AI Monetisation

• How to Identify High-ROI AI Projects for Your Enterprise

  In this episode of the AI Monetisation Podcast, Anurag Bhagat, Senior Generative AI Strategist at the Generative AI Innovation Center, Amazon Web Services (AWS), joins Binny Mathews, Co-founder of ProjectPro, to share how enterprises can identify and scale high-ROI AI projects with confidence.What's Inside?Why executive demand for GenAI is unprecedented—and what it means for enterprisesA practical framework for prioritizing AI use cases across industriesHigh-ROI use cases like intelligent document processing (IDP) and GenAI-powered contact centersBuilding internal roadmaps vs. point solutions: The key to sustainable ROIWhy data quality, metadata, and risk guardrails still matter in the GenAI eraWhat great data scientists do differently: Bridging business understanding with technical depthKey Takeaways:Prioritize low-hanging fruit early to build momentum and buy-inTrue ROI comes from a portfolio of use cases, not isolated pilotsEnterprise GenAI adoption must account for workflow fit, latency, accuracy, and costExpertise remains critical—AI augments, not replaces, human judgmentBuild agile pipelines to swap in better models as the space rapidly evolvesThis episode is essential listening for business and tech leaders aiming to unlock meaningful value from GenAI without falling for the hype!For full show notes, visit- https://bit.ly/3YUPoXoProjectPro helps you tackle your AI projects with ease. Upskilling the team for specific AI projects, collaborating with experts to co-build AI solutions, or opting for end-to-end project outsourcing—ProjectPro has you covered. With ongoing 1:1 support, enterprises can overcome roadblocks and seamlessly take their projects from PoC to production. Learn more- https://bit.ly/4lQ0k2j

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• How AI Solves 7 Burning Problems in Insurance Underwriting

  In this episode of the AI Monetisation Podcast, Hesaam Aslani, Global AI & Gen AI Leader, Financial Services at Capgemini, joins Binny Mathews, to reveal how AI is transforming the $114B insurance underwriting industry.Guest BackgroundHesaam brings deep domain expertise, having led AI and analytics at QBE, Munich Re, and AIG before heading global financial services AI initiatives at Capgemini. His work showcases how GenAI is revolutionizing core underwriting workflows—from risk analysis to fraud detection.This episode is a must-listen for insurance leaders, actuaries, and AI practitioners eager to see how GenAI can drive real business transformation in one of the world’s most data-heavy industries!For full show notes, visit- https://bit.ly/42Lt4RmProjectPro helps you tackle your AI projects with ease. Upskilling the team for specific AI projects, collaborating with experts to co-build AI solutions, or opting for end-to-end project outsourcing—ProjectPro has you covered. With ongoing 1:1 support, enterprises can overcome roadblocks and seamlessly take their projects from PoC to production. Learn more- https://bit.ly/4cFVAbs

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• How to Build an Enterprise-Ready AI Prioritization Strategy

  In this episode of the AI Monetisation Podcast, Lexy Kassan, Lead Data and AI Strategist at Databricks, joins Binny Mathews to share how enterprises can build a practical, scalable, and enterprise-ready AI prioritization strategy.Guest Background:Lexy brings a rich and diverse background to the table. She started her career as a business analyst and evolved into a data scientist, risk analyst, and now a global thought leader in responsible AI. At Databricks, she works closely with CXOs to guide enterprise AI adoption, drive responsible AI frameworks, and reshape data governance and operational models.What's Inside?✅ AI strategy playbook: How to balance hype, risk, and value✅ The new role of data foundations in enabling successful AI✅ What "last mile AI" really means and why it’s business-critical✅ Build vs. Buy: How to assess enterprise AI solutions smartly✅ Responsible AI: From compliance to cross-functional accountability✅ The evolving role of dashboards, agents, and embedded insights✅ When NOT to use generative AI: A contrarian takeKey Takeaways:1. AI success starts with robust data governance and business alignment.2. Don’t over-engineer—sometimes simpler solutions outperform GenAI.3. Shift from dashboards to actionable, workflow-integrated insights.4. Prioritize use cases based on business value, not just technology excitement.5. Responsible AI is everyone’s job—from IT to legal to business units.This episode is essential listening for enterprise leaders, data strategists, and AI practitioners looking to drive real impact from their AI initiatives—without losing sight of cost, governance, or long-term value.For full show notes, visit: https://bit.ly/4lwsEH3ProjectPro helps you tackle your AI projects with ease. Upskilling the team for specific AI projects, collaborating with experts to co-build AI solutions, or opting for end-to-end project outsourcing—ProjectPro has you covered. With ongoing 1:1 support, enterprises can overcome roadblocks and seamlessly take their projects from PoC to production. Learn more: https://bit.ly/3Y2b8QV

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• How IBM’s Tiny Models Deliver Big ROI: A Guide to Build Fit-for-Purpose AI Models

  In this episode of the AI Monetisation Podcast, Nicholas Fuller, IBM's Vice President of AI and Automation, joins Binny Mathews, Co-founder of ProjectPro, to explore how IBM is achieving real-world business impact with tiny, fit-for-purpose AI models. Guest Background: A 23-year IBM veteran, Nicholas leads global efforts in LLM and agentic AI innovation at IBM Research. From mainframe code modernization to tiny time-series models, his team is redefining how enterprises build scalable, trustworthy AI products.What’s Inside?Why fit-for-purpose models outperform massive LLMs for real-world ROIInside IBM’s 5M parameter “tiny mixer” models for time-series forecastingHow Guardian models ensure enterprise-grade safety and data privacyThe future of agentic AI in IT operations and incident managementWhat it takes to build industrial-grade AI benchmarks like ITBench Key Takeaways Fit-for-purpose AI is more efficient and enterprise-ready than massive general-purpose models.Domain-specific models trained on smaller, high-quality datasets can outperform larger counterparts.Security, provenance, and explainability are critical for enterprise AI adoption.Internal co-creation and enterprise-specific benchmarks accelerate trust and deploymentHiring and retaining top AI talent requires purpose-driven work and deep academic partnerships. This episode is essential listening for enterprise leaders, product builders, and AI practitioners seeking practical strategies to scale AI without compromising on safety, trust, or impact!For full show notes, visit- https://bit.ly/43I4eE5ProjectPro helps you tackle your AI projects with ease. Upskilling the team for specific AI projects, collaborating with experts to co-build AI solutions, or opting for end-to-end project outsourcing—ProjectPro has you covered. With ongoing 1:1 support, enterprises can overcome roadblocks and seamlessly take their projects from PoC to production. Learn more: https://bit.ly/3RFrZoTResources Mentioned:Here are some links to dig deeper into the topics:IBM GraniteGranite Time Series ModelsGranite Guardian ModelsIBM SoftwareITBenchPrompt Declaration Language

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  43:15
• How Automation Eliminates Paperwork in Trucking and Logistics

  In this episode, Gary Kendle, Vice President of Transportation at Weber Logistics, joins Binny Mathews, CEO and Co-founder of ProjectPro, to discuss how automation is transforming trucking and logistics by eliminating paperwork, improving efficiency, and driving cost savings.Guest Background:With decades of experience in transportation and logistics, Gary Kendle has led Weber Logistics’ push toward digital transformation. His work in automating freight management, optimizing delivery networks, and streamlining compliance showcases how modern logistics companies can thrive in an increasingly digital world.What's Inside?✅ The biggest paperwork challenges in trucking and how automation solves them✅ Real-world examples of AI-driven logistics optimization at Weber Logistics✅ Reducing operational costs and delays through automated workflows✅ How digital transformation is reshaping fleet management and compliance✅ The future of automation in logistics: What’s next?Key Takeaways:1. Eliminating paperwork through automation speeds up operations and reduces errors.2. AI-driven logistics improve cost efficiency and customer service.3. Compliance and documentation can be fully digitized for seamless auditing.4. Real-time tracking and predictive analytics enhance supply chain visibility.5. Trucking and logistics companies must embrace digital transformation to stay competitive.This episode is a must-watch for logistics professionals, transportation leaders, and business executives looking to leverage automation to drive efficiency and profitability in the supply chain!For full show notes, visit: https://bit.ly/4jhkWyIProjectPro helps you tackle your AI projects with ease. Upskilling the team for specific AI projects, collaborating with experts to co-build AI solutions, or opting for end-to-end project outsourcing—ProjectPro has you covered. With ongoing 1:1 support, enterprises can overcome roadblocks and seamlessly take their projects from PoC to production. Learn more: https://bit.ly/43Dbpxm

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