The world of cryptocurrencies has seen no shortage of upheaval, but regulatory clarity that has arrived with recent legislation has created opportunities. Stablecoins are an area that’s seeing renewed interest in FinTech as a means of reducing friction for global payments. Jordan McKee, Sampath Sharma and Nathan Stovall return to the podcast with host Eric Hanselman to look at how stablecoins are being put to work and how they’re being used. For applications like cross border trade and the remittances trade, stablecoins can increase speed and potentially reduce costs. They can be considered another payment rail through which to conduct business. Stablecoins are not without challenges. There are regulatory imperatives to be met, like anti-money laundering (AML) and know your customer (KYC). Trust needs to be built in the market and education is needed around their potential benefits and risks. Traditional banks are getting involved, but they have additional stumbling blocks. There are technical hurdles, such as the readiness of backend systems to handle the higher precision values of stablecoins. And there are new concerns around custody risk, as handling wallets and the enhanced security required are new skills for many. The potential benefits and lucrative markets may give them enough incentive to take the plunge. More S&P Global Content: US banks maintain favorable earnings while confronting economic uncertainty Money20/20 Europe 2025: Key trends and developments Balance sheet, M&A and capital raising strategies for a volatile environment Next in Tech | Ep. 230: FinTech Advances Street Talk | Episode 142: Despite Looming Rate Cuts, Strong Deposit Franchises Still Take The Cake For S&P Global subscribers: Data Insight: Cross-border payments volume to surpass $17 trillion by 2030 Cross-Border Payments Market Monitor & Forecast - Data Visualization Cross-border payments, stablecoins generate buzz at a low-key Money20/20 Asia Tariffs create urgency for payment optimization strategies among large merchants, SMBs Credits: Host/Author: Eric Hanselman Guest: Jordan McKee, Sampath Sharma, Nathan Stovall Producer/Editor: Feranmi Adeoshun Published With Assistance From: Sophie Carr, Kyra Smith
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Industrial Metaverse
Some might think that the metaverse has been a passing technology fad, but rumors of its demise are greatly exaggerated. While the language may have shifted to things like spatial computing and augmented reality, the technologies and use cases have been flourishing. Analysts Neil Barbour and Ian Hughes return to discuss recent study results and industrial metaverse progress with host Eric Hanselman. Companies are working to build a digital thread that runs through their organizations, linking the physical and virtual worlds. They’re leveraging digital twins to simulate operations and putting AI to work creating and populating the virtual environments in which they run. When gaming companies shift to building virtual large world models in partnership with defense contractors, the metaverse has clearly shifted gears. Virtual environments are being used for training as well as strategic planning. Smart phones are being integrated into retail space planning and assessment and emergency teams are playing Tetris to secure helicopter landing sites. The metaverse is alive and well and making some large steps forward. More S&P Global Content: 451 Digital Industries Insider Metaverse Survey: Nearly half of consumers interested in buying smart glasses Metaverse Digest: A look at Augmented World Expo, Snap updates Lens Studio As the Esports World Cup Wraps, Kagan Looks at the Growing Potential of Competitive Gaming For S&P Global Subscribers: Industrial metaverse adoption grows – Highlights from Metaverse B2B survey Metaverse Digest: Generative AI interactive world-building accelerates More consumers piling into virtual worlds – Highlights from Metaverse Consumer survey The dawn of industrial AI Credits: Host/Author: Eric Hanselman Guests: Neil Barbour, Ian Hughes Producer/Editor: Feranmi Adeoshun Published With Assistance From: Sophie Carr, Kyra Smith
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HR Tech
Managing the capabilities of an organization’s workforce is challenging in the best of times, but the current upheaval created by AI technologies entering the workplace makes it all the more complex. The technologies that have put to work around this problem are many and varied and analyst Ethan Ray joins host Eric Hanselman to look at where we’ve come from and where we could be headed. There’s a rush to determine if new technologies are making workers more productive and what skills are needed to leverage them. Both a recent S&P Global study and the HR Tech conference showed some trends that could be transforming working environments. Workforce intelligence approaches are looking to build a wholistic picture of knowledge, skills and ability of employees and then do skills matching and development planning. As in other technology disciplines, a proliferation of tools has made many organizations’ efforts at workforce management complicated. It’s another place where many are considering integrated platforms that that can bring together HR, IT and financial teams to better understand the use of tools and resulting productivity. There are questions about what we can and what we should measure to truly understand efficiency and effectiveness. How can we understand what combination of skills and tools are generating the best financial outcomes? Better technology should hold the answer, but the path forward is not always clear. More S&P Global Content: AI upskilling: Navigating the urgent need for workforce transformation For S&P Global subscribers: Take 5: AI shakes up HR Workday strengthens standing in AI-driven frontline recruitment space with Paradox buy HR teams see AI as vital but face adoption barriers – Highlights from VotE: Workforce Pro… AI holds potential for workplace transformation, but employee concerns must be addressed – Highligh… MIT Manufacturing Day headlined by circular economy, workforce skills and modularity Credits: Host/Author: Eric Hanselman Guest: Ethan Ray Producer/Editor: Feranmi Adeoshun Published With Assistance From: Sophie Carr, Kyra Smith
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Data Migration
Getting data to where it’s needed has always been an infrastructure challenge, but the scope and scale of the problem has become much more acute as data volumes rise and AI demands more. Research director Henry Baltazar returns to look at the latest results from the Voice of the Enterprise Data Migration study with host Eric Hanselman and reflect on how organizations are addressing the crunch in data movement. There’s been a significant increase in the number of enterprises reporting that they’ve moved to migrating petabytes of data and they’re now not only shifting to cloud, but moving between clouds, as well. They’re also enlisting the help of service providers more often, an indication that the scale of these activities requires professional support to manage risk. Data movement at this scale demands a shift in tactics and more are using physical transport, the shipping of storage media to cloud providers, to get the job done. They can’t risk the downtime needed for network transit, although network capacities are also rising. There are opportunities that cloudy environments present in managing data costs and new strategies that enterprises can put to work to lower not only costs, but risks, too. More S&P Global Content: Next in Tech | Ep. 234: Broadcom VMware Explore Conference Next in Tech | Ep. 224: Context Around MCP For S&P Global subscribers: Data Insight: Public cloud storage market to hit $56B by 2029 as data demand rises As data migration evolves, outage and security concerns grow Security concerns, large payloads are key challenges for data migration – Highlights from VotE: Sto… Credits: Host/Author: Eric Hanselman Guest: Henry Baltazar Producer/Editor: Feranmi Adeoshun Published With Assistance From: Sophie Carr, Kyra Smith
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AI Infrastructure
To get to the benefits that AI offers, organizations have to address their technology infrastructure in ways that are much broader than historical approaches. Senior analyst Greg Macatee joins host Eric Hanselman to delve into what’s required and what enterprises are identifying in the recent Voice of the Enterprise AI and Machine Learning study. Enterprises are struggling with raising the success levels of AI projects. Over 60% report moderate to severe challenges in achieving AI success. Bringing together the computational power and the right quality data in the right locations can be complicated in the hybrid environments that more are operating. It’s not just a matter of being more selective with use cases, AI requires a set of organizational skills that have to be honed. Starting small and iterating can reduce risk while building competency. Infrastructure has to shift in new ways, as well. Data management processes that can build the necessary data pipelines to feed AI applications bring together a broader set of tech disciplines. There are new wrinkles in AI infrastructure ecosystems, with new providers looking to address supply chain constraints, like the Neocloud or GPU as a Service (GPUaaS) providers. Even hyperscalers are looking to them to meet surging demand in a tight market. Those new options offer new choices, but enterprises need to match them with their AI goals. More S&P Global Content: Navigating the AI infrastructure landscape The path from LLMs to agentic AI Next in Tech | Ep. 225: Security for MCP For S&P Global Subscribers: AI infrastructure strategies evolve amid widespread data challenges – Highlights from VotE: AI & Machine Learning Generative AI Market Monitor & Forecast AI infrastructure: Trends, thoughts and a 2025 research agenda Credits: Host/Author: Eric Hanselman Guest: Greg Macatee Producer/Editor: Adam Kovalsky Published With Assistance From: Sophie Carr, Feranmi Adeoshun, Kyra Smith
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