Episodes
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Ajay Patel is the General Manager of Apptio and IBM IT automation. He and Kieron Allen sat down to talk about how enterprises are transitioning from AI experimentation to real business impact. They explored key challenges like cost transparency, governance, and data readiness, as well as the rise of agentic AI to automate workflows at scale. Ajay also introduced Apptio’s new AI TCO and Usage tool, designed to help CIOs and CFOs measure and optimize AI investments.
Smart Spending on AI
The Big Themes:
Enterprises Are Moving Beyond AI Experiments to Strategic Deployment: The era of AI experimentation is over. Enterprises are now actively deploying AI, particularly in sales, service operations, and software development. However, those achieving meaningful impact are taking a strategic approach, rather than letting teams experiment in silos. The C-suite increasingly sees AI as critical, but that value perception isn’t always shared by the wider workforce.AI and IT Budgets: AI now consumes more than 20% of IT budgets, yet overall tech spending is only increasing 4–5%. This creates a 10–15% gap, leading companies to “forward fund” AI initiatives by reallocating from other areas. A key challenge: there’s no standardized pricing for AI. To address this, IBM's Apptio launched the AI TCO and Usage solution. It helps CIOs and CFOs baseline current AI investments, measure unit economics, and identify areas to optimize or expand.Agentic AI, the Next Frontier: Agentic AI is key to scaling beyond isolated use cases. It enables automation at scale and connects AI investment to tangible business outcomes. From cost savings in infrastructure to better visibility in FinOps to boosting customer experience, the ROI is clear when deployed correctly. But none of this happens without data readiness, governance, and strategic clarity.The Big Quote: "AI TCO solution fundamentally starts by giving CIOs [and] CFOs in the business a complete view of where the tech spending and AI spending is, and what stage is that? Is it in a pilot phase? Is it for training models?"
Learn more:
Connect with Ajay Patel on LinkedIn and learn more about Apptio.
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Welcome to the Cloud Wars Minute — your daily cloud news and commentary show. Each episode provides insights and perspectives around the “reimagination machine” that is the cloud.
In today’s Cloud Wars Minute, I dive into Slack’s bold move to restrict API access to bulk data exports, effectively blocking the use of its platform data for LLM training and signaling a strategic pivot toward proprietary AI control and heightened data security
Highlights
00:03 — Salesforce has changed the API Terms of Service for Slack, which will stop companies from using LLMs to ingest data from the platform. Ultimately, the new policy prohibits the bulk export of Slack data via the API and confirms that data access through Slack APIs cannot be used for LLM training.
00:21 — From now on, companies will have to use Slack’s new real-time search API. In a blog post by the Slack developer team, the company states that this new API eliminates the need for large data exports from Slack, keeping customer data secure while maintaining support for key use cases like permission-based search.
00:56 — Now, while Salesforce and Slack say the focus is on security, there is another angle being discussed, that this move encourages a shift towards proprietary technologies. It’s difficult to pinpoint this trend. On one hand, we see a push for interoperability across the industry, while on the other, Slack’s announcement on the real-time research API coincided with support for the Model Context Protocol.
01:25 — Data is still the currency that drives AI and sharing it recklessly with any LLM that requires access can be counterproductive from a business standpoint. Companies like Salesforce don’t want to be liable for data used by third-party applications, and none of the major tech companies want to stifle innovation with overly restrictive policies.
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In this episode of the Office of the CFO Podcast, John Siefert hosts Rob Ashe, VP of North America, SignUp Software, and Blaine Grzegorek, Senior Solution Architect, Sikich, for a conversation on the benefits of partnering with ISVs, top considerations when selecting an ISV, and the impact of AI agents.
Key Takeaways:
Risks of building your own solutions: One major risk that's becoming more prominent is having the expertise in-house to build custom solutions. Another hurdle is the upfront costs compared to subscription costs associated with many ISVs. Oftentimes, Ashe notes, "You have to spend a lot of capital on new tools...to make this new solution or change a process." Grzegorek suggests a third challenge which is meeting compelx needs. Oftentimes, industry expertise is also required, as you may be able to build the technology but might not be ready to translate the business needs to the ERP.Benefits of partnering with an ISV: A big reason organizations turn to ISVs is that they develop purpose-built solutions to address multiple different situations and multiple industries. "That's what I've found clients like about it, there might be a core functionality out of the box but it doesn't really handle every scenario," Grzegorek says. Working with ISVs provides expertise in various industries to consult with to address specific issues and needs.Considerations: Because ISVs work on these types of projects regularly, they are aware of more elements to take into consideration. For instance, Ashe describes how ISVs look at the landscape within Dynamics 365. It's important to consider how the solution will integrate with existing systems, how it will impact security, where data is being sourced from, and more.Selecting an ISV: When selecting an ISV, there are some qualities you should look for to ensure unexpected situations are taken care of. "The documentation they have, that speaks a lot to what they're able to contribute on an ongoing basis," Grzegorek says. Clients are looking for partnership, and working with an ISV is a partnership. You want to be confident that you can reach out to your ISV and get answers right away. "It's hard to see that before you actually start that partnership, so I go to that documentation of what the solution has, what it solves, and if that stuff is detailed...that is a huge indicator." Initial interactions with them are also a good sign of this.Multiple ISV solutions from a single vendor: It's always beneficial to have an ISV that can provide multiple solutions in different areas. One thing to look out for, Grzegorek highlights, is to make sure that the ISV has good alignment internally. Integration time is also a major focus, considering whether you have to integrate or if it's embedded in the system.AI agents and Microsoft Dynamics 365: While the solutions themselves are very powerful, AI agents can add a new level of efficiency. Ashe shares an example of how individuals are now running teams of agents to automate various functions. There are agents fulfilling individual functions within Dynamics 365 that customers are already using, so SignUp Software is like an extension of the platform and the workload. "We feel like we have a really strong value proposition to bring back to Microsoft to leverage the strength and the roadmap of the platform, but then also have immediately valuable solutions that they can take advantage of now," Ashe says.
This episode is sponsored by SignUp Software.Visit Cloud Wars for more.
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In today’s Cloud Wars Minute, I break down the latest growth rankings among the top 10 cloud providers, highlight Google Cloud’s continued lead, and show how legacy giants like Oracle and SAP are rapidly transforming into cloud powerhouses.
Highlights
00:15 — I wanted to share with you the latest numbers for the Cloud Wars Growth Chart, where we take a look at the growth rates of the Cloud Wars Top 10 companies. Google Cloud holds on to the number one spot. But SAP and Oracle are breathing down Google Cloud's neck. Google Cloud grew in its most recent quarter by 28%, with revenue of $12.3 billion.
00:51 — Tied for second place are these two so-called legacy companies. Both grew in their most recent quarters by 27%. SAP’s cloud revenue is now $5.3 billion, Oracle’s $6.7 billion. Next quarter, it is likely that Oracle could well be number one on this list. But that's all the future, and we will see how that goes.
01:42 — In fourth place is Microsoft, 20% growth rate on $42.4 billion in revenue. ServiceNow grew 19% as it cracked $3 billion for the first time in a quarter. AWS, 17% — $29.3 billion. Similar to what we said about Microsoft: 17% growth rate on almost $30 billion in revenue is very impressive.
03:00 — Workday, up almost 14%, to $2.1 billion. Salesforce at 8%, $9.8 billion. Snowflake, up 26% to $997 million. I’m not placing Snowflake within the regular run until its quarterly revenue exceeds $1 billion. It's extremely likely that next quarter, we’ll see Snowflake take its place in the regular run of companies. IBM does not report its cloud revenue anymore. I hope IBM will change that policy.
04:22 — It’s fascinating to see a purely built-for-the-cloud company, Google Cloud, in the number one spot. And who’s behind it? Two venerable companies — mostly still in the software business completely for SAP — but Oracle now, in addition to its fast-growing cloud software business, also has a hypergrowth cloud infrastructure business.
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Balazs Molnar, CEO and co-founder of Rabbit, chats with Kieron Allen about the evolving challenges of cloud cost management and how engineering teams have become central to tackling them. He explains why traditional FinOps tools fall short, how Rabbit dives below the surface to uncover hidden waste (especially in platforms like BigQuery) and why automation is essential for real savings.
Optimizing Cloud with Rabbit
The Big Themes:
Cloud Costs Take Center Stage: Companies are no longer asking, "What can we build on the cloud?" They're now asking, "Why is this so expensive?" Rabbit's origin stems from this exact pivot: cloud costs spiraled out of control, catching businesses off guard. Despite robust migration to cloud environments like Google Cloud, companies found themselves ill-equipped to understand the hidden inefficiencies causing waste. Cloud spend can quickly balloon without the right oversight.The Cloud Buffet Problem: Balazs described cloud computing like a buffet: Engineers can take whatever they want, whenever they want. The cloud’s flexibility is its strength but also its greatest risk. Unlike traditional on-prem setups that required hardware purchases and physical limits, cloud environments are boundless. Engineering teams now hold the wheel, yet they’re typically not tasked to steer toward efficiency. This creates what Molnar calls a "FinOps trap": assuming finance can solve a problem that’s fundamentally technical.Why Optimization Matters Now: Cloud vendors are still growing at impressive rates, but cracks are forming. Some businesses are exiting the cloud, not because they dislike the model — but because costs feel unmanageable. Molnar warns that in most cases, this isn’t a cloud problem — it’s an optimization problem. The promise of cloud was flexibility and scalability. But without proper tools, it becomes unpredictably expensive.The Big Quote: "We all know the news that cloud vendors are growing 30%+ on a year-over-year basis. But we also started to see cracks in the system where companies are actually deciding to move out of the cloud because it's too expensive to them. But the reality [is] it might not have to be that expensive. It's just not optimized."
More from Balazs Molnar and Rabbit:
Connect with Balazs on LinkedIn and check out more about Rabbit.
* Sponsored podcast *Visit Cloud Wars for more.
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Assist, Accelerate, Transform
The Big Themes:
Workday’s Agent System of Record: Workday's Agent System of Record manages the emerging digital agent ecosystem. It provides structure and governance to what could otherwise become a chaotic sprawl of AI agents. By embedding agent management into existing organizational hierarchies, Workday ensures that agents become a structured extension of the workforce rather than a disconnected experiment.Shift Toward Role-Based Agents: Workday is designing agents to reflect the roles and responsibilities of human workers. Rather than focusing narrowly on task or function-specific agents, Workday emphasizes role-based agents that closely align to actual jobs within an organization. Examples include payroll agents, financial audit agents, employee self-service agents, and recruiting agents.Three-Phase Customer Framework: To ease customer adoption, Workday has a three-step framework: Assist → Accelerate → Transform. The assist phase focuses on basic productivity improvements, giving employees relief from repetitive, low-value tasks. Then, companies enter the accelerate phase, expanding the use of agents to drive more meaningful efficiencies and process optimization. The final transform phase represents the full reimagining of work processes with human-agent collaboration at the core.The Big Quote: “A mindset shift for us as AI developers is we made AI as features to solve problems, and now we're thinking a lot about AI as a group of skills."
More from Shane Luke, Ali Fuller, and Workday:
Connect with Shane and Ali on LinkedIn or learn more about Workday's Agent System of Record.
This episode is sponsored by Workday.
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The Big Themes:
SAP’s Flywheel Strategy: SAP introduced a compelling flywheel model that integrates applications, data, and AI to drive enterprise momentum. The idea is that integrated applications generate structured data, which then feeds a robust AI layer. As these layers build on one another, they create a self-reinforcing cycle of productivity, insight, and innovation—a flywheel effect. Unlike Microsoft and ServiceNow, which predict the collapse of applications in favor of agents, SAP asserts that AI agents will enhance, not replace, applications.The Business Data Cloud and Databricks Partnership: A highlight of the event was SAP’s Business Data Cloud (BDC), launched in partnership with Databricks. This foundational layer brings together internal SAP data and external sources like Moody’s or climate models, enabling richer decision-making. SAP showcased real-world use cases, such as tariff fluctuation impact analysis across supply chains, to demonstrate the power of combining enterprise and contextual data.Prompt Optimizer and the End of Prompt Engineering: SAP’s introduction of a “Prompt Optimizer” signals a shift in the AI interface landscape. Instead of manual prompt engineering, users will soon rely on AI to manage and optimize prompts across multiple large language models (LLMs), including ChatGPT, Claude, Gemini, and Perplexity. CTO Philipp Herzig even declared we’re at “the beginning of the end” of prompt engineering.The Big Quote: "[Customers are] not ready to deploy AI and have that completely eliminate the need for apps. The data is just not there. So, maybe five years from now, let's see what progress we've made. But what's in the here and now is that customers are looking for applications."
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Parisa Tabriz is vice president and general manager for Google Chrome, the world’s leading browser platform. She leads efforts to make Chrome a secure and essential enterprise workspace, integrating AI and advanced cybersecurity to meet evolving business needs. In this episode, Parisa joins Bob to explore how Chrome is redefining the browser as a productivity and security platform, the role of AI in enterprise protection, and what’s next for Chrome’s innovations.
Chrome at Google Cloud Next
The Big Themes:
Chrome’s Evolution into a Central Productivity and Security Platform: Over the past 17 years, Chrome has transformed from a simple web browser into a comprehensive platform integral to enterprise productivity and security. Users now spend a significant portion of their workday within Chrome, utilizing it for tasks ranging from document editing to video conferencing. This shift has positioned Chrome as the new endpoint in enterprise environments.Simplifying Enterprise Security with Chrome: Complexity is often the enemy of security. Chrome aims to simplify enterprise security by integrating protective measures directly into the browser, reducing the need for multiple, potentially conflicting security solutions. Features like automatic updates, built-in phishing protection, and centralized policy management allow IT teams to maintain a secure environment with less overheads.Personalization, Governance, and AI Empowerment: Chrome prioritizes features that allow organizations to personalize user experiences while maintaining strict governance over data and AI usage. Tools like data masking, controlled copy-paste functionalities, and the ability to designate approved AI applications help prevent data leaks and ensure compliance with internal policies. By providing these controls, Chrome empowers enterprises to harness the benefits of AI technologies responsibly.The Big Quote: ". . . the browser is the place where you can give people access to the benefits [of AI], but also make sure that you have the controls and governance to turn it off or make sure that your employees aren't copying and pasting data into an unsanctioned AI surface."
More from Parisa Tabriz and Google Chrome:
Connect with Parisa on LinkedIn or learn more about Google Chrome.
Visit Cloud Wars for more.
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Highlights
Google Cloud’s AI Revolution and Customer Success (00:10)
Renner talks about how, for Google Cloud, delivering great outcomes for customers must come before achieving returns. Efforts are underway to push brainpower and expertise directly to customers, while simplifying the sales process by infusing more industry-specific knowledge. Customers are focused on realizing tangible business outcomes with AI.
Google Cloud’s Ecosystem and Partner Ecosystem (02:02)Google Cloud is the fastest-growing company in the Cloud Wars, achieving $12 billion in revenue last quarter. A sharp focus on business outcomes, paired with a robust ecosystem of expertise, is credited for this success. Renner discusses Google Cloud’s partner ecosystem development under Kevin Ichhpurani, president, global partner ecosystem. Growth across the partner ecosystem, including SIs, ISVs, and boutique functional experts, remains a key driver of momentum.
Customer Success and Innovation at Google Cloud Next (03:46)
Innovation and customer success were on full display at Google Cloud Next in Las Vegas, with major product launches and enthusiastic customer testimonials. Marking his two-year anniversary, Renner reflects on how AI has accelerated customer success’ evolution. The volume of customer stories and advocacy is proof of exceptionally high engagement. Many customers have already moved beyond experimentation into full production.
Customer Mindset and Business Outcomes (06:09)
Today’s customers are reimagining what’s possible through AI, marking a profound shift in mindset. Renner talks about the eagerness and commitment of Google’s engineering and consulting teams to work side-by-side with customers. As customers become more sophisticated, they are increasingly focused on identifying business impact and making strategic investments. A collaborative and creative problem-solving approach is central to how Google Cloud delivers value.
Budget Shifts and Business Engagement (07:37)
AI adoption is driving a major shift in spending away from traditional IT control toward broader enterprise engagement. Renner notes that while business engagement has always been important, AI has accelerated the breakdown of old barriers across industries. Teams are approaching go-to-market strategies more mindfully. Verticalization and deep industry focus have become essential in driving business outcomes.
Ecosystem Growth and Customer Demand (11:17)
Google Cloud’s ecosystem continues to expand, with ISVs and SIs playing an increasingly critical role. Renner points to partnerships with Salesforce, ServiceNow, and others as key to expanding Google Cloud’s reach, building credibility, and scaling to meet growing customer demand. The expansion of regional SIs is equally important, ensuring global customer needs are met effectively.
Google Cloud’s Growth and Market Position (13:23)
Renner attributes Google Cloud’s leadership as the fastest-growing company in the Cloud Wars to its focus on customer business outcomes. This strategy has fueled new customer acquisition, a growing sales backlog, and sustained high demand. AI is transforming how Google Cloud engages with customers, driving growth across every product line and deepening its market position.
Leadership and Team Enabling (15:35)
Under the leadership of CEO Thomas Kurian, Google Cloud has made extraordinary strides in customer success and growth. Renner praises Kurian’s passion, energy, and clarity of vision. A major focus remains on providing field teams with the right assets, tools, and alignment to be successful. The addition of new talent to oversee the customer experience journey, reflects Google Cloud’s commitment to strengthening its leadership bench.Final Thoughts and Future Plans (18:32)
Renner shares his appreciation for the opportunity to reflect on Google Cloud’s strategic focus and achievements. The interview closes with a reaffirmation of the AI revolution’s significance and Google Cloud’s central role in shaping the future of business innovation. The outlook is positive.
Google Cloud’s central role in shaping the future of business innovation. The outlook is positive.
This episode is sponsored by Google Cloud.
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this special episode of Cloud Wars Live, Bob Evans chats with Gerrit Kazmaier, president, products and technology, Workday. They explore how Workday is evolving into a platform company, the role of AI agents in reshaping enterprise workflows, and why trust, accuracy, and extensibility are key to future-ready business solutions. Kazmaier also discusses Workday’s approach to ecosystem innovation and composable ERP.
Workday's AI Future
The Big Themes:
Real-World Business Value From AI-Driven Results: Workday’s AI capabilities are already producing concrete results. Kazmaier shares examples like a recruiting agent that increased recruiter capacity by over 50% and contract intelligence tools that slashed legal costs by up to 60%. These aren’t experimental features—they’re embedded in Workday’s workflows to improve productivity and efficiency.Agents Will Enhance, Not Replace Applications: Kazmeier addresses the myth that AI agents will replace applications. Instead, Workday sees agents as accelerators of existing apps. Many enterprise applications were designed around human cognitive limits, but now AI agents can take over some of those mental loads. Over time, agents will become so proficient they’ll perform roles autonomously. But they won’t erase apps,they’ll enhance them.Composable ERP Is Now a Reality: Workday is making good on the long-promised vision of composable ERP: modular, customizable systems that allow organizations to choose the best tools for each job. Historically, integration challenges made composability difficult. Now, AI simplifies that complexity. Intelligent interfaces and smarter integration allow Workday’s ecosystem to plug into its core platform more fluidly.The Big Quote: “This is like early Internet days . . . some people had innovative ideas. But economics weren't just there. Bandwidth was limited and expensive; not everyone had an Ilenternet-ready device...but as exponential improvements happened . . . an entirely new economy was invented, and I think it's the same with AI."
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At Google Cloud Next 2025, Google Cloud Vice President of Applied AI Duncan Lennox sits down with Bob Evans in part three of our series "Google Cloud and the AI Revolution." They discuss how Google Cloud is redefining enterprise applications through purpose-built AI agents, the shift from incremental to transformational innovation, and how businesses can harness agentic AI to deliver seamless, end-to-end customer experiences at scale.
Google Cloud’s Agentic Revolution
The Big Themes:
Beyond Infrastructure to Applied AI: Historically, Google Cloud was associated with infrastructure, data analytics, databases, and backend technologies. However, it's now undergoing a transformation, stepping boldly into the realm of applied AI. Rather than just competing with established players in enterprise applications (like ERP, HCM, or CRM), Google Cloud is innovating at a more foundational level by creating entirely new types of agents and applications.The Customer Engagement Suite, A CRM Rethink: Google Cloud’s Customer Engagement Suite isn’t just an upgrade to traditional contact center software — it’s a full reimagining of how businesses engage with customers. Historically, customer service was seen as a cost center: something to be optimized for efficiency and minimized wherever possible. Google Cloud flips that on its head. With the Customer Engagement Suite, the focus shifts toward creating differentiated, high-quality customer experiences that build brand loyalty, satisfaction, and even new revenue streams.Best Adoption Practices: Lennox discusses several best practices for companies looking to succeed with applied AI. First, start somewhere tangible — don't try to "boil the ocean." Select a high-visibility area where AI can solve real problems and produce measurable results. Second, tie your efforts directly to business outcomes, such as customer experience improvements, revenue growth, or operational savings. Third, choose a strategic partner capable of evolving with you as the technology advances.The Big Quote: "Experimentation is great, of course, but what I see more and more as I talk to C-level executives is they now want to be able to deliver ROI, and you have to make some bets. You've got to choose some areas. For us in applied AI, Customer Engagement Suite has been a great one, because it's a problem that C-level execs can understand."
Learn More:Check out details about Customer Engagement Suite, and follow Duncan Lennox on LinkedIn.
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Erwan Menard is the director of product management for Google Cloud’s Cloud AI division, where he helps lead innovation at the intersection of AI agents, enterprise systems, and business outcomes. In part two of our series, Google Cloud and the AI Revolution, Erwan joins Bob Evans to discuss how governance, intentionality, and rapid scaling are critical to AI agent success, share insights on Google Cloud’s Agentspace and Agent Builder tools, and explore how multi-agent collaboration is reshaping the future of enterprise technology.
Purpose Driven AI Innovation
The Big Themes:
Intentionality Drives Impact: Menard advises organizations not to jump into AI agent development for novelty’s sake, but to begin with a clearly defined problem and desired business outcome. However, once value is proven, it's crucial to scale intentionally. He shares the example of a customer rolling out 40,000 licenses of Agentspace only after deeply considering what kind of first experience they wanted their employees to have.Organizational Culture Shapes AI Adoption: There's no universal model for who should “own” AI governance. It depends on the company’s culture. Some companies may create centralized AI governance teams; others may embed responsibilities within existing business units or IT teams. The key is cultural acknowledgment: governance must be understood as a shared responsibility, not just an operational afterthought.Anchor in Business Value: With so many tools, models, and frameworks emerging, it’s easy for companies to fall into what he calls “optionality evaluation.” That is, spending so much time chasing the latest innovations that they lose sight of why they started exploring AI in the first place. Instead, he urges leaders to ask: What are we trying to improve? Whether it’s speeding up contract workflows, freeing up data scientists from routine tasks, or enhancing customer service, the goal should be clear.The Big Quote: "If you find yourself in a constant evaluation loop for the new shiny object, maybe it's worth taking a pause and saying, 'Why are we doing this again?'"
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At Google Cloud Next 2025, Google Cloud VP and CTO Will Grannis joins Bob Evans to explore how AI is reshaping enterprise technology. Grannis shares how Google Cloud’s OCTO team works with customers on complex challenges, using DeepMind research, next-gen TPUs, and AI-native infrastructure, while noting the fading line between B2B and B2C and the cultural changes needed to adapt.
Inside Google Cloud’s AI Strategy
Google Cloud Is AI-Native at Its Core: Grannis says that Google Cloud’s approach to AI is foundational. The organization’s mindset, shaped by Google’s long-standing leadership in AI, infuses every layer of its stack, from infrastructure to user interfaces. With a legacy of deploying machine learning at scale for over a decade, Google Cloud doesn’t just offer AI tools—it helps customers reimagine their businesses through AI-native thinking, using products like DeepMind and innovations born across Google’s consumer ecosystem.The OCTO Team Solves the Hardest Problems with Customers: Grannis leads the Office of the CTO (OCTO), a team he jokingly calls “the nerdy Navy SEALs.” They tackle highly complex, unsolved customer challenges that can’t be addressed by existing products. Rather than building solutions in isolation, they co-create alongside customers. They start with business outcomes and design backward.Multi-Modality and Multi-Agent Systems Are the Future: Looking ahead, Grannis predicts that multi-modal AI, i.e. models that process images, text, speech, and even scent, will become the standard. He also foresees a shift from single-function agents to “agentic workflows” powered by multiple orchestrated AI agents. Google is prototyping orchestration with projects like Astra, that signal a future where AI is not only intelligent but contextually aware and collaborative.The Big Quote: “People . . . spend a lot of time just trying to take a PDF and analyze it. It seems very true. It is a pain . . I think that’s one reason why a NotebookLM or a product like that has been so popular because it really attacks like the heart of what people hate doing at work. [AI] puts them in the driver’s seat. They can ask questions, they can do analysis.”
Learn more:
Check out OCTO, NotebookLM, and Google Cloud.
Visit Cloud Wars for more.
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Inside SAP Business Network
The Big Themes:
New Organizational Structure: SAP reorganized its internal teams by combining Business Network and Digital Supply Chain into a new unit: Supply Chain Management. While this may sound like internal restructuring, Tony Harris explained that for customers, it signals a major innovation push. A major focus in 2025 will be on supply chain orchestration and supply chain risk — two areas that demand real-time responsiveness and cross-functional collaboration.SAP Business Network as a Response to Tariffs and Disruption: With the rise of geopolitical tensions, trade wars, and tariffs, companies need to rapidly adjust their supplier bases. SAP Business Network helps companies respond to such disruptions. If tariffs threaten certain international suppliers, businesses can use SAP Business Network to quickly identify alternative suppliers in unaffected regions or within domestic markets.Introducing SAP Business Network Promote Subscription: On the very day of the interview, SAP launched a new subscription service called SAP Business Network Promote, designed specifically for suppliers. This offering helps vendors raise their visibility and connect with global buyers on SAP Business Network. Features include enhanced and verified company profiles, uploading of full product catalogs, and access to AI-powered tools for responding to requests for information (RFIs), improving content, and correcting invoice errors. Suppliers also receive robust data insights.Visit Cloud Wars for more.
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Episode 50 | AI Agents in Action
The Big Themes:
The Rise of 'Agent Ratios': As companies roll out more AI agents, the "agent-to-human ratio" could become a useful AI maturity indicator. Currently, we’re seeing early adoption — with Oracle reporting that only 5–10% of its customers have put agents into production. These early use cases focus on low-risk, easily-automated tasks. It’s a cautious start, but the trajectory is upward. Bonnie points out that once the groundwork is laid, the pace of adoption will likely accelerate, yielding increased productivity.Four Smart Questions for Evaluating Enterprise AI Initiatives: To help customers decide whether to adopt AI capabilities, Bonnie offers four key questions: (1) Is it available to me? Not all customers have access to AI features; infrastructure matters. (2) Do I need or want it? Weigh the risk-reward tradeoff, especially in terms of time and internal resources. (3) Is my data protected? Ensure your vendor offers strong governance and compliance support. (4) What is the time to value?Knowing When to Leap and When to Wait on AI Adoption: Should companies wait or dive into AI now? Her advice: it depends. If your organization is in a fast-moving, innovation-driven sector, early adoption is essential to stay competitive. Waiting could mean falling behind. But for highly regulated industries or companies unused to rapid tech change, a cautious approach makes sense.Visit Cloud Wars for more.
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Intelligent Spend's Power
The Big Themes:
Enhancing Supply Chain Collaboration and Visibility: Traditional ERP systems, while efficient in automating internal procurement and supply chain processes, are typically confined within the organization's boundaries, leading to disconnects when interacting with suppliers, manufacturers, or carriers. SAP Business Network addresses these challenges by extending end-to-end automation beyond organizational walls. As a result, organizations can build resilient, agile supply chains.Driving Tangible Business Outcomes and ROI: Organizations utilizing SAP Business Network experience improvements in operational metrics. Companies have accelerated order delivery by 27% and increased go-to-market speed by 30%. A pharmaceutical company reduced safety stock by nearly 50% due to improved supply chain visibility, while Richmond International, a luxury goods producer, achieved an 82% digitization of purchase orders and cut warehouse receiving efforts by half.Leveraging AI and Innovation for Supply Chain Resilience: SAP Business Network empowers organizations to build resilient, adaptive supply chains through innovative technologies and AI-driven insights. By providing visibility not only into direct (tier one) suppliers but also into deeper supply chain tiers (tier two and beyond), the network enables proactive risk management and operational agility. Additionally, SAP’s strategic focus on becoming an AI-first company ensures continuous innovation.The Big Quote: “SAP Business Network was designed to modernize how companies connect with their trading partners, leveraging AI and configurable business rules to enable seamless transaction exchanges by integrating directly with the back-end systems. SAP Business Network digitizes interactions that previously relied on manual emails, one-off portals and hence we're able to streamline processes and reduce inefficiencies."
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The Big Themes:
AI and Humans Working Together: Salesforce envisions a future where AI and humans collaborate rather than compete. Rather than replacing human jobs entirely, AI is seen as a tool that enhances human productivity by handling repetitive tasks, improving decision-making, and streamlining workflows. Salesforce’s AI-driven offerings, like Agentforce, are designed to integrate seamlessly with existing systems to empower employees.Rapid Adoption of AI Agents: At Dreamforce, Salesforce onboarded over 10,000 companies onto Agentforce in just three days, demonstrating the speed at which AI adoption is occurring. This large-scale deployment suggests that businesses are eager to implement AI-powered solutions that can immediately improve efficiency. Unlike traditional software rollouts, which can take months or even years, Salesforce’s AI systems can be integrated within minutes, allowing companies to see immediate benefits.AI’s Future Includes Robotics: Salesforce anticipates that AI will soon extend beyond digital applications and into robotics, enabling automation in physical environments. AI-powered robots could be deployed in manufacturing, logistics, field service, and even household tasks. For instance, AI agents could be embedded in robotic systems that perform maintenance, deliver goods, or assist with healthcare services.The Big Quote: "Our CEO, Mark Benioff, kind of kidded around in Davos to a room full of CEOs saying, 'Congratulations, you're the last CEOs who ever managed an entirely human workforce . . . the punch line is, going forward, there's going to be AI and humans working together to help customers on every company around the world."
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The Big Themes:
Rapid Evolution in Enterprise AI & Cloud Technologies: The pace of AI-driven change in enterprise software is accelerating, making it essential for companies to keep up with frequent updates and enhancements. Major vendors like SAP, Workday, and Oracle are rapidly evolving their AI capabilities, offering new tools and features to meet growing business demands. Companies that fail to adapt risk falling behind as competitors leverage AI for efficiency and innovation.The Databricks Breakup Prediction Example: A compelling illustration of AI’s potential came from Databricks’ origin story: an attempt to predict relationship breakups based on digital footprints. There's a fundamental AI challenge — single-source data (e.g. judging only by a single social media page in the breakup predication example) is insufficient for accurate predictions. Instead, AI requires comprehensive, multi-source data aggregation to generate meaningful insights. This principle is now applied in enterprise software.The Growing Importance of AI-Powered Business Suites: A key takeaway from recent developments is the increasing importance of AI-first, suite-first strategies. SAP, Workday, and Oracle are all prioritizing integrated AI across their application ecosystems, making AI a core component rather than a peripheral feature. This shift reflects growing customer demand for intelligent automation, predictive analytics, and enhanced decision-making across business functions.Visit Cloud Wars for more.
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Validated Partner Status Enhances Client Confidence and Outcomes: Infosys' achievement of becoming an SAP-validated partner for RISE with SAP ensures that Infosys provides a predictable, standardized, and scalable approach to cloud ERP transformations. Clients gain clarity on transition strategies, enabling them to adopt clean core principles and maintain differentiation in their business processes. This rigorous partnership offers assurance about time, cost, and risk in transformation projects.AI-Driven Solutions and Industry-Specific Playbooks Add Value: Infosys leverages AI-first approaches and solutions, such as Infosys Cobalt and Topaz, to drive client transformations. By focusing on industry-specific playbooks and workflows, Infosys reimagines business processes, such as order-to-cash, with AI-driven efficiency. The use of 40+ AI-infused accelerators enables rapid adoption and delivers measurable benefits, like enhanced customer satisfaction and reduced errors.The Critical Role of SAP’s Business Technology Platform (BTP): SAP’s BTP plays a vital role in helping clients maintain clean core principles while allowing unique business workflows to operate independently. Infosys supports this transition by building customer-specific solutions on SAP BTP. For example, an electric utility company reduced billing errors by 30% and enhanced customer satisfaction through predictive insights enabled by Infosys’ intelligent customer insights solution built on BTP.
The Big Quote: “We are leveraging AI for the cloud ERP implementation by embedding AI in the various services we deliver to clients, whether it is code generation, whether it is knowledge acquisition, whether it is using more nuanced industry solutions . . . so that it is leading to improved quality, higher productivity and accelerated timeline for execution."
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Salesforce's Excitement for 2025 and the Role of Agents (01:04)
Benioff shares his enthusiasm for the current technological moment. He explains that agents will help businesses operate at lower costs and improve key performance indicators (KPIs). Agents are being rapidly adopted, with Salesforce deploying its agent platform at scale and significantly reducing the workload on human support agents. "We are in an opportunity, I think, for all of our customers, to connect with their customers in this incredible new way that we call agentics or agents . . . we're witnessing something I think, that we've only seen in the movies."
Salesforce's Market Position and Digital Labor (02:35)
Salesforce is the second largest software company in the world, with a $38 billion market cap and $12.9 billion in cash flow. "I think we're one of the first enterprise software companies to deliver an agentic platform at scale with the level of performance and capability that everybody wants." Its platform, Customer 360, integrates various products, creating a comprehensive solution. It's well-positioned to address the issue of digital labor, which has the potential to transform businesses. Benioff says there's a multi-trillion-dollar total addressable market (TAM) for digital labor.
The Importance of Data and AI in Salesforce's Strategy (10:30)
Benioff outlines three core initiatives at Salesforce over the past 24 months: integrating acquired apps into the core platform, developing a high-performing data cloud, and enhancing the agentic layer. He discusses the importance of a unified data model and the integration of the data cloud with Salesforce's apps. AI and machine learning have made many advancements in recent years and while AI is not yet perfect, it has significantly improved over the past decade.
Salesforce’s Core Values and Commitment to Partnership (15:29)
Salesforce’s core values — trust, customer success, innovation, equality, and sustainability — have remained unchanged for 25 years. As Salesforce moves into new technological frontiers, including AI, Benioff stresses the importance of transparency, communication, and collaboration. "We are moving into a new world together, and we're going to be better together." He reaffirms Salesforce’s dedication to working closely with customers and welcomes them into the future of innovation and technology.
The Role of Agents in Enhancing Human Potential (17:11)
Benioff discusses the potential of agents to enhance human capabilities, citing examples from Disney and Gucci where AI has improved employee performance and customer satisfaction. "We also saw that in Gucci, for one of the call centers where we deployed this technology, revenue [rose] 35% because the agents were just making those employees just better." He touches upon the need for rebalancing roles within the company as AI takes over certain tasks, ensuring that employees are continuously skill-building and evolving.
The Future of Agents and Applications (20:50)
He addresses the misconception that traditional databases and applications will be entirely replaced by voice-driven AI interfaces, like those depicted in the movie Her. He explains that AI models are not data storage systems but intelligence engines that augment and extend existing capabilities. While AI is evolving rapidly, Benioff says that current enterprise systems still rely on databases, applications, and workflows. He clarifies that AI will complement these systems rather than replace them entirely.
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