Results

Fix Your Blindspots. Unleash RevOps. Scale Smarter. | DisrupTV Ep. 415

Fix Your Blindspots. Unleash RevOps. Scale Smarter. | DisrupTV Ep. 415

R "Ray" Wang
Principal Analyst and Founder
Constellation Research

R “Ray” Wang is the CEO of Silicon Valley-based Constellation Research Inc. He co-hosts DisrupTV, a weekly enterprise tech and leadership webcast that averages 50,000 views per episode and blogs at www.raywang.org. His ground-breaking best-selling book on digital transformation, Disrupting Digital Business, was published by Harvard Business Review Press in 2015. Ray's new book about Digital Giants and the future of business, titled, Everybody Wants to Rule The World was released in July 2021. Wang is well-quoted and frequently interviewed by media outlets such as the Wall Street Journal, Fox Business, CNBC, Yahoo Finance, Cheddar, and Bloomberg. Short Bio R “Ray” Wang (pronounced WAHNG) is the Founder, Chairman, and Principal Analyst of Silicon Valley-based Constellation Research Inc. He…...

Read more
Elle DeRosa
Director of Marketing, Communications & Operations
Constellation Research

Elle is the Director of Marketing at Constellation Research and producer of the weekly enterprise tech show, DisrupTV. She leads marketing and communications efforts across all avenues while also managing an array of programs including the SuperNova Awards, Business Transformation 150, AX100, AI150, S50 and ShortLists. She has previous experience in public relations and has a strong passion for the marketing world. Contact Elle at [email protected] ...

Read more

Fix Your Blindspots. Unleash RevOps. Scale Smarter. | DisrupTV Ep. 415

This week on DisrupTV, R "Ray" Wang and Vala Afshar caught up with innovators shaping the next chapter of business and technology:

  • Amy Osmond Cook, PhD, and Ryan Westwood, Co-authors of The RevOps Advantage: How To Maximize Your Revenue Team’s Potential
  • Marty Dubin, Author of Blindspotting: How to See What’s Holding You Back as a Leader

In this episode, we dive into The RevOps Advantage, and uncover how aligning revenue operations can turn chaos into clarity. Our guests break down why RevOps is every company’s “pit crew,” how it helps organizations adopt AI strategically, and what leaders can do to eliminate the blindspots holding their teams back.

We explore the FACTOR framework, leadership awareness, and how RevOps as a mindset drives real growth in times of change. Whether you’re a CEO, RevOps pro, or just trying to run smarter, this episode will help you see what’s been hiding in plain sight.

The Role of RevOps in Business Success

Amy Osmond Cook, a seasoned marketing, revenue operations, and communications executive, emphasizes that RevOps is not just a back-office function—it’s a business growth engine. When implemented correctly, RevOps aligns marketing, sales, and customer success around a shared view of data, enabling faster decision-making and more scalable growth.

Ryan Westwood, a tech entrepreneur and board director, adds that CEOs must commit to collaboration, transparency, and data centralization to make RevOps effective. When leadership prioritizes RevOps, silos are removed, and data becomes the backbone of growth strategy.

Bala Baskaran notes that alignment and transparency are critical to unlocking AI’s potential within organizations. RevOps helps businesses harness automation while maintaining the right level of human oversight—ensuring decisions remain strategic and empathetic.

AI, Data, and Automation: The RevOps Accelerator

AI’s integration into RevOps has transformed how companies operate. The panel discusses how AI-powered analytics, predictive modeling, and data enrichment can help leaders make smarter, faster decisions.

However, the challenge of data hygiene remains front and center. Businesses often struggle to keep information current and relevant—a barrier that technology must continue to solve.

The recent acquisition of Copy.ai was highlighted as a milestone moment for the ecosystem, adding deeper automation and intelligence capabilities to RevOps platforms. As Bala notes, “the next phase of RevOps is about intelligent alignment—connecting data, decisions, and human insight.”

Building a World-Class Revenue Operations Function

The group agrees that a world-class RevOps organization requires more than just software—it requires a CEO who believes in it.

RevOps leaders are increasingly reporting directly to the CEO, reflecting the function’s growing influence in shaping strategy, optimizing performance, and improving customer experiences.

For RevOps to succeed at scale, leaders must build teams grounded in trust, radical transparency, and accountability, ensuring alignment across departments and functions.

Leadership Blind Spots and the Path to Self-Awareness

The conversation transitions as Marty Belden joins to discuss his book Blind Spotting—a framework designed to help leaders uncover the blind spots that limit performance and growth.

Drawing on his experience as a psychotherapist and executive coach, Marty outlines six key blind spots that can derail leadership effectiveness, including emotional biases, flawed assumptions, and identity misalignment.

He explains that even high-performing CEOs can suffer from blind spots when they fail to see how their self-perception differs from others’ experiences of them. These gaps can lead to poor communication, resistance to change, and missed opportunities for innovation.

  • “Self-awareness isn’t a soft skill—it’s a leadership discipline,” Marty explains. “You can train it through science, structure, and consistent feedback.”

Identity, Imposter Syndrome, and Growth

The discussion touches on imposter syndrome, a common blind spot among accomplished leaders. Even successful CEOs can feel undeserving of their achievements, leading to overcompensation or self-doubt.

The key to overcoming these challenges lies in acknowledging personal blind spots, seeking feedback, and consciously aligning one’s identity with evolving leadership roles.

One speaker notes that leadership transformation often begins with humility—being open to small, consistent changes that compound into lasting behavioral growth.

Belonging, Curiosity, and Listening in Leadership

The panel emphasizes that effective leadership isn’t about having all the answers—it’s about creating space for others to contribute.

Leaders who ask thoughtful questions, reflect before reacting, and foster belonging build teams that feel valued and heard. This emotional connection drives innovation and retention far more effectively than command-and-control leadership.

As R "Ray" Wang closes, he reminds listeners that self-awareness and curiosity are foundational to leading in an age of rapid technological change. Science-backed methods, coaching, and reflection help leaders stay adaptive as they scale businesses in an AI-driven world.

Key Takeaways

  • RevOps drives alignment and scalability by centralizing data and promoting cross-functional transparency.
  • AI amplifies RevOps through automation and analytics—but human judgment remains critical.
  • Data hygiene is essential for AI-driven organizations; clean, enriched data powers better decisions.
  • Blind spots hinder leadership effectiveness, but self-awareness can be developed through feedback and reflection.
  • Leaders must align identity with evolving roles to maintain authenticity and confidence.
  • Curiosity and belonging are the new cornerstones of modern leadership.

Final Thoughts

DisrupTV Episode 415 highlights a powerful truth: scalable growth in the modern enterprise is driven by alignment, self-awareness, and intelligent technology.

Revenue Operations is no longer a niche discipline—it’s the central nervous system of every data-driven organization. And as AI reshapes how we work, the most successful leaders will be those who remain human at the core—curious, self-aware, and committed to transparency.

In the end, business transformation isn’t just about systems or automation. It’s about leaders who can see their blind spots, empower their teams, and build cultures where data, empathy, and innovation thrive together.

Related Episodes

If you found Episode 415 valuable, here are a few others that align in theme or extend similar conversations:

 

Future of Work Marketing Transformation New C-Suite Tech Optimization Chief Executive Officer Chief People Officer Chief Marketing Officer Chief Revenue Officer Chief Technology Officer
On DisrupTV <iframe width="560" height="315" src="https://www.youtube.com/embed/3Zt0L8jB7Dc?si=a2PMDztrlVbQyWLo" 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>

Oracle AI World 2025: Shifting left AND right into Oracle’s suite spot

Oracle AI World 2025: Shifting left AND right into Oracle’s suite spot

Michael Ni
Vice President and Principal Analyst
Constellation Research

Michael Ni is Vice President and Principal Analyst at Constellation Research, covering the evolving Data-to-Decisions landscape—where CDOs, CIOs, and CPOs must modernize data infrastructure, integrate AI into decision-making, and scale automation to improve business outcomes. Ni’s research examines how enterprises operationalize AI, automate decision-making, and integrate data management and analytics into core business processes. He focuses on the challenges of scaling AI-driven decision systems, aligning data strategy with business goals, and the growing role of data and decisioning “products” in enterprise ecosystems. With 25+ years as a product and GTM executive across enterprise software, AI platforms, and analytics-driven technologies, Ni brings a practitioner’s perspective to…...

Read more

We’re no longer in the “let’s try a model” era. We’ve crossed into the territory of “make the model do your work.” For Oracle, that’s exactly where AI World 2025 landed.

This week, Oracle went beyond unveiling products by doubling down on its brand promise: reduce complexity so enterprises don’t have to stitch the stack. It’s a shift from experimentation to embedding, from model tuning to decision automation.

Why This Matters to CDAOs and AI Leaders

Let’s be real: most data and AI teams are buried under too many tools, too many silos, and too much governance debt. The promise of AI is huge … but but but the complexity of getting there is overwhelming for even the enterprise fast-followers.

That’s why this move from Oracle hits a nerve. The company’s DNA has always been about centralizing complexity -> integrating the dominant innovations/design of the moment so enterprises don’t have to stitch them together. The promise is engineered together + removing abstractions = performance, manageability, and extensibility. 

Let's look at some of key announcements.

Data Foundation Layer: From Data Silos to Self-Governing Intelligence

Oracle’s Lakehouse isn’t a new product, it’s the convergence of several mature ones:

  • Autonomous AI Lakehouse: Oracle merges its Autonomous Database with Iceberg support, offering query acceleration, multicloud availability (OCI, AWS, Azure, Google), and zero-ETL / zero-copy flows.
  • A “catalog of catalogs” for unified governance of data and model assets across environments.
  • AI Database 26ai: enhancements include vector/hybrid search, support for Model Context Protocol (MCP), built-in “AI Private Agent Factory,” and open agent interoperability.

Think of it as Oracle teaching its database to govern itself across clouds, formats, and workloads.

For data teams, that means fewer pipelines across silos to manage. For CDAOs, it means centralized metadata governance, policy management, and context-rich retrieval for RAG and reasoning agents. Tradeoffs of buying into the Oracle governance and architectural choices always to be considered.

Intelligence Layer: From Insights to Agents

Then came the bigger reveal … 

  • Oracle AI Data Platform: blends Oracle’s cloud, database, and GenAI services into one environment for a full-stack environment uniting data, AI frameworks, and agent lifecycle management. Don't move data to the AI, but move AI to the data (for Oracle, in the DB, of course)!
  • Built-in Agent Studio/Agent Hub providing a developer workbench and business-user cockpit for building, orchestrating, and governing AI agents. The Agent Studio is importantly expanding observability, lineage, evals, human-machine interface controls, and policy enforcement across data and models.
  • Fusion Data Intelligence / Embedded Agents: Oracle embeds reasoning into finance, HR, supply chain apps.
  • … all supported by expanded partner commitments with Global SIs (Accenture, Cognizant, PwC) pledging over $1.5B in investment in capabilities and industry use case building.

This isn’t just about running models. It’s about running the business with AI. TK Anand reiterated Larry Ellison’s point around Oracle’s advantage of “bringing your enterprise data and foundation models together to build agentic experiences.” Implication = enterprises need to play the long game, where value is captured by models that reason over private, proprietary data in context, in real time, and absolutely inside enterprises. 

The Bigger Shift: Start of Decision Automation era

This year marks a turning point: The good: We’re climbing the next S-curve of enterprise AI adoption and moving intelligence into the enterprise. The not so good: most enterprises are still on the last S-curve of moving data and apps to the cloud.

For CDAOs, what will define who wins this next wave? You are already seeing vendor innovation around the next area of innovation.

  • Governance becomes a differentiator. Trust will separate pilots from platforms. Those who can convincingly deliver reasoning without sacrificing privacy or performance will capture the gatekeeper role in the enterprise AI stack.
  • Context, context, context. The winners will be those who can ground every model, prompt, and agent in a business context — connecting metadata, semantics, and decision logic so AI acts with understanding, not hallucination. Context is how insight becomes action, how automation earns trust, and how data turns into decisions.
  • Decision-centric architecture takes center stage. We’re moving from shared data to contextualized intelligence, from dashboards to decisions, from human control to adaptive collaboration and decision automation.

I’ll be writing more in the coming month on the rise of the decision-centric architecture, how it is forming, and what it means for CDAOs designing for the next decade of AI.

What do you think? Will enterprises favor vertically integrated stacks or open, federated ecosystems? Which domain (HR, supply chain, customer, finance) is your “first agentic battleground”? How will you measure decision velocity in your organization?

Drop your thoughts below 👇 — let’s debate where the next S-curve leads.

#OracleAIWorld #DecisionVelocity #CDAO #DataToDecision #AgenticAI #AIInfrastructure #Analytics #ConstellationResearch

New C-Suite Data to Decisions Tech Optimization Oracle Chief Information Officer Chief Analytics Officer Chief Data Officer Chief Technology Officer

7 takeaways on enterprise AI projects from Infosys, Wipro Q2 results

7 takeaways on enterprise AI projects from Infosys, Wipro Q2 results

Larry Dignan
Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

Infosys and Wipro executives said that enterprises are starting to operationalize artificial intelligence projects, scale agentic AI and build a new software stack as pilots move to production with industries such as banking and financial services leading the way.

Those were the highlights from a pair of earnings reports from the Indian services firms that landed within minutes of each other. Infosys reported second quarter earnings of $839 million on revenue of $5.08 billion, up 2.9% from a year ago. Wipro reported second quarter earnings of $368 million on revenue of $2.56 billion, up nearly 2% from a year ago.

Earnings results from services firms are a handy way to get a high level view of what's happening with AI efforts. Both Infosys and Wipro provided color on AI implementations, but the former delivered named references including ABN Amro, Mastercard, Telstra, HanesBrands and Agco Corp.

Here's a look at the takeaways from the Infosys and Wipro results.

Enterprise AI is being scaled by customers.

Infosys CEO Salil Parekh said that "client interactions show strong focus on deploying AI across the enterprise for growth and on cost efficiency programs." He said clients are leveraging Infosys' platforms for AI agents and AI overall.

Wipro CEO Srinivas Pallia said customers are prioritizing cost optimization, vendor consolidation, modernization and scaling AI agents.

On the delivery side, both companies said they are leveraging AI agents more.

AI-driven productivity pays the bills, but growth matters too.

Across industries, AI investments are justified based on cost savings, but customer experience and growth is becoming a bigger part of the ROI mix. Infosys CFO Jayesh Sanghrajka said:

"Clients are actively planning modernization and AI-driven initiatives with a clear focus on cost efficiency, enhanced customer experience and strategic transformation."

Pallia said Wipro's customers are "clearly looking for cost optimization."

The broader theme for both companies is that enterprises aren't into AI pilots as much as they are business outcomes.

Can you monetize trust?

Questions from analysts around agentic AI and automation frameworks often revolved around accuracy and hallucinations. What happens if an AI agent goes rogue?

Both companies highlighted guardrails, years of experience automating processes and industry knowhow. Wipro's Hari Shetty, chief strategist, said Wipro Intelligence is a layer for responsible AI guardrails built into the platform.

Meanwhile, Infosys Chief Delivery Officer Satish H.C. said: "Our Responsible AI office ensures clients have the defense and technical guardrails to address AI-related risks. We are among the first certified on ISO 42001:2023."

The questions were notable since they raised more queries. Can Indian IT giants monetize trust in AI? And are vendors on the hook if AI agents wind up hurting a client's business?

Banking, financial services and insurance lead AI spending.

The fact that financial companies lead the way on AI spending isn't surprising to anyone keeping tabs on earnings reports. The financial sector is one of the most mature industries for AI adoption. Both Infosys and Wipro noted that financial firms are scaling AI pilots.

Sanghrajka said:

"In financial services, clients are actively planning modernization and AI-driven initiatives with a clear focus on cost efficiency, enhance customer experience and strategic business transformation. We see strong momentum in mortgages, capital markets commercial banking and wealth management areas. Banks have spent significantly to build AI infrastructure. Many initiatives are progressing from proof of concepts to full-scale projects with notable traction in Agentic AI."

Healthcare transformation

Healthcare was cited as a strong vertical. Infosys cited strength in healthcare with clients deploying AI and automation. Wipro's Pallia cited a mega deal with a healthcare client. Palia noted:

  • Healthcare is going through structural changes and companies are navigating various policy changes.
  • Payers are trying to accelerate and transform contact centers.
  • Wipro healthcare clients are looking for real-time claim processing, efficiencies in pre-authorization and enhanced transparency.

Healthcare was Wipro's best vertical in the second quarter with revenue growth of 3.9%.

Manufacturing and energy mixed.

Infosys' Sanghrajka said manufacturing "continues to face trade and macro uncertainties, which is creating pressure on discretionary spend specifically in the automotive sector."

However, Sanghrajka said manufacturers are spending on the following:

  • Application and infrastructure rationalization.
  • Leveraging AI for automation.
  • Predictive maintenance.
  • Resolving supply chain bottlenecks.

As for energy, Sanghrajka said utilities are trying to leverage new technologies to meet data center demand. "Utility companies are looking for partners to meet the accelerating electricity demand, creating opportunities in areas like renewable integration, grid modernization, AI-driven optimization, et cetera," he said.

Industries are aiming AI spend at specific issues. Telecom, technology and communication are focused on using AI for customer experience, but cost optimization remains critical. Retailers are also mixed as they wrestle with tariffs and consumer demand.

The new AI stack

Other nuggets worth noting include:

  • Infosys and Wipro both said that big deals are signed due to vendor consolidation plans. Enterprises are looking for end-to-end services and horizontal plays.
  • That vendor consolidation is leading to large scale generative AI and agentic AI deployments.
  • Forward deployed engineers are being used for AI transformation deals.
  • Indian IT services firms are increasingly developing AI stacks for enterprises instead of deploying packaged applications. Infosys' Satish HC said:

"The opportunity with AI is that we are developing a new breed of services stack or software stack for our clients, which wasn't done before. This is a reimagining how we run business or how we even deliver services. The onus is on co-creation with our clients, which is why I think there is a sharper pivot to the leverage of forward-deployed engineers. As we move from POCs to enterprise scale adoption, we see that there will be a lot more need for forward-deployed engineers to work with our clients to drive this co-creation of the new breed of software stack."

 

Data to Decisions Chief Information Officer

Zoho details Indian government migration, expands roster of AI agents

Zoho details Indian government migration, expands roster of AI agents

Larry Dignan
Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

Zoho has moved 1.1 million Government of India users to Zoho Workplace in a move that highlights how the vendor, known for its disruptive pricing and reach with smaller enterprises, can scale.

In addition, Zoho, which has more than 130 million users, rolled out a series of AI agents for its collaboration, human resources and customer experience apps across its platform.

Regarding the India government migration, Zoho Chief Evangelist Raju Vegesna said during a briefing that the 1.1 million users is just the first installment of the migration. "There are a few other million users coming," said Vegesna. "It's an ongoing process."

Zoho said India's National Informatics Center (NIC) asked for proposals in 2023 to shift collaboration services to a dedicated, secure environment. Zoho was selected to manage and migrate official email and office suite services.

The custom rebranded version of Zoho Workspace will be available for government departments for email, files, documents and communications. India's government is specifically using Zoho Mail, WorkDrive, Meeting, Cliq, Mobile Device Management, Writer, Sheet and Show, OneAuth and Contacts.

Zoho's apps are hosted in a secure data center under NIC's control and includes a complete cybersecurity stack.

As for the agentic AI additions, Zoho said its latest AI agents will be available at no charge across Zoho Collaboration, Customer Experience and Human Resources.

The AI agents from Zoho are a fast follow from the launch of Zia Hubs and Zia LLM, its proprietary B2B model.

Among the agents launching:

  • Lead Generation Agent works across Zoho Mail and CRM to go through unread messages, identify sales queries and converts them into a lead in Zoho CRM.
  • AI Base Creation enables customers to create a use case with a prompt. Zia will create a base with relevant tables, sample data and linked fields. The agent works within Zoho Tables.
  • Resolution Expert, which works within Zoho Desk, documents ticket resolutions for other agents to resolve similar issues.

  • Agreement Intelligence, which is used in Zoho Sign, generates drafts of contracts, agreements and documents.
  • HR agents in Zoho Recruit include Candidate Matches, Job Matches and AI-Assisted Assessment Generation.

Philip Edey, Business Analyst at Arctic Spas Inc., said in a briefing that Zoho's AI tools are enabling the company to scale and manage nearly 1,000 leads a week, up from 300 leads. Edey said:

"Integrating AI and agentic systems into our workflow is key for the next six months to the year and going forward. With 14 corporate stores and a huge network of dealers, we want to try to make these tools work for us and work for our staff to make it a better user experience. Zoho's AI driven suite can help us get there."

Vegesna said Zoho is rolling out agents and new Zia capabilities. The approach is "to open it up to a limited set of people, and as we gain feedback, refine it," said Vegesna, who noted cybersecurity is a key area.

Data to Decisions Future of Work Next-Generation Customer Experience Innovation & Product-led Growth Tech Optimization Digital Safety, Privacy & Cybersecurity New C-Suite Marketing Transformation I am Team Leader at the Nominee Organization (no vendor self nominations) Distillation Aftershots zoho 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 Information Officer Chief Executive Officer Chief Technology Officer Chief AI Officer Chief Data Officer Chief Analytics Officer Chief Information Security Officer Chief Product Officer

Salesforce, Google comingle Agentforce 360, Gemini models

Salesforce, Google comingle Agentforce 360, Gemini models

Larry Dignan
Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

Salesforce and Google expanded their existing partnership in a move that brings Google Gemini models to Agentforce 360, integrates Agentforce into Google Workspace for sales and IT service and brings Gemini Enterprise to Slack.

The addition of Gemini to Salesforce's Agentforce 360's Atlas Reasoning Engine goes along with support for models from OpenAI and Anthropic.

Google Cloud announced Gemini Enterprise ahead of Dreamforce and joint customers are likely to endorse the connections between Agentforce 360 as they stitch together AI agents.

Dreamforce 2025

Key parts of the Salesforce-Google expanded partnership include:

  • Gemini users can deploy AI agents in Salesforce for multistep enterprise workflows.
  • Salesforce and Google will expand capabilities in large action models, which automate processes, with fine-tuned Gemini models.
  • The AI agents on the respective platforms will be tied together via Model Context Protocol (MCP) and Agent2Agent (A2A).
  • Users can access Salesforce Customer 360 apps like Agentforce Sales and Agentforce Service from Google Workspace apps like Gmail and Meet.
  • Salesforce customers can access and view data and insights across the Gemini app and Workplace tools such as Sheets, Docs, Drive and Meet.
  • Agentforce IT Service will have integrations with Google products including Workspace, ChromeOS and Looker.
  • Gemini Enterprise will be integrated into Slack's Real-Time Search API. Gemini Enterprise users will be able to ground responses within the most current conversational data and files.
  • Gemini Enterprise agents can be used directly within Slack.
Data to Decisions Future of Work Next-Generation Customer Experience Innovation & Product-led Growth Tech Optimization Digital Safety, Privacy & Cybersecurity Google salesforce 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 Information Officer Chief Executive Officer Chief Technology Officer Chief AI Officer Chief Data Officer Chief Analytics Officer Chief Information Security Officer Chief Product Officer

Salesforce sets $60B revenue target: Will unlimited Agentforce plans drive growth?

Salesforce sets $60B revenue target: Will unlimited Agentforce plans drive growth?

Larry Dignan
Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

Salesforce executives said that growth is reaccelerating due to Agentforce deployments and it is projecting a long-term revenue target of $60 billion by fiscal 2030 excluding the Informatica purchase. The big question is whether new pricing plans designed to meet customers where they are will drive the growth.

The revenue target assumes more than 10% of organic compound annual revenue growth from fiscal 2026 to fiscal 2030. Salesforce also said it aims to have the sum of subscription and support constant currency growth rate and non-GAAP operating margin total 50 by the end of fiscal 2030. Software vendors have typically made the "Rule of 40" as a key metric.

"We are confident in our ability to reach $60-plus billion by FY '30. In addition to that, as you know, we are very focused on profitable growth. One of my key goals as CFO is to deliver Salesforce is not only an agentic enterprise, but a lean agentic enterprise," said Salesforce CFO Robin Washington.

During the Wall Street analyst session, Salesforce executives, notably Chief Revenue Officer Miquel Milano, walked through the pricing and packaging of Agentforce. "We are meeting customers where they are," said Washington, who noted Salesforce is focusing on industries and segments as well as geographies.

Salesforce CEO Marc Benioff said "what we've seen in the last 3 years is that the speed of innovation has outpaced the speed of customer adoption." That situation is changing though.

Benioff said:

"There's only two things that we do. One is building that product. The second thing is now selling it. So now on a global stage, across every geography, every language and across all six of those segments, we have to deliver the goods, and we have to deliver the growth. And we have to get to those -- the numbers are off the screen, but then we're trying to get to these very high numbers."

Pricing matters

Milano outlined an Agentforce pricing strategy that appears to be more flexible to entice enterprises to bet on Agentforce 360 as a platform play. The unlimited plans for Agentforce and Data 360 may give CFOs and CIOs more predictable costs. 

“Customers don’t want to count tokens. They want predictability. The Agentic ELA gives them unlimited use for two or three years,” said Milano.

New monetization models to “meet customers where they are” include:

  • Seat-based editions (e.g., Agentforce for Service/Sales): upgrades existing licenses.
  • Consumption-based credits for flexible AI use.
  • Flex Agreements: reallocate seat spend toward AI consumption.
  • Agentic Enterprise License Agreements (ELAs): flat-fee, unlimited use of Data 360 and Agentforce for predictable costs — already a dozen signed and more than 150 accounts in negotiation.

Milano said:

“CEOs for the most part, they're tired. They're saying I just want to transform. I just want to use AI everywhere. We are clear that there are very few technology vendors that can do this for us. We want Salesforce to do it, but we are worried about the pricing. Predictability of cost was very important for CEOs. So we put together something very simple: Flat fee, unlimited usage of Data Cloud and Agentforce for our customers. They can deploy any use case they want for 2, 3 years. They can ingest as much data as they need for those Agentic use cases.”

Data to Decisions Future of Work Next-Generation Customer Experience Innovation & Product-led Growth Tech Optimization Digital Safety, Privacy & Cybersecurity salesforce 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 Financial Officer Chief Information Officer Chief Technology Officer Chief AI Officer Chief Data Officer Chief Analytics Officer Chief Information Security Officer Chief Product Officer

Snowflake, Palantir forge data integration partnership

Snowflake, Palantir forge data integration partnership

Larry Dignan
Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

Snowflake and Palantir said they will integrate Snowflake AI Data Cloud with Palantir Foundry and Palantir Artificial Intelligence Platform (AIP).

The two companies said the partnership will enable joint customers to build data pipelines, analytics and AI applications faster. Eaton, which is a power management company, is an early customer of the integration.

For Palantir, the company has been rapidly building its ecosystem and partnerships. Systems integrators have also been betting on Palantir's AIP platform. For instance, Accenture acquired Decho, an AI consulting firm focused on scaling Palantir across health and public sector. In July, Deloitte and Palantir announced a partnership.

Snowflake and Palantir said the integration between Foundry and Snowflake Iceberg Tables will lead to bidirectional zero-copy interoperability.

Using Eaton as the example, the customers said the partnership:

  • Will improve customer experience.
  • Connect engineering to manufacturing with supply chain orchestration with agentic AI. That connection should improve inventory, on time delivery and quality.
  • Enhance visibility across Eaton's technical landscape.

Constellation Research analyst Michael Ni said:

"This partnership is a win-win: Palantir gets a scalable data backbone, and Snowflake gains a front-row seat in some of the world’s most mission-critical AI deployments. It’s not just about data storage, but increasingly operationalizing data to decisions, as well as ensuring insights are available across the enterprise.

This announcement isn’t just about helping existing customers. For both, this deal is a land and expand play. Snowflake gains an AI decisioning layer solution partner it didn’t have, and Palantir can now offer unified data, governance, and AI workflows without data duplication. That’s a major productivity and compliance gain that both can offer their customers."

Related:

Data to Decisions snowflake Chief Information Officer

HPE has big AI infrastructure plans that are 'going to take a little bit of time'

HPE has big AI infrastructure plans that are 'going to take a little bit of time'

Larry Dignan
Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

Hewlett Packard Enterprise gave an upbeat presentation on taking networking share and capitalizing on the AI infrastructure buildout, but its fiscal 2026 revenue growth forecast was lower than expected.

At its Security Analyst Meeting, HPE projected fiscal 2026 revenue growth of 5% to 10% and analysts were expecting about 17%. HPE projected adjusted earnings for fiscal 2026 of $2.20 a share to $2.40 a share compared to estimates of $2.42 a share.

HPE also projected a 5% to 7% compound annual revenue growth rate with non-GAAP earnings of at least $3 a share for fiscal 2028. HPE did raise its dividend 10% and announce a $3 billion share repurchase plan.

CEO Antonio Neri emphasized that HPE was focusing on its operating margins and capturing profitable share of AI infrastructure. Neri was joined by Rami Rahim, who gave an overview of the networking plan.

"HPE strategic priorities over the next 3 years are clear. We will build a new networking industry leader, capture AI infrastructure growth profitably, with a focus on sovereign and enterprise customers, accelerate our high-margin software and services growth through our HPE GreenLake Cloud, capitalize on unstructured data market growth with our own IP through Alletra MP Storage and drive customer transition to next-generation server platforms," said Neri.

Neri said the company will deliver annual run rate savings by 2028 of at least $600 million through the Juniper integration and another $350 million from its efforts to optimize efficiency under a program called Catalyst.

"HPE is playing to win in 3 strategic IT markets: networking, cloud and AI, each one serves as an essential building block for modern IT. These markets are all growing at an accelerated pace, driven by advancement in AI and the swift expansion in data center build-outs," said Neri. "We anticipate the overall total addressable market across our portfolio will increase to over $1.1 trillion by fiscal year 2028."

Rahim added that networking will be a critical part of HPE's growth engine for AI infrastructure. "In this new AI era, networking has become mission critical. And as a result, we expect to capture market share in key network product segments that are both large and growing," said Rahim.

Rahim added that HPE's networking business will focus on data center needs for industries, locations, enterprise and AI factories. He said data centers will become more diverse and the era of one-size-fits-all is over.

HPE's presentation was bullish, but the guidance from CFO Marie Myers didn't line up with the expansion plans. Myers explained that HPE is looking to lower its debt load, invest in its products and increase capital returns.

Wall Street analysts weren't thrilled about the outlook, but Neri and Rahim explained that the sales cycles for networking are longer, neo cloud providers are a new market and reference accounts take time.

"We did not bake revenue synergies into 2026 for a specific reason. I have a lot of work in 2026 to integrate 2 businesses together without disrupting any customers. I think I can do that. So we were a bit cautious about expecting too much in that time frame. I think over time, through both commercial and technical integrations, we can see revenue synergies, but that's just going to take a little bit of time," said Rahim.

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

Oracle CTO Larry Ellison on AI use cases for healthcare, agriculture, climate change

Oracle CTO Larry Ellison on AI use cases for healthcare, agriculture, climate change

Larry Dignan
Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

Oracle CTO Larry Ellison is never short of words. In his annual keynote at Oracle's AI World conference (previously Cloud World), Ellison held court for nearly two hours and riffed on a bevy of big AI ideas.

A good chunk of Ellison's talk revolved around talking up Oracle Cloud Infrastructure's plans for a 1.2 billion-Watt AI Brain, which would be Oracle's largest data center with 500,000 Nvidia GPUs. Ellison also touted Oracle AI Data Platform, which will reason on public and private data.

Ellison said Oracle's two biggest opportunities are AI training and AI Reasoning. Private data will enable more valuable models and data will stay private. He added that Oracle databases already contain most of the world's high-value private data.

"The big opportunity in AI training is upon us, and Oracle is a major participant in building data centers to do AI training. But the much, much larger opportunity, the one that will truly change the world, isn't the creation of the models themselves, the training of the models," said Ellison. "What will change the world is when we start using these remarkable electronic brains, and that's what they are. These are remarkable electronic brains to solve humanity's most difficult and enduring problems."

Ellison also noted that AI will also build out its perception game in addition to reasoning. "It's called artificial intelligence as opposed to artificial perception, but it does perceive. It hears it smells. Think about smelling. I mean the idea that you can pick up chemicals that are just drifting around in the atmosphere and figure out what those chemicals are. Dogs can smell cancer in patients," said Ellison. "We should be able to do that with AI, we should be able to. In fact, there's a project I know of called the dog's nose that I'm actually a part of, and we're building sensors. We're building sensors that can smell cancer or other or other illnesses."

According to Ellison, AI players are focusing on two flavors of models. The ones that are most familiar are the reasoning models, but real-time models will be as important. He noted how Google Cloud has Gemini, but physical AI models too. Elon Musk's xAI has Grok, which is a reasoning model, but Tesla represents a real-time model.

Here's a roundup of those problems that AI can solve. Some of these problems are aligned with the Ellison Institute of Technology at Oxford, which is expanding following another £890 million investment from the CTO.

Healthcare

Ellison, which counts Cerner as part of Oracle, is passionate about healthcare. Cerner has leveraged AI to rewrite its code base, but Ellson noted the rebuild also includes retooling accounting and HR systems designed for hospitals. "Hospitals are very unusual," he said.

AI-driven use cases for healthcare include:

AI-powered precision surgery. Ellison described AI robots that surpass human surgical capabilities through superior vision and coordination. For something like cancer removal, AI robots could eliminate some key steps where surgeons remove tissue layers and examine them under a microscope. "AI robots just don't play fair. Their vision is the AI, the vision on the robot and it is microscopic. They don't need a microscope to see individual cells and they can cut between a layer of healthy cells and a layer of cancer cells."

Integrated healthcare workflows. Ellison said there's a big opportunity to automate healthcare workflows. With retrieval-augmented generation (RAG) models can access the latest medical literature, patient test results, and clinical trial information. The AI can identify optimal care while ensuring full insurance reimbursement. That final point is key since you can use AI to predict whether insurance will pay.

Smoothing out hospital cash flow. With better predictions for insurance reimbursement, hospitals will be able to get loans against receivables with a 95% to 99% chance to be reimbursed. Ellison said there could be specialized banks focused on hospitals. "An AI agent can bank all of the information about a particular collection of reimbursements, assuring the bank that those that reimbursements will be adhere to all of the rules," said Ellison. "The clinic and the hospital will be reimbursed. You can discount a little bit, and the bank will then loan on those receivables."

Automating healthcare ecosystems. "If we really want to be successful in health care, we can't just automate hospitals and clinics. We have to automate the entire ecosystem," said Ellison. "You have to automate the pay the patient, the provider, the payer, the regulator, the pharma, companies, banks who finance the hospitals, and governments who regulate the hospitals and collect information from the hospitals. You have to automate the entire ecosystem. You do that and then you will get a truly modern, efficient healthcare system. And that's what we were after when we bought Cerner as a first step."

Ellison said one of the most interesting AI agents built by Oracle connects providers to payers. The agent comes up with the best possible quality of care that is fully reimbursable if the patient can't pay. "The AI model will provide information to doctors as the doctor tries to figure out the best possible care for the patient, then the AI model is also trained on the latest rules and policies. What's the best care and what's fully reimbursable? I have to train the model on all of the insurance rules," said Ellison.

The subtext here is that Ellison could use healthcare automation as a way to talk about layering AI agents throughout its Fusion apps. At Oracle AI World, Oracle outlined the agentic AI efforts in its applications including a marketplace and AI agent studio.

Agriculture, carbon capture and sustainable farming

Ellison said there's a need for "robotic greenhouse systems" and AI driven farming. "We need to produce much more fruit and food than we currently do. We're going to run out of water. We're going to run out of arable land. We can't keep taking habitat and converting it to farmland. We have to be much more efficient," said Ellison. "By growing and by growing in greenhouses and moving plants around, plants only need a lot of room for the few weeks before they're harvested."

Robotic greenhouses will use less water and space. The CO2 footprint would be lower. Ellison said two robotic greenhouses are being built in California and Texas. The building includes a rail system that moves plants from one location to another. No humans are allowed since people contaminate the growing area. The structure is an air pressure building.

"You snap the steel cables onto the footing, and then you turn the fan on, and you inflate the building. You fold the building up. The building is fabric with steel cables. You fold it up and nice, nice, nice packages, and you transport it to where you're building it, or you transport it to Mars on one of those big rockets," said Ellison.

The company behind the robotic greenhouses is Wild Bio, which is part of Ellison's institute at Oxford.

AI-assisted engineering of crops. Ellison said crops can be engineered to remove CO2 from the atmosphere while increasing food production. "We could use our food crops, we could actually increase the food yield while lowering CO2 through a natural process called bio-mineralization," said Ellison. The general idea is to engineer crops to extract nitrogen from the atmosphere via an enzyme called Nitrogenase, naturally found in soybeans.

"Rather than using fertilizer to nourish the plant, the atmosphere has got a huge amount of nitrogen in it. Why don't you simply engineer the plant to take the nitrogen directly out of the atmosphere?" said Ellison.

The engineering of crops would face multiple regulatory and technology challenges as well as the impact on biological systems. Farmers would need new practices and techniques as well as training.

Drones

Forest fire detection and response. Ellison demonstrated autonomous drones equipped with infrared cameras that can "detect forest fires immediately" and even determine if fires were deliberately set.

Medical sample transport. The system includes RFID-tagged specimen vaults that maintain chain of custody while protecting patient privacy. Drones transport blood samples from clinics to testing laboratories, solving logistics challenges while maintaining security. "No one knows this is Larry Ellison's blood. They just know there's an RFID tag on it," said Ellison.

 

Data to Decisions Innovation & Product-led Growth Next-Generation Customer Experience Tech Optimization Future of Work Digital Safety, Privacy & Cybersecurity Oracle 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 Information Officer Chief Executive Officer Chief Technology Officer Chief AI Officer Chief Data Officer Chief Analytics Officer Chief Information Security Officer Chief Product Officer

IBM acquires SAP S/4 HANA services firm Cognitus

IBM acquires SAP S/4 HANA services firm Cognitus

Larry Dignan
Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

IBM said it will acquire SAP S/4 HANA services specialist Cognitus in a deal that will expand its SAP AI-driven industry services.

Terms of the deal weren't disclosed.

According to IBM, Cognitus will bring SAP skills in deploying the RISE and GROW programs with SAP as well as software assets. Cognitus, founded in 2002, offers SAP S/4HANA implementation services as well as application maintenance.

Cognitus, based in Dallas, also has a suite of SAP-endorsed software assets including Cognitus CIS-GovCon to support government contracting, Cognitus CLM for contract management for government, and Cognitus Data Migration, which moves data from legacy systems to SAP S/4HANA. The company also offers Cognitus Real-Time Billing.

SAP customers have picked up the pace with SAP S/4 HANA migrations so they can leverage AI. Cognitus is focused on the SAP transformation project lifecycle with a focus on regulated industries.

Cognitus is focused on the following industries:

  • Aerospace & Defense
  • Engineering, Construction & Operations (EC&O)
  • Utilities
  • Professional Services
  • Manufacturing
  • Consumer Products
  • Wholesale Distribution

IBM said Cognitus will bring deep industry expertise and add to its SAP practice and IBM Consulting Advantage, an AI-driven delivery platform.

 

 

 

Data to Decisions IBM Chief Information Officer
Subscribe to