Designing for Limitations: How TCS Is Using AI to Make Accessibility a Competitive Edge

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 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.  Coverage Areas: Future of Work Tech Optimization & Innovation  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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For decades, accessibility lived in the same bucket as most compliance work: bolted on after the product was built, driven by regulation, and measured by whether complaints stopped coming in. In a recent interview, Constellation analyst Holger Mueller sat down with Shashi Bhushan and Charudatta Jadhav of TCS to make the case that this era is ending, and that AI is the reason the shift is happening now rather than another decade from now.

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From Compliance to Competitive Advantage

The starting number in the conversation is hard to ignore: one out of six people globally lives with a disability. For years, that population was treated as a niche segment with limited purchasing power, worth accommodating for legal and reputational reasons but not worth building a strategy around. That calculation is changing. Bhushan pointed to an estimated $1 trillion in aggregate purchasing power among people with disabilities globally, along with anecdotal evidence that companies that strategically serve this segment see substantially higher revenue outcomes.

The panel drew a direct comparison to how organizations now treat cybersecurity spending: initially driven by fear and regulation, but increasingly justified on business grounds. Accessibility, they argued, is on a similar trajectory, just a few years behind. As Bhushan put it, once the realization sets in that this is a one-out-of-six customer base rather than an act of goodwill, board conversations shift from good intentions to competitive strategy.

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Designing for Limitations, Not Personas

One of the more interesting reframes in the conversation was TCS's move away from traditional persona-based accessibility design. The conventional approach starts with a defined disability persona and designs around its known requirements, useful, but inherently reactive and limited to whatever personas were considered upfront.

TCS's alternative, which Jadhav called "designing for limitations," starts instead from the limitation itself: sensory, environmental, or ecosystem-level constraints. Rather than asking "how do we accommodate this persona," the question becomes "how do we solve for this class of limitation." Jadhav noted that this approach tends to produce a wider canvas for innovation, and frequently ends up improving the experience for people outside the original target group entirely, a pattern accessibility work has produced repeatedly produced: features built for a specific limitation often end up mainstream. Screen readers, originally built for visually impaired users, are a direct ancestor of the voice assistants now sitting on millions of kitchen counters.

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Where AI Changes the Equation

The panel's most forward-looking material centered on what Jadhav called "egocentric models," AI systems trained specifically on accessibility-related data to understand how people with different sensory or physical constraints actually perceive and navigate the world. Unlike general-purpose large language models trained broadly on the internet, these models are purpose-built to understand, for example, how a visually impaired person constructs a mental map of a physical or digital space.

Jadhav extended this into a compelling long-term vision: an AI-powered "digital companion" that accompanies a person across every experience, banking, retail, travel, and beyond, retaining memory of preferences, context, and prior interactions throughout that person's life. Rather than solving accessibility one interaction at a time, the goal becomes eliminating the friction of the limitation itself from the equation entirely. Bhushan, drawing on his own lived experience navigating vision-related accessibility challenges, described the shift plainly: the goal is a world where technology adapts to the human, rather than the human adapting to the technology.

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The Road Ahead

Looking toward 2030, the panel pointed to two converging forces: AI's growing ability to directly enhance human capabilities, and its growing ability to build genuinely equitable systems around those capabilities. Their closing framing captured the throughline of the conversation well: enterprises built around accessibility in the AI era will need to be, in Bhushan's words, SMART, sustainable, meaningful, accessible, resilient, and trusted, with technology functioning as an invisible enabler rather than a visible workaround.

The larger argument running through the discussion isn't really about accessibility as a category. It's about where the next decade of competitive differentiation in enterprise technology is likely to come from, and the panel makes a clear case that the answer includes a market segment most organizations have historically underpriced.

Future of Work Tech Optimization New C-Suite Digital Transformation Agentic AI AI GenerativeAI Chief Information Officer Chief Technology Officer Chief Human Resources Officer Chief AI Officer On CR Conversations

On-Prem's Comeback, Qualtrics' New Playbook, and Why AI Needs Context, Not Just Data

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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Enterprise AI is outgrowing the model and the chatbot. That's the thread running through Episode 139 of ConstellationTV, where the conversation keeps landing on the same question from different angles: once AI has to actually operate inside the business, across infrastructure, customer experience, and decision-making, what does it need to work reliably?

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The Big Debate: Is On-Prem AI Actually Making a Comeback?

Mike Ni moderated a debate between Holger Mueller and Esteban Kolsky on one of infrastructure's oldest questions, reopened by AI: does it run on-prem or in the cloud?

Mueller pointed to strong recent hardware numbers from Dell and HP as evidence of a real on-prem renaissance, but argued the pull toward public cloud is still structural. His analogy: running AI on-prem today is like a company generating its own electricity a century ago. It's possible, but the economics of elasticity eventually win. He introduced a concept he's calling "GPU gravity," the idea that faster GPUs will pull workloads toward them the same way data gravity pulls more data together, because in agent-to-agent interactions, the agent running on faster infrastructure simply makes better decisions, faster, more often.

Kolsky pushed back with an inference-economics argument: for steady, predictable, high-volume AI workloads, owning the infrastructure can be cheaper than the public cloud, and mainframes are seeing renewed relevance because of their CPU management strength. Ni added the practical wrinkle, that CIOs can't easily justify large capital expenditure to a board when workloads are still in experimentation mode, and that latency from data routing is a real cost most people underweight.

The debate didn't resolve into a single answer, and it wasn't supposed to. All three converged on hybrid as the near-term reality, but disagreed on the tilt: Mueller sees the long-term center of gravity moving to public cloud, Kolsky sees a genuine opening for on-prem economics, and Ni framed the real strategic question as workload routing, balancing quality, latency, data access, policy, and cost, rather than picking one mode and committing to it.

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Qualtrics' New Chapter: From Measuring Experience to Simulating It

Liz Miller, Mike Ni and R "Ray" Wang sat down with the Qualtrics team in Salt Lake City following the company's recent launch event, and the shift they described is meaningful. Experience management has historically meant deciding on an experience, pushing it out, and measuring the response after the fact. Qualtrics' new direction moves that earlier: simulate the experience against synthetic panels, predict the outcome, and only then act, rather than running hundreds of live experiments against real customers.

Wang framed the shift around three ideas: simulate, trust, and outcome. The simulation piece lets teams test far more granular audience segments than traditional A/B testing ever allowed, down to sub-sub-personas rather than broad 50/30/20/10 splits. But the more interesting shift is philosophical. Miller pointed out that CMOs have spent years assuming they control the customer experience, when the customer has always been the one actually managing it. Qualtrics' new positioning directly acknowledges this, aiming to deliver "tailored" experiences that adjust in real time based on context, time, location, journey stage, even physiological signals, rather than a single predetermined path.

The two also unpacked "ontology" in plainer terms: it's the structured relationship between the signals a system tracks and what those signals actually mean for the experience being delivered. That structure, built on Qualtrics' roughly 20 years of experience data, is what makes simulation trustworthy rather than just another guess.

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Splunk's Reinvention: Making Agents Reliable, Compliant, and Cost-Aware

Splunk used its recent conference to lay out a broader reimagining of itself as it deepens integration with parent company Cisco. Two announcements stood out to Constellation analyst Chirag Mehta. The new Observability Studio focuses on tokenomics, directly addressing a problem enterprises are already facing with agents in production: keeping them reliable, compliant with policy, and within budget. And Splunk is extending into security operations centers, where AI agents can now handle detection, investigation, response, and governance tasks directly.

The Cisco relationship is providing Splunk with meaningful distribution, with existing Cisco customers now able to discover Splunk's capabilities through products such as Cisco Command Center and AI Canvas. The framing throughout: Splunk's core strength was always turning data into answers, and that strength now extends to monitoring the behavior, security, and economics of AI agents themselves, not just the systems around them.

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New ShortList: Semantic and Context Management

Mike Ni closed the episode by introducing Constellation's newest ShortList, covering semantic and context management, and made the case for why it deserves to be its own category rather than a subset of data management.

His framing: most executives can't cleanly define "enterprise context," but they know immediately when it's missing. A dashboard showing a 12% pipeline shrink isn't actionable on its own; a human operator fills the gap with judgment and experience. AI doesn't have that judgment, which turns missing context into an architectural problem the moment agents start taking action rather than just generating insight.

Ni drew a clear line between data management's traditional questions (what data do we have, can we trust it, what does it mean) and the newer layer semantic and context management adds: what matters right now, and what is an agent allowed or expected to do about it. He evaluated the category across nine capabilities, from semantic management and AI grounding to policy-aware context and explainability, and spotlighted Actian as a vendor worth watching.

Actian's approach centers on a federated knowledge graph that connects metadata, lineage, definitions, and policy across systems without requiring organizations to physically move their underlying data, paired with a knowledge graph that captures relationships and dependencies in a form AI systems can actually traverse, not just search. Ni also highlighted Actian's move toward "activated" context: machine-readable data contracts and support for standards like MCP that let governed context reach analytics tools, applications, and AI agents directly at runtime.

His closing question for AI leaders is the one worth sitting with: are your metadata investments just documenting the business, or are they becoming something your AI can actually use?

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The Throughline

Every segment in this episode circles back to the same tension: enterprise AI's hard problems have moved past the model itself and into the infrastructure, context, and operating choices that surround it. Where workloads run, how experience decisions get made, whether agents stay reliable and cost-aware, and whether AI has the context it needs to act rather than just respond — these are the questions defining the next phase of enterprise AI adoption.

Tech Optimization Data to Decisions Digital Safety, Privacy & Cybersecurity Marketing Transformation Cloud Data to Decisions AI Agentic AI cybersecurity Chief Information Officer Chief Technology Officer Chief Marketing Officer Chief AI Officer On ConstellationTV

Splunk Reimagines Observability in the AI Era

Chirag Mehta

Vice President and Principal Analyst
Constellation Research

Chirag Mehta is Vice President and Principal Analyst focusing on cybersecurity, next-gen application development, and product-led growth. With over 25 years of experience, he has built, shipped, marketed, and sold successful enterprise SaaS products and solutions across startups, mid-size, and large companies. As a product leader overseeing engineering, product management, and design, he has consistently driven revenue growth and product innovation. He also held key leadership roles in product marketing, corporate strategy, ecosystem partnerships, and business development, leveraging his expertise to make a significant impact on various aspects of product success. His holistic research approach on cybersecurity is grounded in the reality that as sophisticated AI-led attacks become…...

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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 agents are moving from experimentation into production. As that happens, enterprises face a new set of challenges: How do you know agents are producing reliable results? Are they staying within policy? What are they costing? And how do you understand their behavior at scale?

At its recent conference, Splunk outlined how it is reimagining its platform around these questions, bringing together observability, AI-powered security operations, and its growing integration with Cisco.

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From Data to Agent Observability

Splunk has long built its business around helping organizations make sense of data. Now, that same capability is being applied to AI agents.

One challenge organizations face when deploying agents in production is ensuring that they remain reliable, compliant, and cost-effective. Splunk's new Observability Studio addresses this by focusing on understanding agent behavior and token usage.

The shift is important. As agents become more autonomous, monitoring traditional application performance is no longer enough. Organizations also need visibility into how agents operate, what they consume, and whether they are behaving as expected.

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Turning Context Into Action

Observability provides the context. The next step is turning that context into action.

Splunk is extending AI agents into security operations, where security analysts can use agents to support detection, investigation, response, and governance.

This points to a broader evolution in enterprise AI. Agents aren't simply generating information or assisting employees. They are increasingly being connected to operational workflows where their actions can have direct business and security consequences.

That makes visibility and control increasingly important.

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The Cisco Connection

Splunk's relationship with Cisco is another major part of the company's evolution.

Cisco acquired Splunk more than two years ago, and the integration has continued while Splunk remains available to its traditional customer base. Cisco customers can now discover Splunk capabilities through products including Cisco Command Center and AI Canvas.

The combination also gives Splunk access to Cisco's broad customer distribution, creating an opportunity to bring Splunk's data and observability capabilities to a wider enterprise audience.

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The Bigger Story: Data at Machine Scale

The next phase of AI will generate enormous volumes of operational data about how agents behave, what they consume, and what they accomplish.

That creates an interesting opportunity for Splunk.

Its traditional strength has been making sense of data. In the agentic era, that increasingly means understanding data generated at machine scale and using it to improve the reliability, security, governance, and economics of AI systems.

The question now is less about whether enterprises will deploy AI agents and more about how they will manage them once they are operating at scale.

Splunk is betting that observability will be a critical part of that equation.

Digital Safety, Privacy & Cybersecurity Data to Decisions cybersecurity Security Chief Information Security Officer On Event Update

Qualtrics Reimagines Experience Management: Simulation, AI and Decision Velocity

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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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…...

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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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For years, experience management has focused on a familiar question: How did the customer feel?

But AI is changing the question.

Now organizations can ask: What experience should we deliver? What outcome will it create? And can we test it before we act?

In this live conversation with Constellation analysts, Liz Miller, R “Ray” Wang, and Mike Ni explore Qualtrics' evolving vision for experience management and why simulation, data, AI, and feedback loops could fundamentally change how organizations make decisions.

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From measurement to prediction

Traditional experience management often begins after the experience has occurred. Organizations collect feedback, analyze sentiment, and use that information to improve the next interaction.

The opportunity now is to move experimentation before the action.

The conversation highlights Qualtrics' use of simulation and synthetic panels to test potential strategies without running every experiment against real customers. That creates an opportunity to explore more scenarios while reducing the cost and risk of experimentation.

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The rise of human experience intelligence

Data alone doesn't explain an experience. A customer may say they're frustrated with pricing when the real issue is delivery, lack of perceived value, or something else entirely.

That means organizations need to connect operational data to the human experience behind it.

The conversation points to this as an important gap for enterprise leaders. Systems can tell you that an escalation happened. They don't necessarily tell you why the customer experienced friction in the first place.

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From A/B testing to A-to-X

Traditional marketing experimentation has always had limits.You test a handful of variables, identify a winner, and assume the result applies broadly. Simulation changes the equation.

Instead of testing only a few scenarios with live audiences, organizations can explore a much broader range of possibilities and more granular customer segments before making a decision.

That creates something much more valuable than another optimization tool:

Decision velocity.

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The data problem doesn't disappear

Simulation and prediction only work if the underlying data is connected.

Many enterprises still operate with fragmented systems and disconnected data. The conversation describes the challenge as a "Franken stack," where information is scattered across systems and important inputs fall through the cracks.

Qualtrics' diagnostic approach is positioned around identifying those gaps and creating a more connected view of the customer experience.

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Experience becomes a business metric

Perhaps the biggest shift is moving beyond satisfaction scores and sentiment. The conversation points toward customer lifetime value and cost of engagement as more meaningful measures.

That changes the conversation for CMOs. Instead of asking whether a campaign generated a positive response, leaders can start asking:

• What drove the outcome?
• What did the experience cost?
• What will happen if we change it?
• What is the impact on lifetime value?

This turns experience from a measurement exercise into a business decision system.

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The new experience management

The most interesting part of Qualtrics' evolution may be that it isn't trying to become every system in the enterprise.

The vision discussed is about creating an intelligence layer that can simulate, predict, and deliver better outcomes across the systems organizations already use.

For enterprise leaders, that could mean a fundamentally different approach to experience:

Measure less. Understand more. Simulate before acting. Learn continuously.

And ultimately, make better decisions faster. That may be the next chapter of experience management.

Next-Generation Customer Experience Data to Decisions Marketing Transformation CX Data to Decisions Marketing Chief Information Officer Chief Marketing Officer On CR Conversations

Leading Through Turbulence: Empathy, AI Workflow Economics, and the New IT Playbook | DisrupTV Ep. 451

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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Leading Through Turbulence: Empathy, AI Workflow Economics, and the New IT Playbook | DisrupTV Ep. 451

In an AI-driven world that is turbulent, over-hyped, and deeply human all at once, the leaders who will define the next era are those who can hold empathy and decisiveness together — and who know the difference between deploying AI and actually monetizing it.

Maria Ross opens with the tension every modern leader feels but rarely names clearly: they are expected to support people and deliver results, often simultaneously and at speeds our brains were not built to sustain. She calls this the empathy dilemma — the struggle to balance genuine human support with the hard reality of performance, accountability, and decisions that will not please everyone.

Her reframe is important for analytically minded leaders who are skeptical of empathy as a leadership concept: empathy is not about being soft or touchy-feely. It is information gathering. It is understanding context well enough to make better decisions. As she puts it:

From hundreds of interviews and years of research, Ross distilled five pillars of empathetic and effective leadership. Self-awareness is the foundation — you cannot make space for others’ perspectives if your ego is filling the room. Self-care is next, because leaders who neglect their own energy and boundaries quickly become burned-out bottlenecks. Clarity is the third pillar — leaving people in limbo keeps them in fight-or-flight, which kills creativity and performance. Decisiveness is fourth: empathy is not about avoiding tough calls; it is about making hard decisions with an understanding of human impact and designing support around them. And finally, joy — the surprising pillar — because levity, camaraderie, and small moments of connection matter even in hard work.

Ross emphasizes one insight above the others: clarity is empathy. Ambiguity is not neutral. When leaders under-communicate strategy, rationale, or expected impacts, they leave people in survival mode. That is not kindness — it is abdication.

This is especially consequential in workforces that now span five generations, where assumptions about what professionalism means, how communication should flow, and what success looks like can differ dramatically. Leaders who over-communicate context and direction are not micromanaging. They are removing the friction that silently drains performance.

Three Actions for CEOs and Boards

Ross distills her advice for senior leaders into three concrete actions. First: take a beat and actually listen. Put the ego aside, resist the urge to hide behind a laptop or send another email, and use cognitive empathy — even without emotional investment — to understand what it is actually like from the employee’s point of view.

Second: lean into clarity as an act of leadership. Don’t assume shared definitions. Over-communicate the strategy, the rationale, and the human implications. Third: make tough decisions — but design them with human support built in. The question is not how to avoid a decision that hurts. It is how to help people through. Sometimes that is as simple as creating structured space for people to be heard before being redirected. Ignore this, Ross warns, and you are rowing against the current of human psychology and change fatigue, making your own job as a leader significantly harder.

What 9/11 and the Anthrax Attacks Taught About Leadership

David Bray brings a crisis-tested lens to empathy and leadership. On the morning of 9/11, he was scheduled to brief the CIA and FBI on technology responses to a hypothetical bioterror event. When the attacks happened, that planning became real-time crisis response — followed weeks later by the anthrax incidents that compounded the pressure on every national security and public health institution involved.

From those experiences, and from subsequent work in bioterrorism preparedness and national security, Bray surfaces several enduring lessons about what separates leaders who stabilize from leaders who compound the crisis.

People Bring Distraction and Fear to Work

Bray’s first lesson is one most organizations pretend is not true: employees arrive carrying global crises, local pressures, and personal worries in their heads. Leaders who design for the fiction of the fully-focused, undistracted worker create the conditions for tunnel vision, reactivity, and burnout. The reality of human cognitive load is not a HR problem. It is a leadership problem.

Without Joy, People Cannot Absorb What’s Coming

In turbulent environments, Bray actively watches for signs that his teams can still find moments of lightness. His reasoning is neurological as much as cultural:

That openness is not a nicety. It is the prerequisite for adopting new technologies, embracing new strategies, and resisting the doomerism that narrows what leaders believe is possible. This connects directly to Maria Ross’s fifth pillar: joy is not a soft add-on. It is a neurological enabler of learning and change.

Final Thoughts

This DisrupTV episode brings together four leaders whose work spans human psychology, national security crisis response, enterprise AI strategy, and M&A IT leadership — and finds a single coherent argument running through all of it.

Maria Ross and David Bray establish the human foundation: that leaders who ignore the neurological and emotional reality of the people around them are not just being unkind — they are making their own jobs harder. Clarity reduces the survival-mode thinking that blocks change. Joy and agency are not soft values; they are the prerequisites for the kind of openness to novelty that AI adoption and organizational transformation actually require.

Hiral Chandrana and Jason James translate that foundation into execution. AI value is not in the model — it is in the workflow economics that the model changes. IT leadership is not about infrastructure stewardship — it is about being a growth partner who speaks the language of outcomes. And no playbook survives first contact with reality unchanged, which is why grit, adaptability, and the willingness to say “I can” matter more than having all the answers at the start.

In an era with no historical precedent for what agentic AI is enabling, the leaders who will define what comes next are those who can hold empathy and decisiveness together, combine technical depth with human insight, and continuously bring their teams back to the question that David Bray asks in every crisis: why are we here, and where do we want to go — together?

Related Episodes

If you found Episode 451 valuable, here are a few others that align in theme or extend similar conversations:

• From Automation to Reinvention: Inside the Infinite Company and the Borrowed Mind | DisrupTV Ep 449
• How AI and Super Teams Are Redefining Customer Experience and Work | DisrupTV Ep. 450
• AI, Human Judgment, and Global Design: What It Takes to Lead in the Next Era | DisrupTV Ep 448

Data to Decisions Future of Work 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>

B2C Marketing Automation: Pegasystems Customer Decision Hub

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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Marketing automation has moved beyond sending the right message to the right customer.

In her latest Constellation ShortList spotlight, Liz Miller examines how B2C marketing automation is evolving from campaign execution to connected customer decisioning.

She spotlights Pegasystems Customer Decision Hub, which takes a pragmatic approach to AI:

• Use deeper reasoning when the decision requires it.
• Use deterministic automation when the decision is repeatable.
• And make decisions that are right for both the customer and the business.

The bigger shift? Marketing automation is becoming less about managing channels and more about making better decisions in context.

Constellation's current ShortList confirms Pega Customer Decision Hub as one of the 12 enterprise B2C marketing automation platforms on the 2026 list. View the full list here: https://www.constellationr.com/research/constellation-shortlist-b2c-marketing-automation-enterprise

Marketing Transformation Marketing Chief Marketing Officer On ShortList Spotlights

Dreamforce Predictions, Pragmatic AI, and the Rise of Decision Intelligence | CRTV Episode 138

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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This week's episode of ConstellationTV covers a lot of ground: a Big Debate on what to expect from Salesforce at Dreamforce, a ShortList spotlight on B2C marketing automation, a deep dive into Oracle's database and agentic AI strategy ahead of Oracle AI World, and a look at the fast-growing decision intelligence platforms market.

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Big Debate: What's Coming at Dreamforce

Two weeks out from Dreamforce, analysts Michael Ni, Holger Mueller and Esteban Kolsky debated where Salesforce stands heading into the conference. Ni argued that Salesforce enters this year's event in a stronger position than last year, noting that the SaaS thesis that AI would fully disintermediate platforms hasn't played out as some predicted. But he flagged a real risk: if Salesforce loses visibility into user clicks and voice interactions to AI intermediaries like Anthropic, it could lose ground in monetization.

Kolsky pushed back on the idea that Salesforce's self-service data advantage is enough to carry the platform. His take: Salesforce needs to double down on governance, execution, and agent management rather than trying to outcompete pure-play data platforms. He went further, predicting that Agentforce itself could be retired within two to three years if it doesn't deliver.

The debate ended without full agreement, but that's the format. Tune in over the next two weeks to see how the actual Dreamforce announcements measure up.

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ShortList Spotlight: B2C Marketing Automation

Analyst Liz Miller broke down what's changed in B2C marketing automation over the past two years. Her take: the category has moved well past list size, segmentation, and channel orchestration. Those capabilities are now table stakes. What separates ShortList-caliber vendors today is the ability to deliver connected customer experiences that drive durable, profitable relationships.

Miller spotlighted Pegasystems' Customer Decision Hub as a standout on this year's list, centering her analysis on the word "pragmatic." Pega's approach applies generative AI at design time, where deep reasoning justifies the cost, while keeping repeatable, high-volume decisions deterministic and automated rather than probabilistic. The result, in Miller's framing, is a platform built at the intersection of what's right for the business and what's right for the customer, rather than optimizing for one at the expense of the other.

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Oracle AI World Preview: Database Meets Agentic AI

Ahead of Oracle AI World, Constellation analysts Holger Mueller and R "Ray" Wang unpacked Oracle's recent wave of database and agentic AI announcements. The headline architectural decision: Oracle keeps transactional data inside the Oracle database rather than migrating it into a separate data lakehouse. Unstructured content is ingested into an Oracle AI Data Lakehouse, is vectorized by the Oracle AI Vector Database, and the resulting vectors are then written back to the transactional database. CIOs and CISOs favor this model because it avoids the need to recreate data security and governance profiles in a second system.

Other announcements covered included the AI Database Private Agent Factory for building agents directly on Oracle infrastructure, deterministic trusted answer search to eliminate the risk of hallucinations, voice-driven interactive reports in APEX that stay grounded in existing data, and MCP server support for both on-premises and cloud (autonomous AI database) customers.

The bottom line, as the analysts summed it up: Oracle's differentiation is that customers don't have to move or rearchitect their data to get agentic AI capabilities, while most competitors require exactly that.

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ShortList Spotlight: Decision Intelligence Platforms

Ray Wang closed the episode with Constellation's Decision Intelligence Platforms ShortList, a market he projects will reach $42.3 billion by 2031. These platforms run mission-critical, self-driving, self-healing business processes, spanning use cases like campaign-to-lead, procure-to-pay, and hire-to-retire, and trace their lineage back to RPA, process mining, BPM, and journey orchestration.

Wang spotlighted Celonis as one of the vendors on this year's list, highlighting its May 2026 acquisition of Ikigai Labs and the launch of the Celonis Context Model (CCM). The acquisition brings Ikigai's patented Large Graphical Model technology, MIT-backed research focused on tabular and time-series data, into Celonis' platform, adding real-time digital twin capabilities, scenario simulation, and dynamic planning on top of Celonis' existing process intelligence graph. Wang also noted the architecture's zero-copy integrations with AWS, Databricks, Microsoft Fabric, and Snowflake, delivering significant query performance gains.

As agentic workflows become more embedded in enterprise operations, Wang frames decision intelligence platforms as increasingly central to how businesses actually run, not a peripheral analytics layer.

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Decision Intelligence Platforms: How Celonis Enables the Autonomous Enterprise

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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AI is getting better at generating answers. The next challenge is getting it to make and execute decisions inside the systems that run the business. That's where decision intelligence comes in.

The latest Constellation ShortList for Decision Intelligence Platforms explores a new class of enterprise applications designed to continuously automate precision decisions across mission-critical processes. These platforms sit at the intersection of process mining, intelligent workflow, business process management, journey orchestration, and AI.

The opportunity is bigger than automating individual tasks. The goal is an autonomous enterprise where business processes can continuously learn, adapt, and execute with the appropriate level of human oversight.

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From insight to action

Decision intelligence platforms are designed to automate deterministic decisions with compliant execution while improving the precision of probabilistic decisions. That distinction matters.

Enterprise AI can't stop at telling someone what happened or recommending what to do next. It increasingly needs to understand the business context, determine the appropriate action, and orchestrate execution.

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Context becomes critical

Celonis is an important example of this shift.

With its acquisition of Ikigai Labs and the introduction of the Celonis Context Model, Celonis is bringing together process intelligence, operational context, forecasting, simulation, and AI together.

The broader idea is that enterprises need more than language models to understand how work gets done. They need models that understand the relationships, dependencies, processes, and operational conditions surrounding business decisions.

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The autonomous enterprise

As AI agents become embedded in enterprise workflows, decision intelligence becomes increasingly important.

Agents need context. They need recommendations. They need governance. And ultimately, they need a way to translate decisions into action. That makes decision intelligence less of a standalone AI capability and more of an emerging operating layer for the autonomous enterprise.

The companies that can connect context + decision + orchestration + execution will have a significant advantage as AI moves deeper into business operations.

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How Oracle Is Reinventing the Database for the AI Era

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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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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Capgemini

Analyst relations at Capgemini.&nbsp; ...

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