Results

IBM’s Advantage Platform: Killing Technical Debt and Scaling AI on AWS

IBM’s Advantage Platform: Killing Technical Debt and Scaling AI on AWS

How do you take projects that used to take 10 months and deliver them in 8 weeks? In this AWS re:Invent conversation, IBM’s Javier Olaizola Casin explains how IBM and AWS are helping enterprises accelerate with data, AI, and hybrid cloud.

We discuss:

  • How IBM's Advantage agentic framework reduces cycle times from months to weeks
  • Tackling technical debt and large-scale application modernization (including VMware exits)
  • Why data curation, governance, and compliance are the real enablers of AI at scale
  • The role of hybrid cloud and AI in transforming workflows and business processes
  • How to move from incremental efficiency gains to step-change business impact
  • Rethinking organizational design for an “always-on,” agentic enterprise
  • Scaling backend systems for a world where every human has multiple AI agents

If you’re working on enterprise AI, modernization, or hybrid cloud strategy, this interview offers a practical view on what it really takes to move faster than your market.

Data to Decisions Future of Work Next-Generation Customer Experience AI Data to Decisions Cloud LLMs Chief Data Officer Chief AI Officer Off

Autonomous Security for Cloud by IBM Consulting

Autonomous Security for Cloud by IBM Consulting

Cloud security was never meant to be manual—but for most enterprises, it still is. In this video, we explore how IBM Consulting’s Autonomous Security for Cloud (ASC), co-developed with AWS, tackles the growing gap between fast-moving cloud environments and traditional, rule-based security operations.

Learn how ASC:

  • Translates industry regulations, client policies, and real-time cloud
  • Metadata into enforceable AWS-native controls
  • Delivers continuous compliance instead of point-in-time audits
  • Uses Gen AI and fine-tuned LLMs to keep security configurations aligned as workloads, policies, and risks change
  • Embeds controls directly into cloud landing zones with infrastructure as code

If your teams are drowning in alerts, managing exceptions, and chasing configuration drift across AWS accounts and regions, discover how autonomous security can help you move from reactive controls to continuous assurance.

Digital Safety, Privacy & Cybersecurity Cloud LLMs Generative AI AI Chief Information Security Officer On

AI, Critical Thinking, and Geopolitical Risk: Inside DisrupTV’s Deep Dive on Gemini, Multimodal AI, and Global Resilience | DisrupTV Ep. 426

AI, Critical Thinking, and Geopolitical Risk: Inside DisrupTV’s Deep Dive on Gemini, Multimodal AI, and Global Resilience | DisrupTV Ep. 426

AI, Critical Thinking, and Geopolitical Risk: Inside DisrupTV’s Deep Dive on Gemini, Multimodal AI, and Global Resilience

On the latest episode of DisrupTV, co-hosts Vala Afshar, Chief Evangelist at Salesforce, and R "Ray" Wang, CEO and Founder of Constellation Research, convened a timely conversation at the intersection of AI innovation, critical thinking, and geopolitical risk.

Joining them were Peter Danenberg, Distinguished Software Engineer at Google and a key contributor to the Gemini AI platform, and Dr. David Bray, Distinguished Chair at The Stimson Center and CEO of LDA Ventures. Together, they explored how multimodal AI, community-driven innovation, and geopolitical awareness are becoming essential capabilities for leaders navigating the Age of Intelligence.

Inside Google Gemini: From Demos to Developer Communities

Peter Danenberg offered a behind-the-scenes look at Google’s Gemini AI platform, including emerging capabilities like Code Canvas and Computer Use, which move AI beyond chat interfaces and into real-world workflows.

A central theme of Danenberg’s work is community engagement. What began as a small Gemini Meetup with roughly 20 attendees has grown into a thriving forum of more than 600 participants—developers, builders, and AI practitioners experimenting at the edge of what’s possible.

These meetups aren’t just technical demos; they serve as a feedback loop between users and platform builders, allowing insights from real-world experimentation to flow directly back to Google’s leadership. According to Denenberg, this user-driven model is critical for shaping AI tools that are both powerful and practical.

Multimodal and Ambient AI: The Next Evolution

Looking ahead, Danenberg highlighted the shift toward multimodal and ambient AI systems—models that can process text, images, sound, and contextual signals simultaneously, and operate continuously in the background of human activity.

These systems aren’t meant to replace human judgment, but to augment decision-making, creativity, and problem-solving. The challenge, he emphasized, is ensuring that humans remain active participants rather than passive recipients of AI-generated outputs.

AI and the Risk to Critical Thinking

Drawing from his widely viewed TED Talk, Denenberg addressed a growing concern: the potential erosion of critical thinking in an era of increasingly capable large language models.

He cited research comparing brain activity when people rely on AI tools versus when they actively create or reason through problems themselves. The takeaway isn’t to avoid AI—but to design systems that challenge users to think, test assumptions, and maintain a sense of ownership over their work.

His experiments with Socratic-style AI learning environments reflect this philosophy: AI should ask better questions, not just provide faster answers.

Geopolitical Risk, AI, and the New Reality for Global Enterprises

Dr. David Bray expanded the conversation beyond technology into geopolitical and cybersecurity realities facing enterprises today. As global supply chains become more fragmented and nation-state actors increasingly weaponize AI, companies must rethink how they manage risk.

Bray emphasized that AI-driven cyber threats now operate at machine speed, requiring equally adaptive and responsive defenses. Traditional, static security models are no longer sufficient when adversaries can rapidly tailor attacks using AI tools.

AI, Cybersecurity, and Board-Level Accountability

One of Bray’s strongest messages was the need for board and executive awareness. AI risk is no longer confined to IT departments—it spans legal, operational, geopolitical, and reputational domains.

He stressed tighter collaboration between CIOs, CISOs, and General Counsel, particularly for organizations operating across borders. Boards must understand not just where AI is deployed, but how geopolitical shifts can amplify technical vulnerabilities.

Human–AI Collaboration as a Competitive Advantage

Despite the risks, both speakers were clear: the future belongs to organizations that master human–AI collaboration.

Denenberg envisions AI systems that help organizations model worldviews, anticipate risk, and explore scenarios—enhancing human foresight rather than automating it away. Bray reinforced this view, noting that resilience comes from pairing machine-scale intelligence with human judgment, ethics, and strategic context.

Key Takeaways from DisrupTV Episode 426

  • AI is moving beyond chat into multimodal, ambient systems embedded in daily workflows

  • Community-driven AI development accelerates innovation and improves real-world adoption

  • Critical thinking must be protected through intentional AI design, not blind automation

  • Geopolitical risk and AI security are inseparable, especially for global enterprises

  • Human–AI collaboration, not replacement, is the defining advantage in the Age of Intelligence

Final Thoughts: Intelligence With Intention

This DisrupTV episode made one thing clear: AI’s true value isn’t found in raw capability alone, but in how thoughtfully it’s integrated with human expertise, organizational culture, and global awareness.

As Vala Afshar and R "Ray" Wang underscored in closing, leaders who invest in community, critical thinking, and contextual intelligence won’t just keep pace with AI—they’ll shape how it responsibly transforms business and society.

In an era defined by rapid technological change and geopolitical uncertainty, intelligence with intention may be the most important innovation of all.

Related Episodes

If you found Episode 426 valuable, here are a few others that align in theme or extend similar conversations:

 

Future of Work Data to Decisions Tech Optimization Chief Executive Officer Chief Technology Officer Chief AI Officer Chief Information Officer Chief Data Officer

From “activation energy” and agent orchestration to donkeycorns and relationship capital, DisrupTV 425 explains what actually separates AI hype from real business impact.

On DisrupTV <iframe width="560" height="315" src="https://www.youtube.com/embed/J5CupyHoVng?si=GHB_W8FIfV0UhJBW" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>

Meta vs. Microsoft: Michael Ni on the AI CapEx Divergence | With Mike Ni

Meta vs. Microsoft: Michael Ni on the AI CapEx Divergence | With Mike Ni

In our latest segment on the Schwab Network, Michael Ni, Vice President and Principal Analyst at Constellation Research, breaks down the contrasting AI investment stories of two tech giants.

While both are spending heavily, the market is rewarding them very differently based on how that capital translates to the bottom line.

The Tale of Two CapEx Strategies.
According to Ni, the divergence comes down to immediate margin contribution versus long-cycle platform discipline:

  • Meta's AI Monetization Loop: Meta put a 70% increase in CapEx on the board, but they successfully showed how that investment directly contributed to margin.
  • Efficiency in the Ad Economy: By embedding AI deeper into ad productization and auto-generation, Meta achieved an 18% lift in impressions and a 6% increase in pricing power.
  • Microsoft’s Long-Term View: Microsoft saw a 66% CapEx increase, but Ni notes the market has "punished" them for their platform discipline, even as Azure continues to turn AI infrastructure into durable margins.
  • Beyond the Chatbot: Ni emphasizes that enterprise buyers are ramping up spend because AI is now showing real ROI within core business processes, not just simple chat interfaces.
Revenue & Growth Effectiveness Tech Optimization AI finance Chief Revenue Officer Chief AI Officer On

Securing AI for Cybersecurity at Enterprise Scale | With Mark Hughes, IBM

Securing AI for Cybersecurity at Enterprise Scale | With Mark Hughes, IBM

In this Davos interview, IBM’s Mark Hughes explains how to secure AI and use AI for cybersecurity at enterprise scale. Learn how AI agents are transforming threat detection, incident response, and identity management, and why governance and security by design are critical to safe AI adoption.
Hughes breaks down the risks of unsecured AI deployments, the importance of post?breach resiliency, and how boards and CIOs should rethink architecture, data security, and agent privileges. He also warns leaders to prepare now for quantum computing and post?quantum cryptography (Y2Q), with disruption expected around 2028–2029.
If you care about AI security, autonomous security operations, hybrid cloud, and quantum?ready cryptography, this conversation is a must?watch for CISOs, CIOs, and board members.
Digital Safety, Privacy & Cybersecurity AI cybersecurity

Learn how AI agents are transforming threat detection, incident response, and identity management, and why governance and security by design are critical to safe AI adoption.

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mark-hughes

Exploring the Future: AI, Quantum Computing, Sovereign Cloud, and Enterprise Security

Exploring the Future: AI, Quantum Computing, Sovereign Cloud, and Enterprise Security

ConstellationTV episode 122 dives deep into pressing trends in AI, quantum computing, sovereign cloud, and enterprise security. With input from Constellation analysts Holger Mueller, Liz Miller, and Chirag Mehta, alongside IBM's Mark Hughes and Constellation Research CEO R "Ray Wang", the episode unpacks the transformative technologies and challenges businesses face as we approach 2026. Here's a breakdown of the key discussions, predictions, and insights to help tech and business leaders maximize the value of this insightful episode.

AI and Quantum Computing: What's Next for Technology?

The first major topic revolves around artificial intelligence and quantum computing, with Holger Mueller shedding light on NVIDIA CEO Jensen Huang’s controversial remarks about frontier AI models. Huang dismissed open-source models by suggesting they would catch up within six months—a claim with limited backing, as Mueller humorously pointed out.

From there, Mueller dives deeper into developments in quantum computing. He highlighted a key announcement from Microsoft, which is building a cloud infrastructure complete with a quantum operating system: 

“Microsoft is having an event as we speak in Copenhagen... they're putting a full cloud infrastructure in front of that, coming up with a quantum OS.”

Additionally, IBM’s and D-Wave’s innovations were discussed in detail. D-Wave, for instance, revealed a strategic acquisition of quantum circuits, which Mueller believes will make the organization a long-term viable vendor: “Can play no either way, which will make D-Wave a more long-term viable vendor.” The takeaway? Quantum computing is on the rise, set to redefine industry capabilities as businesses ramp up efforts in this domain. 

“Strong start of the year for Quantum.”

Sovereign Cloud: Europe's Game-Changing Investment

Sovereign cloud initiatives emerged as another essential theme. Liz Miller emphasized the steady movement by European organizations toward compliance and self-reliance: “We're seeing a whole lot of actual movement in requirements for Sovereign Cloud.” Mueller elaborated on AWS and IBM’s substantial investments.

  • AWS’s Regional Sovereignty in Germany: AWS is creating a full-blown cloud infrastructure in Brandenburg, Germany, akin to its US East region but operated exclusively by EU passport holders—a significant step toward sovereignty: “It’s a massive, almost 7,000,000,000 investment... [and] run by only EU passport holders.”
  • IBM’s Sovereign Cloud Core: On IBM’s front, the company has introduced a system that allows enterprise customers to run locally from their data centers—a lighter but equally valuable step toward sovereignty: “The ability for enterprises to run locally in their own data center... makes it automatically sovereign.”

Mueller concluded with an emphatic prediction: “2026 is also gearing up to be the year of sovereign cloud.”

Enterprise AI and Security Concerns

Mark Hughes (VP at IBM) and Ray Wang delve into enterprise challenges regarding AI security systems. Hughes emphasized AI's dual role in security: enhancing detection and automating workflows while maintaining the integrity of AI deployments.

  • “AI is making us quicker than adversaries.”
  • “We need a security wrap around AI models and agents to ensure functionality.”

He warned that fragmented approaches among enterprises often lead to inefficiencies: 

“Organizations are using multiple approaches, multiple vendors, and are now unable to scale effectively.”

Post-QM Cryptography: Preparing for Quantum Challenges

Hughes also shared sobering projections about quantum threats to existing cryptography systems, predicting that by 2029, quantum capabilities will pose significant risks. Businesses need to start preparing now by identifying vulnerable systems and adopting quantum-resistant cryptography. He urged leaders: 

“Get busy discovering what cryptography you have and looking at how you can remediate.”

Amplifying Decision Velocity and Tackling Tech Debt

This episode underscored the importance of decision velocity—a concept that encapsulates the need for faster decision-making and quicker execution. Wang noted: “The decision velocity has to match the speed of execution. You can't have digital speed and decision delays. It’s time to ramp up now.”

Speakers also highlighted how AI removes excuses for slow decision-making as legacy systems hold businesses back. As Mueller points out, 

“The technical debt that you haven’t addressed is going to hold your AI speed back. The sins of the past will catch up to you in 2026.”

Anticipation for Upcoming Events: Cisco AI Summit

The episode closes with key insights on upcoming industry events, notably the Cisco AI Summit. Wang expressed excitement about its ecosystem approach, which features major names such as Jensen Huang, Tarek Amin, Anthropic, and Anne Neuberger. Chirag Mehta (VP & Principal Analyst) highlighted the growing importance of real-world AI use cases in driving adoption: 

“Applications drive adoption. It’s the workflows that show the value.”


Final Thoughts: Get Ready for 2026

The speakers stress urgency across every topic discussed, from sovereign cloud advancements to exploiting quantum computing and securing AI deployments. Crucially, as highlighted by Mueller: 

“2026 will be the year of sovereign cloud, and of reckoning for technical debt and excuses that have held businesses back.”

Whether you're a business leader navigating enterprise AI adoption, a technology enthusiast exploring quantum computing, or a practitioner grappling with cybersecurity challenges, this podcast offers invaluable predictions and strategies. Take note and act now—the future is approaching faster than ever.

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Don't miss ConstellationTV episode 122, where Liz Miller and Holger Mueller unpack the latest technology news shaping the AI and cloud landscape.

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Why AI Pilots Fail, Why 2026 Matters, and How Entrepreneurs Win in the Age of Agents | DisrupTV Ep. 425

Why AI Pilots Fail, Why 2026 Matters, and How Entrepreneurs Win in the Age of Agents | DisrupTV Ep. 425

Why AI Pilots Fail, Why 2026 Matters, and How Entrepreneurs Win in the Age of Agents

On DisrupTV Episode 425, co-hosts Vala Afshar, Chief Evangelist at Salesforce, and R “Ray” Wang, CEO and Founder of Constellation Research, tackled one of the most urgent questions facing leaders today:

Why does so much AI promise fail to turn into real business results—and what changes next?

Joining them were two voices with very different but highly complementary perspectives on the AI transition:

  • Vernon Keenan, founder of Keenan Vision and longtime industry analyst, known for his work advising enterprises and hyperscalers on AI strategy.

  • Nicholas Thorne, co-author of Me, My Customer, and AI and founder of Autos, focused on how AI is reshaping entrepreneurship, venture creation, and small business economics.

Together, the conversation moved beyond surface-level AI hype to unpack why 95% of GenAI pilots are labeled “failures,” what actually blocks adoption, and how AI is quietly reshaping jobs, consulting, and company creation—often without dramatic headlines.

Why 95% of GenAI Pilots “Fail” (And Why That’s Misleading)

A widely cited MIT statistic claims that 95% of enterprise GenAI pilots fail. According to Vernon Keenan, this number obscures more than it reveals.

Keenan challenged the methodology behind the study, noting its overreliance on balance sheets and survey instruments that fail to capture what’s happening inside organizations. His own research at UC Berkeley Haas, based on interviews with roughly 45 ecosystem participants, surfaced a different root cause:

The Real Problem: Activation Energy

Most enterprises underestimate the work required after deploying an LLM. Simply embedding a model into a chat interface doesn’t create value.

Enterprise AI success requires:

  • Orchestration patterns – agents coordinating tasks across systems, not just responding to prompts

  • Context assembly – harmonizing data across CRM, ERP, finance, support, and operations

  • Agentic processes – AI acting inside real workflows, not alongside them

The models aren’t the bottleneck. System design, integration, and organizational will are.

2026: The Year AI Gets Real (But Diffusion Still Lags)

Keenan described 2026 as “the year AI gets real”—not because the technology suddenly appears, but because economic pressure finally forces adoption.

Key dynamics shaping this next phase:

  • AI agents are already real and generating serious ARR at startups and AI-native vendors

  • Diffusion remains uneven, especially across the mid-market and small businesses

  • Enterprises are still learning how to operationalize agents at scale

Over the next five years, Keenan expects a full transition into what he calls the “age of the agent,” where embedded and overlay solutions unlock a new model of growth.

Once optimized, agents can be replicated infinitely at near-zero marginal cost—introducing virtual employee economics and forcing executives to rethink growth, productivity, and headcount entirely.

Quiet Erosion: How AI Reshapes Jobs Without Headlines

Rather than mass layoffs, Keenan warned of “quiet erosion”—the gradual hollowing out of entry-level and cognitive work.

Examples include:

  • Cognitive commoditization, where much of what MBAs and junior consultants know now lives inside LLMs

  • AI-first boutiques replacing traditional consulting leverage models

  • Small teams using agents to do the work of dozens

The real risk isn’t losing your job to AI—it’s losing your company to competitors who adopt AI faster and more effectively.

Tiny Teams, Donkeycorns, and a Million AI-Powered Businesses

Where Keenan focused on enterprise friction, Nicholas Thorne focused on what AI makes newly possible.

AI dramatically lowers the cost of starting a company—but it also raises the bar for differentiation.

Through his company Autos, Thorne uses agent orchestration to help founders:

  • Generate landing pages, videos, and lightweight apps

  • Set up CRM, lifecycle emails, and ad tests

  • Handle payments and operational workflows

His ambition is bold but grounded: enable one million people to build $1M/year businesses, which he calls “donkeycorns”—small, focused, profitable companies that grind like mules and party like unicorns.

Relationship Capital: The Only Durable Advantage Left

In a world where everyone has access to the same models, Thorne argued that relationship capital becomes the real moat.

Winning companies will:

  • Define themselves by who they serve, not just what they build

  • Maintain deep, continuous feedback loops with early customers

  • Use customer insight to prompt, iterate, and evolve faster than competitors

Your rate of innovation isn’t constrained by the model—it’s constrained by how well you understand your customers.

Key Takeaways from DisrupTV Episode 425

  • AI pilots fail due to lack of activation energy, not bad models

  • Orchestration and context matter more than raw AI capability

  • 2026 marks the start of a multi-year “age of the agent”

  • AI erodes jobs quietly through productivity, not mass layoffs

  • Tiny teams can now compete with legacy firms using agent leverage

  • Relationship capital is the most defensible asset in an AI-saturated market

Final Thoughts: AI as Electricity, Not Experimentation

Across enterprises, startups, and boardrooms alike, the message from DisrupTV 425 was clear:

  • AI is no longer a proof of concept

  • Leaders now demand outcomes, not demos

  • Agents, orchestration, and customer intimacy define winners

Like electricity before it, AI becomes invisible once it’s essential. Organizations that master activation energy, agent-driven workflows, and relationship-led innovation won’t just survive quiet erosion—they’ll define the next era of work and entrepreneurship.

Related Episodes

If you found Episode 425 valuable, here are a few others that align in theme or extend similar conversations:

 

Future of Work Data to Decisions Tech Optimization Chief Executive Officer Chief Technology Officer Chief AI Officer Chief Information Officer Chief Data Officer

From “activation energy” and agent orchestration to donkeycorns and relationship capital, DisrupTV 425 explains what actually separates AI hype from real business impact.

On DisrupTV <iframe width="560" height="315" src="https://www.youtube.com/embed/J5CupyHoVng?si=GHB_W8FIfV0UhJBW" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>

Memory price surge may crimp on-premise AI, data center deployments

Memory price surge may crimp on-premise AI, data center deployments

On-premise enterprise AI deployments and any hardware upgrades for servers, PCs and other devices in the works are going to become more expensive as memory prices surge.

Memory prices have been a concern for the technology industry for months. Trendforce is projecting 80% increases in PC and server DRAM. IDC said the memory shortage will affect smartphones and other electronic devices. In addition, enterprise vendors have already said they plan on passing along memory costs to technology buyers. You can thank the AI infrastructure boom for the memory squeeze.

Simply put, prices everywhere are going to go up for hardware and that reality is likely to crimp on-premises enterprise deployments and any tech purchase. For instance, Micron Technology already has agreements on price and volume for everything it can produce in 2026.

Micron CEO Sanjay Mehrotra said:

“Memory is now essential to AI's cognitive functions, fundamentally altering its role from a system component to a strategic asset that dictates product performance from data center to the edge. This structural shift means that system capabilities heavily rely on advanced memory for real-time contextual processing, which is vital for achieving autonomous and intelligent behaviors in AI data centers as well as in applications ranging from self-driving cars to advanced medical diagnostics.”

Pure Storage’s John Colgrove, Founder, Chief Visionary Officer & Director, said memory is an issue. Colgrove said that rising NAND prices will make it harder for enterprises to buy data center gear and he expects more interest in Pure Storage’s subscription plans. “I think as prices continue to go up on NAND as it becomes harder and harder to obtain new gear. I think that tends to move people more towards Evergreen/One,” said Colgrove, referring to Pure Storage’s subscription plan.

In December, Dell Technologies Jeff Clarke, chief operating officer, said the memory supply and demand mismatch is a big issue. Speaking at an investment conference, Clarke said:

“I've been at this for almost four decades. This is the most unprecedented mismatch in demand and supply that I've ever seen in the memory industry, which you're seeing correspondingly reflected in spot price. But there's an equal component is the material going to be available. We're out with our long-term agreements, our partnerships that we've had for many, many years. I've grown up in this industry, know most of those CEOs for a long period of time, and those relationships matter in these times.”

Clarke also said that these higher memory prices are ultimately pass along to the buyer. He said consumers will be more sensitive to the price increases, but enterprises will buy at market rates to solve a problem.

HPE CFO Marie Myers said at an investment conference in December that increased memory costs will be passed on. “Both DRAM and NAND are sort of leading (in price increases). A lot of this has been driven by just the tremendous demand pressure that's been out there with AI. And the last couple of months, I think we've all witnessed some pretty significant price changes in both NAND and DRAM,” said Myers. “We expect to pass on a lot of these increases in commodity costs to customers.”

Taiwan Semi CEO C.C. Wei said on the company’s earnings call that unit growth will be minimal for PCs and smartphones, but his company is benefiting from the AI infrastructure boom too. The takeaway is to stick with the high-end hardware. Taiwan Semi works with more high-end vendors and “the high-end smartphone is less sensitive to the memory price. So, the demand is still strong,” said Wei.

Bottom line: Hardware upgrades are likely to become more expensive for a wide swath of technology buyers.

Tech Optimization Data to Decisions Big Data Chief Information Officer Chief Technology Officer Chief Information Security Officer Chief Data Officer

What's Agentic Commerce Without Infrastructure? (Distillation Aftershots)

What's Agentic Commerce Without Infrastructure? (Distillation Aftershots)

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Welcome to a new edition of The Board: Distillation Aftershots (*).

This newsletter shares curious and interesting insights and data points distilled from enterprise technology to identify what’s notable.

In this issue, we have to talk about agentic commerce, given how much it was discussed at NRF this past week. Have to… even if we did a newsletter on it before (11/23 issue). The last time we addressed it was an intro to the topic; this time, we have more in-depth links for you to read. First, my take.

I said in the previous newsletter:

I have forever said commerce (or e-commerce as we called it originally) was not supposed to be an application.”

And that is also applicable to agentic commerce: it cannot function independently, it needs a strong infrastructure to support it, and that’s where vendors must provide value. And it turns out most of them agree with that (and that drives me crazy) by releasing open-source, open-API, and easy-to-use resources as part of their agentic commerce offerings. Not a single vendor, as far as I can find, has said they are the only solution for agentic commerce; they all say, “We are part of the solution, check out how we integrate.”

During NRF (the National Retail Federation show in NYC happening every January), technology vendors went crazy to highlight how they are addressing agentic commerce, and how it is the latest (and most likely) way we will shop in the future. Before committing to this vision, remember we said (and attempted) the same about social commerce. And I'm sure there were a few other smaller versions (metaverse, anyone?) of the same that bubbled up at NRF over the years. I am not demeaning the potential value of agentic commerce; I am saying there’s precedence for thinking the latest and greatest technology will replace previous iterations, when in reality it simply adds to the overall, integrated, not-a-standalone-solution model that enterprises run.

And so, the value of agentic commerce, as with past versions of x-commerce, is that by extending the ability to purchase via different interfaces, we extend the availability of the product to consumers. Better ways to get to the product, faster ways to check out, an easier way to choose, pay, expect, and receive. This will never change, even if brain-computer interfaces become the standard model for shopping. Enterprises must ensure their commerce solutions are well-oiled, open, and easy to integrate into an agentic interface. That’s the secret. Always has, always will be: tune up your commerce infrastructure to be a platform for building an Agentic Commerce Ecosystem.

Here are some reading resources:

  1. Walmart, which is proving to be an avant-garde enterprise in AI adoption, announced it is integrating its shopping experience into Gemini. If you are not in Gemini, your commerce system may collapse to Walmart’s ambition. Our own Larry Dignan wrote about it in more detail.
  2. Speaking of Gemini, Google puts its weight behind extending its AI solutions to accommodate all commerce platforms. As they say, “we are combining the best of Google Cloud's AI and infrastructure with a business's own institutional intelligence to power a truly agentic commerce journey” – it is about the customer journey.
  3. While searching for standards, I came across the Agentic Commerce Protocol. I have not seen it being adopted, nor do I think it’s necessary to be honest, but if you are seeking a way to integrate your commerce ecosystem with all frontier models and partners, it’s a place to start.
  4. A LinkedIn post from a vendor (read: take it with a grain of salt) claims a 54% higher conversion rate for agentic commerce versus traditional commerce, along with some ungodly explosive year-over-year growth rate for a solution that has been operating less than a year (here is where the grain of salt comes in handy). Also on LinkedIn: agentic payments are necessary for agentic commerce (hmm… maybe, more on this later).
  5. Before NRF, Bloomberg says ChatGPT enables connections with Spotify, Zillow, and Stripe(to address those LinkedIn comments). Published September-October 2025.
  6. And finally, a BCG research report that tells enterprises how to approach agentic commerce: with caution and consideration. Published October 2025.

What’s your take? We are fostering a community of executives who want to discuss these issues in depth. This newsletter is but a part of it. We welcome your feedback and look forward to engaging in these conversations.

If you are interested in exploring the full report, discussing the Board’s offering further, or have any additional questions, please contact me at [email protected], and I will be happy to connect with you.

(*) A normal distillation process produces byproducts: primary, simple ones called foreshots, and secondary, more complex and nuanced ones called aftershots. This newsletter highlights remnants from the distillation process, the “cutting room floor” elements, and shares insights to complement the monthly report.

Board Strategy New C-Suite ML Machine Learning LLMs Agentic AI Generative AI Robotics AI Analytics Automation Quantum Computing Cloud Digital Transformation Disruptive Technology Enterprise IT Enterprise Acceleration Enterprise Software Next Gen Apps IoT Blockchain Leadership VR Chief Executive Officer Chief Information Officer Chief Technology Officer Chief AI Officer Chief Data Officer Chief Analytics Officer Chief Information Security Officer Chief Product Officer

Agentic AI experiences will determine enterprise winners

Agentic AI experiences will determine enterprise winners

Agentic AI to date has revolved around architecture, standards, use cases, process automation and productivity, but customer experiences and visions of reinventing categories are moving to the forefront.

Simply put, the agentic AI winners on both the buy side and sell side will likely be decided by customer experiences. This CX-meets-AI theme is already emerging on the consumer side. In recent weeks, we've seen the following:

  • Google said Gemini is getting personal with Personal Intelligence, a setting that connects your personal Gmail, YouTube, Google Photos and other apps to Gemini. It's an interesting move that highlights how AI agents are going to create personalized experiences.
  • OpenAI is planning on being a healthcare industry AI player with the launch of OpenAI for Healthcare, a HIPAA-compliant version of ChatGPT for clinicians, just days after debuting ChatGPT Health for consumers. The upshot here is that ChatGPT wants to be your healthcare front door. OpenAI also outlined its 2026 focus on practical AI.
  • Anthropic also launched Claude for Healthcare, which aims to be "a complementary set of tools and resources that allow healthcare providers, payers, and consumers to use Claude for medical purposes through HIPAA-ready products." In addition, Anthropic launched Claude Cowork, which is a research preview that enables you to bring agentic tools to the desktop.

A card carrying cynic (guilty as charged) would note that these efforts are really about stepping in front of value chains to be the gatekeeper. If Google, OpenAI and Anthropic platforms become the primary distribution platform, they'll reap the AI rewards. But the real game in the enterprise trenches will revolve around agentic experience.

At three conferences this week (two investment meetups and National Retail Federation), the CX end of the agentic AI equation started to surface for the enterprise. Retailers talked about integrating AI agents and vendors pitched multiple approaches. Google launched Universal Commerce Protocol (UCP), a standard for agentic AI commerce, checkout directly through AI mode along with direct offers and interactions to connect brands and shoppers. Google Cloud also unveiled Gemini Enterprise for Customer Experience, a suite that includes a shopping agent, customer experience agent studio, Vertex AI powered search and food ordering agent.

Other vendors also lined up a parade of AI agent announcements.

The real agentic AI magic will occur when the customer is delighted because an agent just gets you. This vision was outlined by Walmart's Daniel Danker, Executive Vice President of AI Acceleration, Product & Design. Speaking at the ICR Conference, Danker said Walmart isn't worried about being disintermediated. Its partnerships with OpenAI and Google are about growth.

The future is Walmart's agent working with other agents to provide a seamless customer journey. This agentic shopping journey will be practical, friction free and helpful. Walmart is positioning itself as the execution and fulfilment backbone of AI discovery and commerce.

"We understand customers so well that we know that they're probably running out of laundry detergent. It's also recognizing that because they tend to buy a gallon of milk, they're probably in a 4-person household, so they're probably going through laundry detergent at a certain pace. And so, we know the right moment to recommend that laundry detergent. Agentic AI will then just go ahead and send you the laundry detergent before you even run out of it. So that's the promise. We're on a journey toward it. We're not quite there yet, but we're moving fast," explained Danker.

Danker noted that consumers will always love shopping--it's a sport to many--but agentic AI can automate the mundane to improve experiences.

Walmart isn't the only giant thinking through agentic commerce experiences. Albertsons CEO Susan Morris said the company is partnering with the likes of Google, OpenAI and Databricks to ensure "every decision is smarter, every process is more efficient and every interaction is more seamless."

Morris said the biggest bet for agentic AI is digital customer experiences. "Our autonomous shopping assistants are meeting customers where they are and delivering frictionless personalized journeys, keeping our omnichannel customer experience modernized and on trend," said Morris.

Agentic CX will also move beyond retail. Healthcare is a major focus for both vendors and enterprises. Salesforce's Mark Sullivan, President of Salesforce, said at the JP Morgan Healthcare Conference that AI agents can become a healthcare concierge. He noted CVS, which recently outlined its engagement vision, and AstraZeneca were Agentforce customers.

CVS Health CEO David Joyner has said the company is focused on "building a simpler, more connected and more affordable health care experience for consumers, health care professionals, and payors." The goal is to be the "front door to healthcare."

Sullivan laid out how agentic AI can deliver care. "Finding care providers is more difficult than ever, and we think this can solve that problem. And then we think of any experience that you have with any procedure you might have, the prep, the post, the follow-up, we all depend on our spouses to do those things. And that's not necessarily the right way to do it. Why? Think of the old medicine where your doctor might call you before, make sure you did all the things that you need to do before your procedure and might follow up after to make sure you took the right medicine and didn't find your way back to the emergency room," explained Sullivan. "We think agents can do that. And we think we can do that better than anything that's ever been rendered before. And we think that keeps people out of the emergency room. We think that changes the health care economy in a meaningful way."

Veeva CFO Brian Van Wagener said the company is rolling out AI agents across its product line to better deliver care. Veeva is a top CRM provider for healthcare and life sciences companies. "We think the combination of those two things, AI in the platform and deep industry-specific agents is going to be transformational for the long term for our customers and is a place where we can bring a lot of value," said Van Wagener.

Michael Farrell, CEO of Resmed, said the theme of an AI-driven health concierge is critical for its core value, which sits at the intersection of health and sleep. "We also have a non-FDA-cleared product because it's just a concierge that I call our digital sleep health concierge. It's called Dawn. Not as in a woman, but as in the sun rising over the horizons that you wake up refreshed. And this is a digital sleep health concierge to help you with questions about exercise, drinking water, balancing your day life to have a better sleep life, stopping caffeine after sort of 5 clock, not having alcohol after 8," said Farrell.

 

The customer experience in industrial markets is different than retail or healthcare, but the role of agentic AI as an enabler is the same. Caterpillar launched its Cat AI Assistant and primary objective is to make it easier for customers to buy, maintain, manage and operate equipment. Speaking at CES 2026, Caterpillar Chief Digital Officer Ogi Redzic said "for a customer Cat AI Assistant is like a proactive partner. It flags machines that need attention, provides custom insights and makes actionable recommendations."

Under the hood, Cat AI Assistant "is a group of AI agents operating together on top of our digital ecosystem presented as a single, single assistant that's multimodal," said Redzic.

In finance, this agentic-AI-meets-CX theme is also powerful but has more of an employee spin. Bank of New York CEO Robin Vince said the company is focused on AI agents and digital workers that are primarily focused on its employee experience.

Google Cloud said in December that Gemini Enterprise is integrated into Bank of New York's Eliza AI platform. Robin Vince, President and CEO of Bank of New York, said agentic AI transforms the culture.

"We now have an enterprise AI platform, Eliza, that's general intelligence, model-agnostic and it supports this multi-agentic functionality that underpins the digital employees. Then we've put in place the resources to support that to really enable the scaling of it," said Vince. "We've got our own Nvidia hardware and tech, but we've also got the collaborations with Google, OpenAI and others. We're proud that in 2025 alone, we deployed over 130 digital employees, industry-leading multi-agentic AI capabilities. Our digital employees work alongside our people, supporting them with tasks like validating payment details and remediating code vulnerabilities, allowing teams to focus on higher value work and client outcomes."

Citigroup CEO Jane Frazer said the company's AI efforts have transformed operations and now it is focusing on client experiences. "We are shifting our focus to how we can use AI tools and automation to further innovate, reengineer and simplify our processes beyond risk and controls to improve client experience whilst reducing expenses," she said.

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