
In this episode of AI Realized, Sean White, CEO of Inflection AI, discusses the augmentation of human experience through AI and its implications for enterprises. Sean emphasizes AI as a tool to enhance human capabilities and compares AI's evolution to the early Internet era. He discusses Inflection AI’s competitive advantages, such as its large-scale data models and commitment to transparency and user control, including licensing options for enterprises. He highlights use cases in healthcare, regulatory compliance, and enterprise operations. The conversation also explores ethical considerations around AI and wearable technology, the importance of privacy, and the role of federated learning. Sean concludes by encouraging creative thinking about AI's potential and collaboration across the field.
Isar Meitis
Isar Meitis is a seasoned entrepreneur, the CEO of Multiplai, an AI implementation expert, and host of the Leveraging AI Podcast. A former F-16 pilot and Major in the Israeli Air Force, Isar has led four companies as CEO and now advises startups and enterprises on scaling with AI. Known for blending sharp strategic insight with hands-on experience, he’s a sought-after keynote speaker, investor, and mentor driving practical innovation in the AI-powered business world.
Episode Summary
In this episode of AI Realized, Isar Meitis, CEO of Multiplai, outlines crucial steps for successfully implementing AI in organizations. He emphasizes the importance of continuous education and staying updated with AI capabilities, using tools like Google's Notebook LM. Isar recommends forming an AI committee with representatives from different departments and leadership to guide implementation, define rules, and ensure data privacy. The committee should encourage AI experimentation within set guidelines, define the proper tools, manage training, and create efficient processes. Long-term strategies involve conducting strategic assessments, skills gap analysis, and identifying low-hanging fruits for immediate benefits. To drive adoption and enthusiasm, leadership should lead by example, celebrate small wins, and foster human relationships to differentiate in a competitive AI-driven world. Finally, he advises not to fear AI and highlights the importance of hands-on experimentation and learning.
Ivan Lee
Ivan Lee is the Founder and CEO of Datasaur, a platform focused on private LLMs and data labeling for enterprise AI. A former product leader at Apple and founder of multiple startups, Ivan brings deep expertise in natural language processing, AI infrastructure, and product strategy. Recognized as a LinkedIn Top Voice, he’s a prominent thought leader shaping how businesses harness AI responsibly and effectively.
Episode Summary
In this podcast episode of AI Realized, Ivan Lee, founder and CEO of Datasaur, discusses his company's mission to democratize access to natural language processing (NLP). Datasaur introduced a data labeling platform used by major organizations like Netflix and the FBI and launched LLM Labs to facilitate the customization of large language models (LLMs). Ivan elaborates on the importance of evaluating AI models in production, focusing on cost, latency, and quality, and introduces the concept of prompt unit testing to ensure consistent model performance. He highlights the need for data scientists to understand business-side ROI and notes the significant unit costs associated with LLMs. Ivan explores the potential for cost reduction driven by innovations like OpenAI's GPT 4o Mini and open-source models like Lama. He also considers the implications of running LLMs on-device for industries with strict data privacy needs. Lastly, Ivan advises enterprise executives to start small, piloting AI solutions to demonstrate their effectiveness, and emphasizes the future of a multi-model AI solution landscape within organizations.
Mark Heynen
Mark Heynen is a global technology leader and seasoned entrepreneur, currently serving as Chief Product Officer and Co-founder of Knapsack. With deep experience in scaling frontier technologies, Mark has held leadership roles at Stripe, Ripple, and Google, helping bring innovative platforms to global markets. His work spans AI, blockchain, and connectivity, making him a key voice at the intersection of emerging tech and enterprise transformation.
Episode Summary
In this episode of AI Realized, guest Mark Heynen, Chief Product Officer and Co-founder of Knapsack, discusses the motivations behind the creation of Knapsack, driven by data privacy and security challenges faced during AI adoption in regulated industries. Mark explains the importance of bringing AI to data instead of uploading sensitive information to the cloud, highlighting the compliance issues and risks involved with data security and high-cost AI deployments with uncertain ROI. The conversation covers Knapsack's approach using open-source, small language models and the concept of automations as a precursor to fully autonomous agents. Mark emphasizes the benefits of on-device AI processing, enabling real-time and private insights without data leakage. He encourages businesses to experiment with local LLMs and start thinking about automation to enhance productivity while ensuring compliance and data privacy. The episode concludes with an invitation to learn more and engage with Knapsack's private beta.
Matt Maccaux
Matt Maccaux is the Head of Customer Engineering at Google and leads the AI-driven transformation projects that leverage data, modern applications, and cloud operating principles. Previously, as Director of Sales Engineering at Hewlett Packard Enterprise, he led a global team that helped clients convert data into actionable insights, achieving 40% year-over-year growth and $100M in sales in FY23. With over 15 years of experience in AI, Machine Learning, and Analytics, he excels in building high-performing teams and developing data-centric strategies. He is passionate about empowering organizations to unlock the full potential of their data to drive innovation and create value.
Episode Summary
Matt Maccaux, Head of Customer Engineering at Google Cloud, shares practical advice on AI adoption for enterprises and digital natives. He explores ethical data use, reducing bias, and the role of synthetic data. Maccaux stresses the need to improve existing datasets and outlines when synthetic data adds value. He identifies key barriers to deployment—lack of executive buy-in and limited budgets—and advises enterprises to start with productivity use cases. While digital natives move faster due to less technical debt, they also face budget limits. Maccaux urges leaders to engage peers across industries to balance innovation with real-world constraints.
Awais Bajwa
Awais Bajwa, Head of Data and AI Banking at Bank of America, has over 15 years of experience, leading strategic deals totaling over $60 billion. He founded Bank of America’s global AI banking practice in Palo Alto and has unique insights into AI adoption in financial institutions. Awais previously established the software investment banking practice at Bank of America and the digital infrastructure banking practice at Barclays in London. He holds a Master’s degree in Engineering from the University of Oxford, positioning him as a distinguished advisor on AI in the financial sector.
Episode Summary
Awais Bajwa shares the way the Bank of America’s developers are leveraging Gen AI to transform software development and improve efficiency. Key focus areas include augmented code generation, code refactoring, language migration, and test case generation. Bajwa emphasizes the necessity of deliberate implementation within the bank's siloed IT infrastructure, stressing security, risk management, compliance, and scalability. Challenges in adopting AI involve ensuring security, managing risks, and maintaining application robustness in banking operations. Bajwa encourages continuous experimentation with AI technologies and reskilling to stay ahead.
Paul Baier
Paul Baier is the CEO and Co-Founder of GAI Insights, a leading industry analyst firm specializing in enterprise Generative AI. With over 20 years of experience in software leadership, Paul is passionate about helping companies achieve ROI through the use of AI technologies. As an Executive Fellow at Harvard Business School, Paul brings academic insight to practical business applications. He is also the organizer of AI Blueprint for MA, a volunteer initiative supporting AI talent development in Massachusetts.
Episode Summary
In this episode, Paul Baier discusses why enterprises must “own their intelligence” in the era of generative AI. He outlines the risks of cognitive outsourcing to public models, shares practical steps for identifying and protecting strategic data, and introduces the WINS framework for AI prioritization. From rethinking workforce structure to reorienting board-level conversations, Paul urges leaders to learn by doing.