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AI Hype vs. Human Reality: Why SaaS Isn’t Dying and Healthcare Is Rising | DisrupTV Ep. 434

AI Hype vs. Human Reality: Why SaaS Isn’t Dying and Healthcare Is Rising | DisrupTV Ep. 434

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…...

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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] ...

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Human-Centered AI, Nursing’s Future, and the “Lunatics” Driving Innovation

On DisrupTV Episode 434, hosts R “Ray” Wang and Vala Afshar brought together three distinct perspectives—from healthcare, AI strategy, and enterprise journalism—to explore what actually matters in an AI-driven world.

Featuring Ena Hull (President & CEO, Ultimate Health School), Dr. Michael Wu (Chief AI Strategist, PROS), and Ron Miller (Editor at FastForward), the conversation cut through hype to reveal a clear throughline: AI may scale systems, but humans determine outcomes.

Nursing at a Breaking Point—and a Path Forward

Ena Hull painted a stark picture: nursing is both one of the most stable, AI-resistant careers and one of the most strained.

Demand is surging due to aging populations and post-COVID attrition, yet supply is constrained by faculty shortages, regulatory hurdles, and burnout. The issue isn’t lack of interest—it’s a bottlenecked pipeline.

Her solution: rethink the model.

  • Modernize education: Move from semester-based systems to modular, skills-based, faster pathways.
  • Unlock faculty capacity: Transition experienced (and burned-out) nurses into teaching roles.
  • Leverage simulation: Use AI-driven clinical simulations to reduce reliance on scarce in-person training slots.
  • Design for longevity: Embed wellness, stress management, and leadership training early.

The takeaway is clear: without redesigning how nurses are trained and supported, the system will continue to leak talent faster than it can replace it.

The “SaaSpocalypse” Isn’t Happening—But Change Is

Dr. Michael Wu challenged the idea that LLMs and agents will replace SaaS wholesale.

His argument is grounded in reality: today’s AI systems are probabilistic, not deterministic. That creates hard limits.

LLMs struggle with:

  • Consistency and repeatability
  • Explainability and auditability
  • Real-time performance at scale

That makes them a poor fit for domains like pricing, finance, and compliance-heavy decisions.

But disruption is happening—just selectively.

AI excels in areas like marketing, content, and workflows where:

  • Precision isn’t mission-critical
  • Speed and scale matter more than perfection

Wu’s guidance for leaders:

  • Experiment aggressively—but intelligently
  • Focus on repetitive, high-value, data-rich tasks
  • Use AI to augment, not replace, core systems

The real opportunity isn’t ripping out SaaS—it’s pairing deterministic systems with AI where each performs best.

Why Breakthroughs Come from “Lunatics”

One of the most compelling ideas came from Wu’s historical lens on innovation.

Breakthrough innovation doesn’t come from incremental improvement—it comes from compounding ideas, often sparked by unlikely collaborations.

Historically, progress accelerated when:

  • Builders (“how” people) and thinkers (“why” people) came together
  • Ideas were exchanged freely across disciplines
  • “Crazy” ideas were tolerated long enough to mature

These groups—once meeting in Enlightenment-era salons and even full-moon gatherings—were dubbed “lunatics.”

The modern implication:

Organizations must intentionally create spaces where:

  • Cross-functional thinkers collide
  • Unconventional ideas are explored
  • Experimentation is safe, not career-limiting

Before every breakthrough is an idea that sounds unreasonable.

AI Hype vs. Enterprise Reality

Ron Miller grounded the discussion with a journalist’s perspective from the front lines of enterprise tech.

Despite rapid innovation, real-world results are uneven:

  • Only about one-third of AI projects reach production with measurable ROI
  • Costs remain high, with pricing models still evolving
  • Enterprises are still figuring out how to map AI usage to business value

At the same time, clear value is emerging in:

  • Developer productivity
  • Research and knowledge work
  • Meeting prep and decision support

Miller’s key insight: AI is most effective today as an assistive tool, not an autonomous replacement.

And importantly, human networks—conferences, conversations, lived experience—remain a critical source of insight that AI simply cannot replicate.

Key Takeaways

  • Human-centered design wins: AI scales systems, but human judgment, care, and creativity remain irreplaceable.
  • Not all AI fits everywhere: LLMs are powerful, but their limitations make them unsuitable for many core enterprise systems.
  • Education and workforce models must evolve: Nursing highlights how outdated structures—not lack of demand—create systemic shortages.
  • Innovation requires collision: Breakthroughs happen when diverse thinkers connect and “unreasonable” ideas are explored.
  • Execution matters more than hype: Most AI projects still struggle—leaders must focus on measurable outcomes, not experimentation alone.

Final Thoughts

Episode 434 reinforces a critical truth: the future isn’t about choosing between humans and AI—it’s about orchestrating both effectively.

The organizations that win won’t be the ones that automate the fastest, but the ones that:

  • Redesign systems around real human needs
  • Apply AI where it truly adds value
  • And create cultures where bold, even “lunatic,” ideas can thrive

In a world of accelerating technology, human-centered strategy isn’t a constraint—it’s the advantage.

Related Episodes

If you found Episode 434 valuable, here are a few others that align in theme or extend similar conversations:

Future of Work Tech Optimization New C-Suite AI Chief Executive Officer Chief Technology Officer Chief AI Officer Chief Experience Officer

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

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

R "Ray" Wang at Indiaspora Global AI Summit

R "Ray" Wang at Indiaspora Global AI Summit

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…...

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Don't miss R "Ray" Wang's keynote highlights at the Indiaspora Global AI Summit.

The first movers who adopt this AI revolution, whether agentic or generative, will drive massive change. It's a winner-takes-all market.

The problem with AI is that it's capital-intensive, right now, creating a closed system with few players. We have a centralization model rather than a decentralization model.

But that is all going to change.

We are in the Age of Exponential Scale, and infinite possibilities abound. This means you have to be faster, better, OR cheaper; then faster AND better; then faster AND better AND cheaper.

Want the full keynote? Reach out to [email protected] to get access today.

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Slackbot vs Salesforce, Gemma 4’s Open‑Source Push & HubSpot’s AI Pricing Bet

Slackbot vs Salesforce, Gemma 4’s Open‑Source Push & HubSpot’s AI Pricing Bet

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. ...

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Martin Schneider
Vice President and Principal Analyst
Constellation Research

Martin Schneider has had a unique career that has spanned both analyst and marketing practitioner roles, focused on high technology and related industries. The unifying factor has always been both a keen analysis of go-to-market trends, while also having achieved success as a marketing leader. Schneider started his career as a journalist covering B2B technologies, and quickly transitioned into a leading analyst covering application software for the 451 Group in NYC, where he specialized in CRM, marketing automation, and business intelligence/analytics technologies. After analyzing various go-to-market strategies of dozens of technology vendors, Schneider made the move to the vendor side, where he led successful go-to-market teams for several startups and established tech providers,…...

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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…...

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Hannah Mason
Marketing Director
Constellation Research

Hannah Mason is a marketing director at Constellation Research. She oversees brand positioning, creative direction, and content development across digital platforms, events, and campaigns. Her work spans branding and design—including graphics, sales collateral, and event presentations—along with website content management, newsletters, and Constellation Insights. Mason also manages surveys and produces Constellation’s video collateral, including ConstellationTV. Her role ensures that the Constellation brand is communicated with clarity, creativity, and consistency across all channels. Contact Hannah at [email protected]. ...

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In Episode 127 of ConstellationTV, Constellation Research analyst Martin Schneider and Editor-in-Chief Larry Dignan joined forces to dissect three critical topics impacting enterprise technology today: Slack’s new AI-powered capabilities, the rise of open-source AI models like Gemma 4, and HubSpot’s outcome-based AI pricing strategy. R "Ray" Wang, founder of Constellation Research, rounds out the discussion with an insightful spotlight on Smartsheet, a leading contender in the work coordination platform market.

Slack’s AI Expansion: Game-Changer or Incremental Upgrade?

Slack recently announced the rollout of 30 new features for Slackbot, its AI assistant. These enhancements aim to streamline workflows and improve collaboration, but are they worth the investment?

Key Highlights:

  • Salesforce’s $27 Billion Bet: Larry Dignan kicked off the segment by quipping, "Slack is changing the world. It's the best thing since sliced bread...maybe we'll finally see the value from $27,000,000,000 spent on a new UI for Salesforce, really." For executives managing CRM integration costs, this underscores the scale of Salesforce's wager on Slack’s inclusion in its ecosystem.
  • Headless Software & Flexible Architecture: Martin Schneider elaborated on Slackbot’s architecture, affirming its flexibility: "It's a big move and big noise and, you know, a giant step for headless kind, right? The foundations are there, and that's the important thing." For CIOs, this statement highlights the importance of investing in architecture that scales with evolving AI models. Larry added: "What Slackbot is really doing from an architecture standpoint is leapfrogging the large language models (LLMs)."

  • Immediate Concerns: Larry voiced skepticism about Slack’s iterative AI updates, stating, "I'm a little skeptical because, you know, we've been playing around with Slack for five years now, but maybe they finally got it right. Maybe it is the ultimate teammate we're looking for." This cautionary view highlights the importance of evaluating vendor-driven innovation against tangible business outcomes, a priority for CFOs optimizing tech budgets.

Open-Source AI Models: Enterprise Adoption Taking Shape

The discussion turned to the momentum of open-source AI, with models like Gemma 4 rising to prominence. For executives tasked with balancing innovation and cost control, this segment offered critical perspectives.==

Key Highlights:

  • Global Competition in AI: Larry Dignan lamented the current state of U.S. AI, noting: "The U.S. is just getting clocked by Chinese open-source models." This acts as a wake-up call for CxOs to ramp up investments in enterprise AI or risk falling behind global competitors.
  • Business Customization: Larry emphasized the enterprise importance of open-source models, saying, "Open source models matter a hell of a lot to the enterprise because you're going to have to customize these things. It's gonna be about domain knowledge, not necessarily your big master foundation model."

  • Cost and Innovation: Martin Schneider added, "What we've seen over the last couple of years is just a very expensive global proof of concept. Enterprises are going to need to leverage open source models to lower costs and enable internal innovation." For CTOs, this validates a strategic shift toward open-source technologies as cost-effective, scalable solutions.

HubSpot’s Outcome-Based Pricing: Changing the SaaS Game

HubSpot is breaking new ground with its outcome-based pricing model for AI agents, charging businesses based on results rather than flat subscription fees. This experiment could reshape SaaS pricing strategies across industries.

Key Highlights:

  • Details of the Pricing Model: Larry broke down HubSpot’s approach: "HubSpot is pricing per outcome. They are charging you 50¢ per resolved conversation for customer service agents and $1 per lead recommended for outreach."
  • Potential Backlash and Timeliness: Larry acknowledged risks to adoption, remarking, "Every time we've seen this idea floated, customers kind of revolt. This time might just stick because it might actually be the right time."
  • Strategic Positioning: Martin explained why choosing outcome-based models makes sense for specific AI use cases: "The value that we get from SaaS software isn't the value that we got two, three, four, five years ago. It's got to change or else these guys are going to get so commoditized down to just death, right?"

For CFOs, HubSpot’s pricing approach represents both an opportunity and a risk. On the one hand, outcome-based models directly align vendor charges with business improvements. On the other hand, they demand rigorous ROI analysis, as poorly targeted implementation could lead to higher costs without performance gains.

ShortList Spotlight on Smartsheet: Work Coordination Platforms Redefining Collaboration

After the news segment, R "Ray" Wang brought Smartsheet into the spotlight, which has earned a place on Constellation Research’s shortlist for work coordination platforms. The enterprise collaboration market is poised for explosive growth, and Smartsheet is a leading option.

Market Insights:

  • Industry Growth: Ray highlighted that the market for work coordination platforms is projected to grow to $46.3 billion by 2031, expanding at an annual growth rate of 11.4%. For CEOs keeping tabs on digital transformation strategies, this is a clear indicator that investments in these platforms are essential for boosting organizational effectiveness.

Platform Strengths:

  • Efficiency & Accountability: Ray framed Smartsheet as a category leader, stating, "Smartsheet helps employees better organize, track, optimize their productivity and effectiveness."
  • Core Features: He detailed the platform’s capabilities, including centralized task tracking, automated workflows, shared real-time views, and interactive dashboards: "Smartsheet coordinates centralized task tracking, automated notifications, and updates project progress while providing dashboard insights."
  • Integration with Major Platforms: Smartsheet’s compatibility with Slack, Microsoft, and Google Workspace further reinforces its appeal to enterprises seeking seamless interoperability.

For CIOs and COOs prioritizing operational efficiency, the case for Smartsheet is becoming increasingly compelling. The platform’s ability to align teams, automate workflows, and enhance visibility across projects directly addresses enterprise challenges around collaboration and productivity.

Final Takeaways

This episode of CRTV highlighted transformative shifts across enterprise technology. Whether it was Slack’s ambitious AI overhaul or the rise of new pricing models through HubSpot, the discussions underscored the need for executive leaders to align tech strategies with business outcomes.

  • AI Adoption vs. ROI: Executives should prioritize AI investments that drive tangible benefits beyond hype. As Larry pointed out, "mid-market companies don't care about AI for the sake of AI. They care about growth and returns."
  • Open Source as a Cost-Control Strategy: CTOs should explore how open-source AI solutions can lower operational costs while enabling domain-specific innovation.
  • Outcome-Based SaaS Pricing: CFOs must reevaluate how SaaS pricing models impact profitability, ensuring experimentation aligns with bottom-line benefits.

  • The Rise of Work Coordination Platforms: Smartsheet’s capabilities are a strong example of platforms addressing inefficiencies in collaboration and project tracking. With the market growing in size and importance, enterprises must accelerate adoption.

Catch the Next CRTV Episode in Two Weeks!

🔔 Don't forget to follow and subscribe to ConstellationTV across the following platforms:

YouTube, Spotify, LinkedIn, and X for more insights into enterprise technology trends.

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On ConstellationTV

From Demos to Revenue and Love: What DisrupTV 433 Reveals About the Future of AI and Leadership

From Demos to Revenue and Love: What DisrupTV 433 Reveals About the Future of AI and Leadership

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…...

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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] ...

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From Demos to Revenue and Love: What DisrupTV 433 Reveals About the Future of AI and Leadership

On Episode 433 of DisrupTV, hosts Vala Afshar and R “Ray” Wang explored two defining forces shaping modern business:

  • AI as core infrastructure and a revenue engine
  • Love and experience intelligence as the ultimate differentiators

Featuring Brian Bryson of MIT Technology Review and Marcus Buckingham, author of Designing Love In, the episode makes one thing clear: the future belongs to organizations that combine AI-scale execution with human-scale leadership.

AI Is No Longer Optional—It’s Infrastructure

Brian Bryson framed a critical shift: AI is no longer a sidecar—it’s becoming foundational to how businesses operate.

As AI embeds into core systems, new challenges emerge:

  • Probabilistic vs. deterministic systems: AI outputs probabilities, not certainties, breaking traditional governance models.
  • Trust becomes critical: Even highly accurate systems fail if employees or customers don’t trust them.
  • Leadership shifts to the top: AI is no longer a CIO initiative—it’s a CEO mandate.

The implication is clear: winning companies won’t just deploy AI—they’ll redesign workflows, roles, and decision-making around it.

From Experiments to Revenue Machines

The era of AI pilots is over. The focus now is measurable business impact.

Across industries, three areas are seeing the biggest gains:

  • Cost efficiency (today’s baseline)
  • Revenue growth (rapidly accelerating)
  • Customer experience (being reshaped in real time)

Real-world examples bring this to life:

  • At ServiceNow, 85% of IT tickets are now handled by AI agents.
  • On Salesforce Commerce Cloud, 1 in 5 ecommerce dollars is influenced by AI.
  • AI-driven lead recovery turned 350,000 ignored leads into $10M in 90 days.

Agentic AI is also going bottom-up. Employees are building workflows and systems in hours—often without coding backgrounds—turning ideas into execution faster than ever.

AI Autonomy Requires Deep Connectivity

Autonomy doesn’t mean independence—it means deeper integration.

As Vala noted, systems like autonomous vehicles rely on dense layers of data, sensors, and real-time context. The same is true in business:

AI-driven organizations are becoming more connected, not less.

This shift is moving companies from experimentation to full-scale transformation—where AI is embedded across operations, not isolated in pilots.

The Missing Piece: Designing Love Into Business

While AI scales systems, Marcus Buckingham argues that love scales outcomes.

His core insight:

Experiences drive behaviors, and behaviors drive results.

When employees and customers describe peak experiences, they consistently use one word: love.

And that matters because behavior change isn’t linear. The biggest impact happens at the extreme positive end—when people move from “like” to “love.”

Experience Intelligence: The New Leadership Edge

Marcus introduces experience intelligence—the ability to design experiences that create emotional connection and drive performance.

At the center is a simple but powerful definition:

Love is feeling more fully yourself over time.

To create that, leaders must design for five key feelings:

  1. Control – clarity and predictability
  2. Harmony – emotional understanding
  3. Significance – feeling seen and valued
  4. Connection – not going it alone
  5. Growth – becoming better over time

These aren’t soft concepts—they’re measurable drivers of engagement, loyalty, and performance.

Human-Scale Leadership in a Machine-Scale World

As AI becomes embedded everywhere, efficiency will no longer be a differentiator—it will be table stakes.

What will stand out instead:

  • Experience
  • Emotion
  • Human connection

Leaders must balance two parallel priorities:

  • Build AI-powered systems that drive revenue and scale
  • Design human-centered experiences that create meaning and loyalty

This is where IQ, EQ, and what Vala calls “LQ” (love quotient) converge.

Key Takeaways

  • AI is infrastructure: It’s no longer optional—it’s embedded in core systems and led from the CEO level.
  • Revenue > demos: The focus has shifted to measurable outcomes, from cost savings to revenue growth.
  • Agents unlock hidden value: AI can reclaim missed opportunities at scale—from ignored leads to service backlogs.
  • Trust is everything: Without trust, AI adoption stalls—even if the technology works.
  • Love drives performance: The strongest business outcomes come from experiences people truly love.
  • Experience intelligence matters: Leaders must intentionally design for human connection, not just efficiency.

Final Thoughts

DisrupTV 433 highlights a defining tension of our time: businesses are scaling through AI while risking disconnection from the humans they serve.

The winners will resolve that tension. They will build organizations where AI drives efficiency, revenue, and scale—while leaders design experiences that foster trust, meaning, and yes, even love.

Because the future isn’t just about smarter systems. It’s about more human ones.

Related Episodes

If you found Episode 433 valuable, here are a few others that align in theme or extend similar conversations:

Future of Work Tech Optimization New C-Suite AI Chief Executive Officer Chief Technology Officer Chief AI Officer Chief Experience Officer

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

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

Why Smartsheet Leads in Work Coordination Platforms for 2026

Why Smartsheet Leads in Work Coordination Platforms for 2026

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…...

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Work coordination platforms are becoming critical to modern digital work. Discover why Smartsheet earned a spot on the 2026 Constellation ShortList for Work Coordination Platforms.

In this video, R “Ray” Wang, Principal Analyst and Founder of Constellation Research, unpacks the growing disconnect between everyday collaboration tools and the real work employees need to get done. He explains how the work coordination platform market is projected to reach $46.3B by 2031, and how these platforms help teams organize, prioritize, and stay accountable across an expanding number of projects, colleagues, and stakeholders. Ray highlights Smartsheet as a cloud-based work management platform that delivers:

  • Centralized project and task management
  • Automated workflows, rules, notifications, and updates
  • Flexible views (grid, Gantt, Kanban, calendar) to match how teams prefer to work
  • Real-time collaboration, shared dashboards, and resource management
  • AI-driven insights and integrations with Slack, Microsoft, and Google Workspace

If you’re evaluating tools to better coordinate projects and business processes at scale, this overview will help you understand where Smartsheet fits in the broader work coordination landscape—and why these platforms drive efficiency, visibility, and project success.

View the full Work Coordination Platforms ShortList here.

ShortList Future of Work Data to Decisions
Off ShortList Spotlights

Human Agency, China’s Tech Titans, and India’s Rise: Inside DisrupTV Episode 432

Human Agency, China’s Tech Titans, and India’s Rise: Inside DisrupTV Episode 432

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…...

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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] ...

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Human Agency, China’s Tech Titans, and India’s Rise: Inside DisrupTV Episode 432

On Episode 432 of DisrupTV, hosts R “Ray” Wang (CEO & Founder, Constellation Research) and Vala Afshar (Chief Evangelist, Salesforce) explored three major forces shaping the global tech landscape:

  1. How algorithms and AI are reshaping human agency
  2. How China’s tech titans and EV makers are changing global competition
  3. Why India is emerging as a third major tech superpower

The episode featured two insightful guests: Marcus Fontoura, Microsoft CTO for Azure Core and author of Human Agency in the Digital World, and Rebecca Fannin, journalist and author of Tech Titans of China.

Human Agency in a World of Algorithms – With Marcos Fontoura

Algorithms amplify—and constrain—our choices. Marcus traced the evolution of computing from replacing human calculators on the Manhattan Project to today’s algorithms shaping social media, job networks, and consumer behavior. While efficiency improves lives, it can also reduce human control and unintentionally cause harm.

Auditing Your Digital Life
Marcos recommends a practical framework:

  • Identify tasks that amplify humanity: mentoring, caregiving, creative work
  • Identify tasks that can be delegated to AI: repetitive, formulaic, or administrative tasks

The guiding principle: decide what only humans should do, and let AI handle the rest.

Human-Led, Machine Assist
Marcus emphasized that technology’s purpose is empowerment, not replacement. AI breakthroughs—like DeepMind’s AlphaFold—demonstrate how intelligence can create tangible societal value without displacing human agency.

AI and Value-Producing Work
Drawing on lean management principles, Marcos distinguishes between:

  • Value-producing work: tasks directly tied to creative output or revenue
  • Overhead: administrative or repetitive tasks

AI should reduce overhead, freeing humans for higher-value, meaningful work.

China’s Tech Titans, EV Disruption, and Venture Capital Realignment – With Rebecca Fannin

A total rewrite: Rebecca explained why the new edition of Tech Titans of China required a full overhaul. China’s tech landscape has shifted across batteries, drones, semiconductors, and venture capital, with geopolitical tensions redefining cross-border collaboration.

The VC Split
US VCs are largely withdrawing from China, creating “China for China, US for US” investment arms. Cross-border VC is now constrained, altering funding flows for tech startups.

DeepSeek and AI Efficiency
Rebecca highlighted highly efficient, low-capital AI models emerging from China. These “DeepSeek” efforts force Silicon Valley to rethink the relationship between capital intensity and innovation quality.

Chinese EVs: Market and Security Implications
China dominates EV production, with companies like BYD surpassing Tesla. Their low-cost, high-quality vehicles pose both commercial and national security challenges for the US and Europe.

State-Led Capital Model
With US VCs pulling back, China’s government now drives strategic tech investments, funding semiconductors, AI, and industrial technology. This raises questions about efficiency, risk appetite, and long-term competitiveness.

US Response: Rebuilding the Industrial Heartland
Rebecca advocates for:

  • Reinvesting in domestic manufacturing
  • Focusing on strategic tech sectors (semiconductors, AI, batteries)
  • Accepting a more active government role in tech and infrastructure

India: The Third Tech Superpower

India is emerging as a cost-efficient, talent-rich alternative to the US–China duopoly:

  • Third-largest producer of unicorns
  • Hundreds of millions of internet users, with rapid growth
  • Innovation at 1/10th to 1/100th the cost of Western incumbents in areas like space and digital infrastructure

Challenges remain—energy infrastructure, capital flight—but India is increasingly capable of supporting independent innovation ecosystems.

Key Takeaways

  • Human agency matters: Audit your digital life, delegate tasks to AI wisely, and protect what only humans can do.
  • AI as empowerment, not replacement: Focus on increasing value-producing work and reducing drudgery.
  • China’s tech rise is structural: EVs, AI efficiency, and state-led capital reshape global competition.
  • US industrial strategy must adapt: Investment in strategic sectors and infrastructure is urgent.
  • India is a third tech pole: Cost efficiency and talent are driving a new global tech player.

Final Thoughts

Episode 432 of DisrupTV illuminates a world where technology, geopolitics, and human agency intersect. Leaders, policymakers, and individuals alike must deliberately design for empowerment, efficiency, and opportunity in a landscape increasingly mediated by algorithms and global competition. The future will reward those who understand where AI can support humans, where human judgment remains irreplaceable, and how nations position themselves in the evolving global tech hierarchy.

Related Episodes

If you found Episode 432 valuable, here are a few others that align in theme or extend similar conversations:

Future of Work Tech Optimization New C-Suite AI Chief Executive Officer Chief Technology Officer Chief AI Officer Chief Experience Officer

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

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

Cybersecurity, Nvidia GTC, CEO Mandate for AI | ConstellationTV Episode 126

Cybersecurity, Nvidia GTC, CEO Mandate for AI | ConstellationTV Episode 126

Liz Miller
Vice President & Principal Analyst
Constellation Research

About Liz Miller: Liz Miller is Vice President and Principal Analyst at Constellation, focused on the org-wide team sport known as customer experience. While covering CX as an enterprise strategy, Miller spends time zeroing in on the functional demands of Marketing and Service and the evolving role of the Chief Marketing Officer, the rise of the Chief Experience Officer, the evolution of customer engagement, and the rising requirement for a new security posture that accounts for the threat to brand trust in this age of AI. With over 30 years of marketing experience, Miller offers strategic guidance on the leadership, business transformation, and technology requirements to deliver on today’s CX strategies. She has worked with global marketing organizations to transform everything from…...

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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. ...

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Holger Mueller
Vice President and Principal Analyst
Constellation Research

Holger Mueller is VP and Principal Analyst for Constellation Research for the fundamental enablers of the&nbsp;cloud, IaaS, PaaS and next generation Applications, with forays up the tech stack into BigData and Analytics, HR Tech, and sometimes SaaS. Holger provides strategy and counsel to key clients, including Chief Information Officers, Chief Technology Officers, Chief Product Officers, Chief HR Officers, investment analysts, venture capitalists, sell-side firms, and technology buyers.&nbsp; Coverage Areas: Future of Work Tech Optimization &amp; Innovation&nbsp; Background: Before joining Constellation Research, Mueller was VP of Products for NorthgateArinso, a KKR company. There, he led the transformation of products to the cloud and laid the foundation for new Business Process as a…...

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Hannah Mason
Marketing Director
Constellation Research

Hannah Mason is a marketing director at Constellation Research. She oversees brand positioning, creative direction, and content development across digital platforms, events, and campaigns. Her work spans branding and design—including graphics, sales collateral, and event presentations—along with website content management, newsletters, and Constellation Insights. Mason also manages surveys and produces Constellation’s video collateral, including ConstellationTV. Her role ensures that the Constellation brand is communicated with clarity, creativity, and consistency across all channels. Contact Hannah at [email protected]. ...

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AI Is Now the CEO’s Job: Key Trends from Enterprise Tech, Nvidia GTC, and Constellation’s CFF/AIF

Artificial intelligence has moved from experimental projects at the edge of the business to the center of boardroom strategy. Recent conversations across enterprise technology, Nvidia’s GTC conference, and Constellation Research’s own Future Forum (CFF) and AI Forum (AIF) show the same pattern: AI is no longer just an IT concern. It is a structural force reshaping security, infrastructure, operating models, and even geopolitics.

This blog highlights three major trend areas reflected in CRTV Episode 126 and the surrounding events:

  1. Enterprise technology and security news
  2. Nvidia GTC and the next phase of AI infrastructure
  3. CEO- and board-level themes from Constellation’s CFF and AIF

Enterprise Tech & Security: “Security Is a Data Problem”

The platformization of cybersecurity

A major trend in enterprise technology is the rapid convergence of security and data platforms. Traditional cybersecurity vendors have long focused on endpoints and perimeter defense. Now, data-native platforms are moving aggressively into security:

  • Databricks is positioning itself as a security player by building security capabilities directly on top of its data platform, reducing the need for costly data ingestion into separate SIEM tools.
  • Elastic is embedding security natively into its search and observability stack, again emphasizing proximity to data.
  • ServiceNow has expanded into security through acquisitions, bringing a workflow-centric approach that ties incident response and security operations into broader business processes.

The emerging pattern: “security is a data problem.” Rather than shipping telemetry to specialized tools and paying for duplicated storage, enterprises are increasingly looking to secure data where it already lives and use AI on that data to detect and respond to threats.

Agentic AI and the next security challenge

As agentic AI systems proliferate—autonomous or semi-autonomous agents acting on behalf of users and applications—security thinking is shifting again. At events like RSA, this is showing up as:

  • A focus on securing agents and their toolchains rather than just securing static applications.
  • Increased emphasis on governance of data flows into and out of agents, including prompt injection defenses, data leakage controls, and policy enforcement at the data layer.

Non-traditional security vendors with strong data and AI capabilities are using this moment to undercut endpoint-centric incumbents by promising:

  • Less data movement
  • Lower ingestion and storage costs
  • Tighter integration between analytics, AI, and security controls

Advertising and AI: from “digital” to “answer engines.”

On the marketing and media side, enterprises are preparing for an era of “answer engine marketing” or “generative engine marketing”—where AI systems surface answers, not pages, and where ads may be injected directly into those answers.

Key trends:

  • Generative AI in discovery: Platforms like Apple Music (in partnership with Ticketmaster), Google TV (with Gemini), and Amazon’s ad stack are using AI to drive content discovery and personalization across connected devices.
  • CTV and data-driven targeting: Connected TV has become a prime advertising surface, powered by granular audience data and predictive models.
  • Resurgence of “old” channels: Direct mail (e.g., Valpak) and outdoor advertising are benefiting from precise data-driven segmentation and dynamic content, contradicting past assumptions that these channels were “dead.”

The core driver behind all these developments is the same: better use of audience and behavioral data, appropriately secured and governed, to place the right content in front of the right person at the right moment—across digital, physical, and hybrid surfaces.

Nvidia GTC: The AI Factory Era

Pivot to inference and the Vera Rubin platform

Nvidia’s GTC conference—as some have called it, the “Woodstock of AI”—highlighted a clear shift: from a narrow focus on training large models to a broader emphasis on inference at industrial scale.

A central symbol of this shift is the Vera Rubin system, designed as a next-generation AI “factory”:

  • It is optimized around inference workloads, not just training.
  • It introduces specialized components such as the Language Processing Unit (LPU) to improve efficiency and responsiveness for language-heavy inference and agentic systems.
  • It combines GPUs, CPUs, storage, and ultra-fast networking (e.g., NVLink and associated interconnects) in a tightly integrated fabric.

The direction is clear: enterprises are expected to build or rent AI factories—clusters of systems like Vera Rubin—to serve as the backbone for running fleets of agents and AI applications in production.

Software, open models, and vertical LLMs

Nvidia continues to consolidate its position not only as a hardware provider, but as a software and ecosystem orchestrator:

  • A growing catalog of vertical LLMs and domain-specific models spans areas such as healthcare, robotics, simulation, synthetic data generation, and financial services.
  • Many of these models are made available through Nemo and related initiatives that emphasize open or open-weighted approaches, helping enterprises jumpstart projects without building everything from scratch.
  • The Nemo Tron Alliance and similar collaborations are creating an ecosystem of startups aligned around Nvidia-centric tooling, hardware, and deployment patterns.

While Nvidia does not position itself as an enterprise software vendor in the traditional sense, it is building a de facto AI operating environment that reduces friction for adopting its hardware. In this model, “software is free” in the sense that it helps drive demand for infrastructure.

Energy, scale, and the move toward space-based AI

A more experimental but increasingly serious thread involves energy constraints and new compute geographies:

  • There is growing recognition that large-scale AI will be constrained by power availability as much as by chips or models.
  • Concepts such as space-based data centers powered by solar have moved from science fiction to early-stage architectural thinking, with renderings and prototypes being discussed publicly.
  • Ambitions around custom fabs (e.g., “Terra fab”) underscore a trend toward vertical integration: from chip design to fabrication to deployment in specialized environments (including space, automotive, robotics, and beyond).

While these scenarios may be years away from mainstream enterprise adoption, they reflect a larger reality: AI strategy is increasingly inseparable from energy strategy and geopolitics.

CFF & AIF: AI as a CEO and Board Mandate

Constellation Research’s Future Forum (CFF) and AI Forum (AIF) brought together CEOs, board members, CIOs, and technology leaders. Across these events, a single message cut through the noise:

AI is the CEO’s job.

From “digital transformation” déjà vu to real accountability

The notion that “AI is a CEO issue” echoes earlier eras when customer experience (CX) and digital transformation were framed as top-of-the-house responsibilities. In many organizations, those prior mandates never fully materialized:

  • CX initiatives remained fragmented across marketing, sales, and service, hampered by siloed data and misaligned incentives.
  • Digital transformation often turned into incremental digitization rather than true business model reinvention.

The AI moment feels similar—but with higher stakes. This time:

  • Boards are directly asking CEOs, “What is our AI strategy?”
  • CEOs are expected to own enterprise-wide alignment, not delegate AI entirely to IT or innovation labs.
  • Leaders who fail to steer AI in a coherent way may face personal accountability faster than in past transformation waves.

Culture, operating models, and the pace of change

Participants at CFF and AIF consistently highlighted culture and operating model as the real bottlenecks, not technology:

  • Organizations with entrenched functional silos and conflicting incentives (e.g., sales, marketing, and service) struggle to align on data and AI.
  • AI adoption requires rethinking processes and “sacred cows”—from compensation models to decision rights.
  • There is a growing knowledge gap between boards, CEOs, and AI practitioners, turning basic AI discussions into a game of telephone.

Simultaneously, the pace of change in AI models and platforms makes strategic planning more complex:

  • A decision to standardize on one model provider (e.g., OpenAI) can look outdated within months as competitors like Anthropic or open-source ecosystems catch up or leap ahead.
  • Enterprises are wary of becoming locked into any single foundation model, vendor, or cloud platform, driving interest in model-agnostic architectures and multi-model strategies.

Open source, “claws,” and safe experimentation

At the AI Forum in particular, there was an animated discussion around open AI stacks, including tools like OpenCLIP / Open-weights models and various “claw” frameworks that allow organizations to orchestrate and govern multiple models and agents.

Key enterprise concerns include:

  • How to experiment safely with open and local models without exposing sensitive data or critical systems.
  • How to define governance boundaries for internal innovators who will inevitably bring in new tools and frameworks.
  • How to leverage open ecosystems to avoid vendor lock-in, while still meeting requirements around support, compliance, and security.

Many leaders are adopting a tiered experimentation strategy:
using isolated, low-risk environments (e.g., dedicated machines or sandbox infrastructure) for early trials, before integrating new tools into core data and application stacks.

Geopolitics, power, and sovereignty

Finally, CFF and AIF discussions reinforced that the AI strategy is now entangled with geopolitics:

  • Differences in energy costs, regulatory regimes, and data sovereignty are shaping where and how AI can be deployed at scale.
  • Regions such as China and India are developing their own models, data practices, and infrastructure approaches, which may diverge meaningfully from North American and European patterns.
  • Executives are increasingly aware that power availability, chip supply, and national policy can materially impact AI roadmaps, even though these factors are largely outside their direct control.

For many enterprises, this means AI planning must include scenarios for supply chain volatility, regulatory shifts, and regional model ecosystems, not just technology capabilities.

From Hype to Hard Choices

Across enterprise news, Nvidia’s GTC announcements, and Constellation’s CFF and AIF, a consistent picture emerges:

  • Security is converging with data and AI, pushing enterprises toward platforms that can analyze and protect information in place.
  • AI infrastructure is industrializing, with “AI factories” and specialized hardware/software stacks designed for always-on inference and agents.
  • AI has become a CEO and board mandate, forcing organizations to confront culture, operating models, vendor lock-in, power constraints, and geopolitics—not just tools and models.

The organizations that navigate this moment successfully will treat AI not as a set of disconnected pilots, but as a strategic, cross-functional transformation that redefines how they create value, manage risk, and compete.

On ConstellationTV

Global Growth, Status, and AI Agents: What’s Shaping the Next Decade of Business | DisrupTV Ep. 431

Global Growth, Status, and AI Agents: What’s Shaping the Next Decade of Business | DisrupTV Ep. 431

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…...

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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] ...

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Global Growth, Status, and AI Agents: What’s Shaping the Next Decade of Business | DisrupTV Ep. 431

In DisrupTV Episode 431, hosts R "Ray" Wang and Vala Afshar explored two forces that will shape the next decade of business: global expansion in an AI-first world and the powerful role of social status in decision-making.

Featuring Russell Haworth, CEO of Acclaro, and Toby Stuart, UC Berkeley professor and author of Anointed, the conversation highlighted how companies scale globally, build trust, and navigate influence in an era where AI agents increasingly mediate interactions between people, products, and brands.

Together, the discussions revealed an emerging reality: globalization, AI, and status dynamics are becoming deeply intertwined.

Global Expansion Starts at Design, Not Launch

Russell Haworth emphasized a common mistake many companies make when expanding internationally.

Most organizations build products for their home market first—often the U.S.—and only consider localization once domestic success arrives. By then, adapting product design, UX, and go-to-market strategies becomes costly and slow.

His advice: design global from day one.

Localization isn’t just translation. It touches nearly every part of the business:

  • User experience: Interface layouts built for English can break when translated into languages with longer text or different structures.
  • Payments and regulation: Local payment systems, legal requirements, and compliance vary widely across markets.
  • Customer trust: If users cannot interact in their own language or cultural context, retention suffers.

As Haworth put it, if customers can’t understand your company, you don’t have a translation problem—you have a churn problem.

Hyper-Localization and the AI + Human Model

Modern global growth requires something deeper than simple localization: hyper-localization.

This means adapting messaging, imagery, campaigns, and channels to specific audiences—even within the same country. Cultural nuance matters across regions, demographics, and social groups.

AI plays a key role in scaling this effort.

AI systems can rapidly translate and adapt content across multiple markets, enabling companies to operate globally at speed. But human experts remain critical for cultural nuance, market testing, and ensuring messaging resonates authentically.

The winning formula is clear: AI for scale, humans for nuance.

Organizations that combine both can dramatically increase engagement and conversion in international markets.

Social Status in a Winner-Take-Most Economy

The second half of the episode shifted focus to social status and influence, a topic explored in Toby Stuart’s book Anointed.

Stuart explained that status shapes many of our decisions—often unconsciously. When we face uncertainty or too many choices, we rely on signals like reputation, affiliation, and brand prestige.

Status comes from multiple sources:

  • Achievement: expertise or performance valued by a group
  • Occupation: roles with built-in prestige
  • Personal reputation: generosity, collaboration, or leadership within communities
  • Ascribed traits: characteristics like gender, race, or background
  • Network associations: status gained through relationships and affiliations

These signals often determine who gets attention, funding, or opportunity—even when the underlying quality of ideas or products is similar.

The “Anointment” Effect

Stuart illustrated this dynamic with the art market.

A painting attributed to a student of Rembrandt might sell for thousands. The exact same painting, if authenticated as a Rembrandt, could be worth millions.

Nothing about the object changes—only the name attached to it.

This same pattern appears in venture capital, hiring, media influence, and product perception. Once a person or brand is recognized as high-status, the market tends to treat their output as higher quality.

Status becomes self-reinforcing.

AI Agents and the Future of Trust

Both conversations converged around one emerging reality: AI agents are rapidly becoming intermediaries in decision-making.

Consumers increasingly rely on AI systems to recommend products, plan travel, evaluate vendors, and even prepare for meetings.

This shift could reshape how status works.

Today, humans rely heavily on reputation and pedigree because we cannot evaluate everything ourselves. AI agents, however, can analyze massive amounts of data and potentially assess quality more directly.

In the near term, this may actually increase reliance on status signals, as people look for trusted sources in an increasingly complex digital landscape.

Over time, as AI evaluation improves, traditional prestige signals—like brand reputation or elite credentials—may become less dominant.

But new hierarchies will emerge around which agents, platforms, and AI systems people trust to act on their behalf.

Key Takeaways

  • Global expansion must start at the design stage. Localization is not a post-launch task—it’s a foundational market strategy.
  • Hyper-localization drives engagement. Companies must adapt messaging, media, and experiences to specific regional and cultural audiences.
  • AI and humans work best together. AI enables global scale, while humans ensure cultural relevance and brand authenticity.
  • Status still shapes opportunity. Reputation, affiliation, and networks strongly influence decisions in business and society.
  • AI agents will reshape trust and influence. As digital intermediaries grow more powerful, new status hierarchies will emerge around the ecosystems and platforms people rely on.

Final Thoughts

Episode 431 of DisrupTV highlighted a powerful intersection of forces shaping the future of business.

Companies that succeed globally will design for international markets from the beginning, combining AI-driven scale with deep cultural understanding.

At the same time, leaders must recognize that status and influence still shape how opportunities flow, even in an AI-driven economy.

As AI agents increasingly mediate how people discover, evaluate, and buy products, the next competitive advantage will lie in earning trust—both from humans and from the digital systems acting on their behalf.

In a world defined by globalization, AI, and networked influence, the winners will be those who design intentionally for scale, culture, and credibility from day one.

Related Episodes

If you found Episode 431 valuable, here are a few others that align in theme or extend similar conversations:

Future of Work Tech Optimization New C-Suite AI Chief Executive Officer Chief Technology Officer Chief AI Officer Chief Experience Officer

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

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

Enterprise AI Reality Check, Services-Centric ERP, Infosys 2026

Enterprise AI Reality Check, Services-Centric ERP, Infosys 2026

Hannah Mason
Marketing Director
Constellation Research

Hannah Mason is a marketing director at Constellation Research. She oversees brand positioning, creative direction, and content development across digital platforms, events, and campaigns. Her work spans branding and design—including graphics, sales collateral, and event presentations—along with website content management, newsletters, and Constellation Insights. Mason also manages surveys and produces Constellation’s video collateral, including ConstellationTV. Her role ensures that the Constellation brand is communicated with clarity, creativity, and consistency across all channels. Contact Hannah at [email protected]. ...

Read more

ConstellationTV Episode 125 features three conversations about where enterprise AI and automation are really headed: the economics and architecture of AI at scale, the evolution of services-centric ERP, and how global systems integrators like Infosys are turning AI strategy into execution.

Below is a recap of the key themes and takeaways.

Enterprise AI Reality Check: GTC, Tokenomics, and Agent Orchestration

Martin and Larry open the episode with a look ahead to Nvidia GTC, which Martin describes as the “mecca” or even the “Woodstock” of AI. Beyond the spectacle of new chips, they’re focused on a more pressing question: is the current AI spend model sustainable for most enterprises?

From Hype to Economics: Tokenomics and Cost Models

The discussion centers on tokenomics and the underlying AI cost model:

  • Today’s AI leaders—Nvidia, Anthropic, OpenAI, the hyperscalers—benefit from an infrastructure-heavy, scale-driven model where more infrastructure can translate into more revenue.
  • For “the average bear” enterprise, that dynamic doesn’t hold. The current wave of experimentation, endless pilots, and loosely defined use cases is driving spend without clearly demonstrating value.

Martin and Larry argue that we’re heading toward a reckoning in AI investment. As budgets tighten, organizations will need:

  • Clear, well-defined use cases with measurable outcomes
  • A shift away from “we’re doing AI because we have to” toward value-anchored initiatives
  • A more sane spend profile, especially around inference costs and token usage

Less Agent Sprawl, More Orchestration

Another key theme is agent orchestration. Many organizations have rushed to build agents for extremely narrow use cases, leading to:

  • Agent proliferation: anyone can spin up an agent; almost everyone has
  • Complexity in IT, governance, security, and maintenance
  • Rising costs without corresponding gains in business outcomes

The future, they suggest, is fewer, smarter agents that:

  • Support multiple use cases per agent
  • Produce outputs that can feed multiple workflows and applications
  • Are managed via robust wrangling and orchestration capabilities

In other words, enterprises must move from “one agent per micro-use-case” to strategically designed agent ecosystems that optimize spend and value.

Anthropic vs. OpenAI and the Rise of the Context Layer

Martin also calls out the ongoing Anthropic vs. OpenAI narrative. While headlines focus on model releases and benchmark gains, the real shift is:

  • Both vendors are building vertically integrated stacks around their LLMs
  • The true battleground is not just the model layer, but the context and business layer that sits between models and applications

Referencing Satya Nadella, they note that context will decouple from the model. This points toward:

  • Multi-model futures where enterprises mix and match commercial, open-source, and custom models
  • The need for business context fabrics that understand the enterprise’s data, processes, and vertical nuances
  • Vendors like Zoho and Salesforce are already building these context layers inside their platforms and vertical offerings

The implication: the big “foundation models” we see today may be global proof-of-concepts. Long-term advantage will come from domain-specific, industry-specific, and context-rich AI built on top of (and independent from) any given base model.

Services-Centric Cloud ERP: Automation, Decision Velocity, and a Winner-Takes-Most Market

In the second segment, R "Ray" Wang introduces Constellation’s services-centric ERP ShortList, focused on finance and professional services–driven organizations.

Market Outlook: AI, Automation, and Zero-FTE Ambitions

Ray outlines a forecast for the services-centric ERP market through 2031, with strong growth driven by:

  • AI and automation embedded across finance, operations, and services
  • A push toward intelligent process automation that moves beyond insight to actual decisioning and execution
  • Ambitious goals like moving parts of the back office toward “zero FTEs”—not by eliminating humans entirely, but by automating repetitive processes and elevating human work to higher-value decision making

He frames the future of ERP as being less about transactional systems of record and more about:

  • Decision velocity: how quickly an organization can sense, decide, and act
  • Augmenting humans with machines (and vice versa)
  • Embedding AI and automation into core workflows, rather than bolting it on

What Separates ERP Winners from Laggards

According to Ray, successful services-centric ERP platforms today typically provide:

  • Strong enterprise financials
  • Grant management and elements of HCM
  • Indirect procurement capabilities, with professional services automation, project planning, and travel and expense as important, sometimes optional, pieces

What really differentiates the leaders:

  • Native AI and automation capabilities
  • Ability to enable intelligent process automation across end-to-end workflows
  • Support for fast, high-quality decision making (decision velocity) across finance and services

Intuit Enterprise Suite and the Mid-Market Opportunity

Ray highlights Intuit Enterprise Suite as an important solution on the shortlist, especially for:

  • Small-to-midsized enterprises
  • Divisions of large companies that need services-centric ERP capabilities without the overhead of heavyweight enterprise systems

The key insight: many still see Intuit as purely small-business focused, but the enterprise suite is increasingly moving up-market and competing in a space that demands serious automation, compliance, and scalability.

Live from Infosys 2026: Data to Decisions, Governance, and the Speed vs. Velocity of AI

The final segment switches to a live cut from an Infosys analyst day in New York City, featuring Liz Miller, Mike Ni, and R "Ray" Wang.

From Data Foundations to Decisioning

Mike emphasizes a shift many enterprises are trying to make:

  • Moving beyond data foundations alone
  • Focusing on processes where AI and automation directly drive decisions
  • Collapsing decision loops and decision trees so that insights lead to automated or semi-automated actions, not just dashboards

This is where platforms like Infosys’ Topaz come into play: enabling domain-specific, jointly developed solutions with customers that speed up time to value.

Responsible AI and Governance as Accelerators

A recurring theme at Infosys: governance and responsible AI.

Liz notes that:

  • Governance was front and center in customer conversations
  • Infosys’ long-standing reputation for solving complex, high-stakes, long-term transformation problems makes it a natural leader on this front
  • For regulated industries, clear governance and responsible AI frameworks are not blockers—they are enablers that allow organizations to move faster with confidence

Infosys’ customers aren’t chasing hypothetical innovation projects; they are solving real, pressing problems, repeatedly bringing those problems back to Infosys over many years.

Expertise vs. Experience, and the Role of Platforms

Ray draws a sharp line between expertise and experience:

  • Expertise—knowing tools, methods, and patterns—is increasingly commoditized.
  • Experience—deep knowledge of industry processes, regulations, and operational nuance—is what enables organizations to build AI solutions quickly, safely, and at scale.

He argues the winners in this market share three traits:

  1. Deep industry and process experience
  2. A strong platform foundation for data, governance, automation, and AI
  3. A clear strategy and order of operations for transformation

This leads to a critical distinction: speed vs. velocity.

  • Speed is movement for its own sake—spinning up pilots and proofs of concept.
  • Velocity is speed with direction, aligned to strategy, sequencing, and measurable impact.

In an AI?driven, winner?takes?most market, those that first reach a viable solution in the right domain can capture outsized share—Ray points to patterns like 60% for the first mover, 20% for the next, and a scramble for the remaining 20%.

To win, enterprises need not just to move fast, but to move fast in the right direction, with governance, platforms, and industry experience underpinning their efforts.

Why This Episode Matters

  • AI hype is giving way to economics: tokenomics, cost models, and ROI are taking center stage.
  • The context and business fabric layer is becoming the true differentiator, not just LLM performance.
  • Agent orchestration and governance—of agents, data, and decisions—are now core enterprise capabilities.
  • Platforms with deeper industry experience are what turn AI pilots into market?shaping capabilities.
  • Strategy and order of operations determine whether you’re merely fast—or whether you have velocity in a winner?takes?most AI landscape.

For CIOs, CTOs, CFOs, COOs, and business leaders navigating AI, ERP modernization, and large?scale transformation, Episode 125 serves as both a reality check and a pragmatic roadmap for where to focus next.

Future of Work Data to Decisions Innovation & Product-led Growth Next-Generation Customer Experience Tech Optimization
On ConstellationTV

From Experience to Transformation: How Businesses Help Customers Become Who They Want to Be | DisrupTV Ep. 430

From Experience to Transformation: How Businesses Help Customers Become Who They Want to Be | DisrupTV Ep. 430

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] ...

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The Future of CX: AI, IRL, and the Transformation Economy | DisrupTV Ep. 430

DisrupTV Episode 430 marked a major milestone—10 years on air and more than 1,500 interviews. To celebrate, hosts R "Ray" Wang and Vala Afshar explored a bigger question about where business value is heading next.

For decades, companies have focused on delivering better products, services, and more recently, memorable customer experiences. But according to author and strategist Joe Pine, the next shift goes even further.

The future belongs to businesses that help customers become who they want to become.

Enter the Transformation Economy

Joe Pine, co-author of The Experience Economy, joined the show to discuss his latest thinking: the rise of the Transformation Economy.

In previous economic eras, value progressed from commodities to goods, to services, and eventually to experiences—memorable interactions that engage customers emotionally.

But transformations are different.

Instead of selling a moment or interaction, companies help customers achieve a lasting outcome.

  • Experiences create memories

  • Transformations create change

In this model, the true “product” is not the service or experience itself—it’s the improved version of the customer on the other side.

Experiences become the raw material used to guide people from where they are today to where they aspire to be.

Why Transformations Matter Now

Several forces are accelerating this shift.

First, people are searching for meaning.
The pandemic reminded many of us that time and connection matter deeply. Experiences returned quickly once restrictions lifted—but many people now want more than entertainment. They want progress, purpose, and personal growth.

Second, self-improvement has gone mainstream.
Coaching, fitness programs, financial planning, mental wellness platforms, and professional development services are all booming. Customers are increasingly willing to invest in offerings that help them become healthier, wealthier, wiser, or more purposeful.

Third, time itself has become the new economic lens.

Joe Pine frames economic value through three stages:

  • Goods & services: time well saved

  • Experiences: time well spent

  • Transformations: time well invested

Transformations generate a compounding return because the payoff is the person the customer becomes over time.

The Role of AI in Guiding Transformation

AI will play an important role in enabling the transformation economy—but as a tool, not the guide.

Used well, AI can help organizations:

  • Personalize experiences at scale

  • Recommend the “next best step” in a transformation journey

  • Deliver continuous nudges, coaching prompts, and insights between human interactions

This is already happening across industries like education, financial services, and leadership coaching, where AI supports ongoing development while human mentors provide empathy, context, and guidance.

The key distinction: technology can assist transformation, but people ultimately transform themselves.

CX Still Starts with Simplicity

In the second half of the episode, CRM experts Paul Greenberg and Brent Leary grounded the conversation in practical customer experience lessons.

Their point was simple but powerful:

Before businesses attempt to transform customers, they must first make things easy.

Convenience still matters. Customers often just want a fast, frictionless interaction—whether that’s dropping off a package, resolving a support issue, or completing a purchase.

Great experiences don't always mean delight or spectacle. Often, they simply mean respecting a customer’s time and helping them make progress.

Key Takeaways

  • The next economic shift is toward transformation. Businesses will increasingly be judged by how they help customers achieve meaningful outcomes.

  • Experiences are a stepping stone, not the destination. Memorable moments should guide customers toward lasting change.

  • Time well invested is the new value metric. Customers want offerings that create progress, not just entertainment.

  • AI can personalize transformation journeys. But human empathy, mentorship, and purpose remain essential.

  • Convenience still comes first. Before transformation, companies must eliminate friction and respect customer time.

Final Thoughts

The transformation economy challenges companies to rethink their purpose.

Instead of simply delivering products, services, or even experiences, organizations must ask a deeper question:

How are we helping our customers grow?

Businesses that succeed in the next decade will design offerings around the outcomes people truly want—better health, stronger careers, deeper knowledge, greater purpose, and ultimately a better version of themselves.

Profit then becomes something different: not the goal, but the signal that the company is successfully helping people flourish.

Related Episodes

If you found Episode 430 valuable, here are a few others that align in theme or extend similar conversations:

Future of Work Tech Optimization New C-Suite AI Chief Executive Officer Chief Technology Officer Chief AI Officer Chief Experience Officer

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

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