Next in Tech

We continue our CEO series with Douwe Kiela, the CEO of Contextual AI, who is addressing the challenges of building effective agentic applications. The shift to agentic amplifies the need for enterprises to improve their data management capabilities and infrastructure scaling. The best models won't perform well, if there isn't well built context to support them. Much like people, if there's not enough of the right information, decision making is going to suffer. There's an evolution from the prompt engineering needed to generate better results from LLM's, to the context engineering that crafts the right data to feed agents.

This is an area where agents can also help to tackle the data quality problem that many enterprises face. Standing the old computing paradigm on its head, effective agentic applications ought to take garbage in and put information out. Well built agentic architectures can understand data characteristics and not only evaluate its quality, but also classify it and apply the appropriate security controls to its use. The scope and scale of agentic potential demands much greater thought to achieve its full value. We need only look to the recent Open Claw project to see both the up and downsides.

More S&P Global Content:

• Next in Tech | Ep. 244: Agentic Customer Experience
• Next in Tech | Ep. 222: FinOps – Managing Cloud and AI Costs
• Next in Tech | Ep. 205: Agentic AI Impacts
• AI for security: Agentic AI will be a focus for security operations in 2025

For S&P Global subscribers:

• Agents in the enterprise: Laying the groundwork for automation
• The CX AI Agent Index 2025
• Agents are already driving workplace impact and agentic AI adoption – Highlights from VotE
• Big Picture 2026 AI Outlook: Unleashing agentic potential

Credits:

• Host/Author: Eric Hanselman
• Guest: Douwe Kiela
• Producer/Editor: Feranmi Adeoshun
• Published With Assistance From: Sophie Carr, Kyra Smith

The next in our series of discussions with CEO's of companies that are putting AI to work has Fransico Martin-Rayo of Helios discussing the agricultural supply chain with host Eric Hanselman. Helios is leveraging AI to generate insights in the complex dynamics of food production and sourcing at a dramatically finer level of granularity. AI not only enables more complex analysis but also allows customized delivery of the results. Shifting interfaces from legacy dashboards and static reports to queryable constructs lets users explore the analyses in ways that better fit their needs. AI can deliver custom insights at scale in ways that weren't possible with traditional application interfaces.

One of the principal shifts accelerating AI, is the availability of better data. Helios integrates massive weather data sets with market history and global events to generate forecasts. While the volumes of data are growing it's seen significant reductions in the cost per token in their infrastructure. Improving efficiency can expand the depth of analysis, as well as the frequency of forecast updates.

More S&P Global Content:

• ANALYSIS: Tariff gap likely to keep China's soybean imports anchored to Brazil
• India to export 2.5 million mt wheat after near 4-year ban
• Look Forward Journal: Geopolitics of data centers
• Next in Tech | Ep. 209: Datacenters and Energy Markets in Europe

For S&P Global Subscribers:

• 2026 Trends in Data, AI & Analytics
• 2026 US Data Centers and Energy Report
• Highlights from Enlit Europe 2025: Flexibility, visibility and digital energy

Credits:

• Host/Author: Eric Hanselman
• Guest: Francisco Martin-Rayo, CEO and Co-Founder of Helios
• Producer/Editor: Feranmi Adeoshun
• Published With Assistance From: Sophie Carr, Kyra Smith

We're kicking off a new series of discussions with CEO's of companies that are putting AI to work to tackle complex problems. Sean Kelly of Amperon joins host Eric Hanselman to dig into how they're using AI for energy grid forecasting. The combination of weather, changes in generation capacity with renewables, and now increased data center demand is making forecasting a critical requirement for grid stability, as well as energy trading. While this might have been a problem that could be tackled with spreadsheets back in the day, scope and scale of the problem has grown to a size that is outstripping traditional methods. AI-based approaches can scale, but there are challenges with managing the size of the datasets being used and the computational costs that some models demand.

Effective integration of AI into complex problem solving demands not only a deep understanding of the problem space, but also innovation in sourcing data and scaling its applications. The payoff can be much faster results with greater perspective depth. But that requires investment in automation and careful engineering to get there.

More S&P Global Content:

• Look Forward Journal: Geopolitics of data centers
• Next in Tech | Ep. 209: Datacenters and Energy Markets in Europe

For S&P Global Subscribers:

• 2026 Trends in Data, AI & Analytics
• Revamped US energy strategy — meeting AI-driven data center demand amid shifting geopolitics
• 2026 US Data Centers and Energy Report
• Highlights from Enlit Europe 2025: Flexibility, visibility and digital energy

Credits:

• Host/Author: Eric Hanselman
• Guest: Sean Kelly, CEO, Amperon
• Producer/Editor: Feranmi Adeoshun
• Published With Assistance From: Sophie Carr, Kyra Smith

There are such significant changes going on in how data is managed and in how AI manages data, that it's not always clear which requirements are driving which trends. Jim Curtis returns to look data highlights from AWS re:Invent and to identify important changes that are taking place. FinOps and broader cloud cost management efforts are leading providers to offer tools and programs to corral spending. AWS has introduced database savings plans to provide discounts in much the same way they've done with other services as they look to foster platform commitment. AWS is also expanding its platform capabilities for AI development, with AWS SageMaker integrating additional tools to simplify the creation and deployment of AI solutions.

The intersection of databases, cloud computing, and artificial intelligence is creating more focus on vectorization. It's fueled the evolution of search capabilities, which offers a more semantically rich and efficient way to organize and retrieve data compared to traditional methods. AWS S3 now has vector support, taking the venerable object store into AI-capable territory. AI is revitalizing established technologies and compelling cloud providers to deliver more integrated and tailored services.

More S&P Global Content:

• Next in Tech Episode 250: The Agentic Enterprise
• Next in Tech Episode 224: Context around MCP

For S&P Global subscribers:

• 2026 Trends in Data, AI & Analytics
• Data Platforms Market Monitor & Forecast 2025
• Survey Data Hub – Voice of the Enterprise: AI & Machine Learning, Use Cases 2026
• Agents are already driving workplace impact and agentic AI adoption – Highlights

Credits:

• Host/Author: Eric Hanselman
• Guest: James Curtis
• Producer/Editor: Feranmi Adeoshun
• Published With Assistance From: Sophie Carr, Kyra Smith

The National Retail Federation's annual NRF conference has become a showplace for the latest technology, as well its core retail foundations. Sheryl Kingstone returns to discuss what was on display and how it will impact retail and the larger tech landscape with host Eric Hanselman. While we may be a ways off from having robot dogs retrieving shoes at your local mall store, automation and agentic applications are delivering significant value in customer interactions - $22 billion in the recent 451 Research study. The days of clunky chatbot interfaces seem to be well and truly behind us.

One the greater challenges in scaling agentic applications is maintaining consumer trust as applications and use cases grow. Part of that trust will depend on effectively managing fleets of agents. In order to scale, organizations have to develop an AI agent control plane that can manage memory, maintain context and guide agent actions. Regulatory requirements are in their early stages, but enterprises have to focus on controls that will ensure they can maintain customer trust as matter of basic business operations.

More S&P Global Content:

• Next in Tech podcast: Agentic Customer Experience
• Next in Tech episode 222: FinOps
• Next in Tech | Ep. 205: Agentic AI Impacts
• AI for security: Agentic AI will be a focus for security operations in 2025

For S&P Global subscribers:

• NRF 2026 Spotlight: Agentic Experiences Redefine Retail Execution
• NRF 2026 Big Show signals physical retail's digital backbone
• Agents in the enterprise: Laying the groundwork for automation
• The CX AI Agent Index 2025
• Agents are already driving workplace impact and agentic AI adoption – Highlights from Vot…
• Big Picture 2026 AI Outlook: Unleashing agentic potential

Credits:

• Host/Author: Eric Hanselman
• Guest: Sheryl Kingstone
• Producer/Editor: Feranmi Adeoshun
• Published With Assistance From: Sophie Carr, Kyra Smith

The choice of use cases in AI has a significant impact on achieving on project outcomes. The latest results of the 451 Research Voice of the Enterprise AI use cases study are out and Alex Johnston joins host Eric Hanselman to explore the data and its implications. The study highlights a widespread, yet often unstructured and fragmented, adoption of AI within organizations, indicating a stall in overall maturity despite significant growth in usage. Key challenges include a clogged project pipeline, where many initiatives remain in limited deployment, and difficulties in consistently measuring return on investment (ROI), although most projects are seen as delivering value.

Organizations achieving better outcomes prioritize strong governance, consistent measurement, and "human-in-the-loop" applications, rather than attempting immediate full autonomy. There are major concerns around data quality, rising costs, and a lack of centralized control stemming from the diverse sourcing of AI capabilities and varied user proficiency. Cost concerns are driving organizations towards

More S&P Global Content:

• Next in Tech Episode 250: The Agentic Enterprise
• Next in Tech podcast: Agentic Customer Experience
• Next in Tech episode 222: FinOps
• Next in Tech | Ep. 205: Agentic AI Impacts

For S&P Global subscribers:

• Survey Data Hub – Voice of the Enterprise: AI & Machine Learning, Use Cases 2026
• Agents are already driving workplace impact and agentic AI adoption – Highlights from Vot…
• Big Picture 2026 AI Outlook: Unleashing agentic potential

Credits:

• Host/Author: Eric Hanselman
• Guest: Alex Johnston
• Producer/Editor: Feranmi Adeoshun
• Published With Assistance From: Sophie Carr, Kyra Smith

We're just out of the recent earnings season and we've seen a wild range of results and some interesting implications. Melissa Otto CFA, head of S&P Global's Visible Alpha research team, returns to discuss what that markets have been saying and what she makes of the data with host Eric Hanselman. Macroeconomic effects are having some impact, as consumer sentiment diverges across the top and the bottom of the economy. In technology, there are mixed feelings about AI as the hunt continues for use cases with decisive revenue returns. The hyperscalers are continuing to invest capital at staggering rates and, so far, the markets have mostly approved. AI supply chain companies, like NVIDIA, are generally moving forward with solid results.

The larger question is where is the AI boom headed. There are constraints not only in supply chains for data centers, but also in energy supply. Agentic AI has a lot of promise, but needs to prove out its value and earn trust, as providers look to improve efficiency with more targeted silicon, like ASICs, to stand up alongside the forests of GPU's being deployed. As investors hunt for improved returns, they may be rotating to international opportunities and small cap companies that might be able to see faster returns from AI deployments.

More S&P Global Content:

• Next in Tech podcast: Agentic Customer Experience
• Nvidia GTC in DC Blackwell expectations increase
• Otto: Markets are grappling with how to price AI-related stocks
• Next in Tech podcast, Episode 239: AI Infrastructure

For S&P Global Subscribers:

• A view of peaks and plateaus
• AI to lead tech spending in 2026, but orgs losing track of energy efficiency – Highlights from Macroeconomic Outlook, SME Tech Trends
• Hyperscaler earnings quarterly: Alphabet, Amazon and Microsoft charge ahead on AI capacity buildouts
• Agents are already driving workplace impact and agentic AI adoption – Highlights from VotE: AI & Machine Learning
• Big Picture 2026 AI Outlook: Unleashing agentic potential

Credits:

• Host/Author: Eric Hanselman
• Guest: Melissa Otto, CFA
• Producer/Editor: Feranmi Adeoshun
• Published With Assistance From: Sophie Carr, Kyra Smith

For the 250th episode, we're looking a bit further forward to explore what enterprises should be thinking about as they look to put agentic capabilities to work. Melissa Incera, Alex Johnston and Sheryl Kingstone return to discuss the challenges and potential with host Eric Hanselman. As AI agents evolve beyond simple chatbots in customer experience and business operations, enterprises have to adapt both their infrastructure and data management capabilities to benefit from agentic potential. Automation is great, but getting to fully autonomous operations requires building more trust than exists today for most. In fact, 451 Research Voice of the Enterprise study results show that those who show a healthy skepticism about agent capabilities are the most successful in achieving their AI project goals.

Agents are making big step forward in establishing continuity in processes by adding memory to AI model interactions. At the same time, concerns about cost are bringing up the need for the same types of visibility and control that's being used with FinOps efforts in cloud. All of this is taking place in an evolving regulatory landscape where the need for a balanced approach between innovation and safety is guiding the best outcomes.

More S&P Global Content:

• Next in Tech podcast: Agentic Customer Experience
• Next in Tech episode 222: FinOps
• Next in Tech | Ep. 205: Agentic AI Impacts
• AI for security: Agentic AI will be a focus for security operations in 2025

For S&P Global Subscribers:

• Agents in the enterprise: Laying the groundwork for automation
• The CX AI Agent Index 2025
• Agents are already driving workplace impact and agentic AI adoption – Highlights from VotE: AI & Machine Learning
• Big Picture 2026 AI Outlook: Unleashing agentic potential

Credits:

• Host/Author: Eric Hanselman
• Guests: Melissa Incera, Alex Johnston, Sheryl Kingstone
• Producer/Editor: Feranmi Adeoshun
• Published With Assistance From: Sophie Carr, Kyra Smith

This year's AWS re:Inforce conference was larger and fueled by greater agentic capabilities. Part of the 451 Research team that was at the conference, Henry Baltazar, Scott Crawford, William Fellows and Melanie Posey, join host Eric Hanselman to explore the announcements and progress that's been made in expanding agentic capabilities and much more. As an incumbent infrastructure provider, AWS is looking to the top of the infrastructure stack to secure their advantage. A suite of developer tools, including the Kiro IDE, are looking to make the creation and operation of agents simpler. There was progress in FinOps, with greater cost transparency and support for partner opportunities in helping customers manage their cloud spend.

There was also a more enthusiastic embrace of multicloud environments, with the introduction of AWS Interconnect, a service that provides easy and scalable interconnection with other cloud providers, with Google being the first and Microsoft Azure said to be in the works. 451 Research's Voice of the Enterprise (VotE) data shows dramatic increases in data migration volumes, making interconnection performance more critical. With the holidays in full swing, how many Mariah Carey song title references can you spot in this episode?

More S&P Global Content:

• Next in Tech episode 236: Data Migration
• Next in Tech episode 222: FinOps
• AI for security: Agentic AI will be a focus for security operations in 2025

For S&P Global subscribers:

• 2026 Trends in Applied Infrastructure & DevOps
• Data Insight: SKU removals run out of steam — hyperscale SKU changes for November 2025
• AWS' agentic strategy comes into focus with AgentCore platform and pre-built agents
• Cloud spending expansion on tap for 2026 despite bleak macroeconomic outlook – Highlights from VotE…

Credits:

• Host/Author: Eric Hanselman
• Guests: Henry Baltazar, Scott Crawford, William Fellows, Melanie Posey
• Producer/Editor: Feranmi Adeoshun
• Published With Assistance From: Sophie Carr, Kyra Smith

Supercomputing has shifted from an esoteric and exotic part of technology to much more mainstream, mostly driven by AI. The massive amounts of computational power that once were reserved for the largest of computing problems in high performance computing (HPC), like weather and seismic analysis, are now commonplace in the world of AI. Analyst Gabriella Brown returns to talk about complex computing problems, quantum computing and photonics with host Eric Hanselman. SC25 has grown to over 16,000 attendees and almost 600 exhibitors, enough to sprawl across St. Louis' Americas Center and into its football stadium. As they mature, the next step in enterprise adoption is working out how all of these will work together. AI is tackling many problems, but quantum could address a whole different class of computing questions.

Quantum computing is scaling up and moving closer to becoming a key part of an everyday computing portfolio. Techniques like quantum annealing are finding practical applications today while pure-play quantum approaches are increasing the density and stability of their computing capabilities as they push for quantum advantage, the point at which they're doing things that classical computers can't. New areas like photonic computing were also on display at SC25, as well as all of the supporting infrastructure to power, house and cool HPC installations. As AI clusters head toward gigawatt power dissipation, they require specialized support.

More S&P Global Content:

• Cybersecurity, talent needs and ongoing adoption were key themes at Quantum.Tech USA 2025
• Access to quantum hardware remains cloudy, but more options are starting to appear
• Quantum computing and the future of data privacy

For S&P Global subscribers:

• 2026 Trends in Applied Infrastructure & DevOps
• Information security, cloud and AI vendors stand out as critical to businesses – Highlights from Vo…
• Quantum Computing Market Monitor & Forecast
• Quantum computing competitive landscape and market forecast: Expecting $6.5B by 2029
• Mea culpa — NVIDIA GTC brings quantum to the stage to help set the record straight

Credits

• Host/Author: Eric Hanselman
• Guests: Gabriella (Ellie) Brown
• Producer/Editor: Feranmi Adeoshun
• Published With Assistance From: Sophie Carr, Kyra Smith