Action at Tableau Conference 2026 | Full Coverage

Tableau’s Trevor Hall Talks AI Architecture

Action’s Keith Helfrich sits down with Trevor Hall, Chief Architect over Tableau and analytics products at Salesforce, for one of the most technically consequential conversations of TC26. They explore where Tableau fits in a world of conversational analytics and AI agents, why governance and semantic layers are becoming ever more important, and how new capabilities like composable data sources, Knowledge Graphs, and the Knowledge Engine may shape the next generation of enterprise analytics.

The Conference Beneath the Conference

In this post-TC26 thought piece, Keith reflects on the split-phase moment emerging across the analytics industry. While keynote messaging focused heavily on agentic AI and autonomous analytics, the strongest practitioner reactions came from workflow improvements, composability, governance, and friction reduction. The piece explores why AI is exposing long-deferred structural problems inside organizations, and why operational coherence, semantic consistency, and shared understanding may become the real competitive advantage of the next decade.

From Tableau to Collective Intelligence with Ashley Howard Neville

Ashley Howard Neville joins Keith Helfrich to discuss Tableau, AI, collective intelligence, data governance, and why human context still matters in modern analytics. A thoughtful conversation about where the industry may be headed next.

Opening Up Tableau with Thomas Nhan

At the conference, Keith sat down with Thomas Nhan, Director of Product at Tableau, for a wide-ranging conversation about where analytics platforms are heading in an AI-first era. The discussion explores Tableau’s evolution toward API-first and “headless BI” architectures, the challenge of unlocking business logic trapped in legacy XML structures, and the growing tension between flexibility, governance, and enterprise-scale performance. Keith and Thomas also examine why human creativity, judgment, and narrative-building still matter, even as AI agents become increasingly embedded in analytics workflows.

Actionauts Respond to the TC26 “True to the Core” Session

Keith and Jonathan unpack Tableau’s “True to the Core” session at TC26, examining how Tableau leadership is responding to mounting pressure from AI disruption, partner competition, and shifting customer expectations. The conversation explores Tableau’s renewed defense of dashboards as a shared organizational reality, its push toward openness and extensibility, new licensing flexibility across the Salesforce ecosystem, and the ongoing tension between AI-assisted workflows and traditional analytics craftsmanship. Along the way, Keith and Jonathan reflect on software quality improvements, semantic interoperability, and what Tableau’s evolving identity may mean for analysts and enterprise data teams moving forward.

Tableau’s Role in the Era of AI

In this video, Keith and Tableau’s VP of Product Management, Matthew Miller, discuss the fundamental shifts occurring in the analytics industry as it transitions from traditional “drag-and-drop” methods to a new era of conversational AI. Reflecting on over a decade of Tableau’s evolution, Matthew talks about how the core mission of helping people see and understand data remains unchanged for Tableau, even as the “love languages” of data interaction expand to include natural language and AI agents.

Action’s TC26 Devs on Stage Reaction

Keith Helfrich and Jonathan Drummey’s unpack the TC26 Devs on Stage presentations, from long-awaited composable data sources to the crowd’s surprisingly loud enthusiasm for quality-of-life improvements like layers, dark mode, vector exports, and dynamic formatting. The conversation also explores the growing gap between Tableau’s future visions of agentic AI and the practical realities of governance, enterprise deployment, and day-to-day dashboard work.

Action’s TC26 Keynote Reaction

Keith and Jonathan’s immediate reaction to the TC26 keynote: a tighter, more grounded presentation with clearer product direction, a strong push toward AI and action-oriented analytics, and new leadership that signals credibility, But there are still some real open questions around vision, real-world adoption gaps, and whether Tableau’s future leans GUI-first or truly code-first. A solid step forward, but the deeper story is still unfolding.

Is Tableau Still the Future of Analytics?

In this interview, Keith Helfrich sits down with Cristian Saavedra Desmoineaux to talk about whether Tableau still has a place in an AI-driven analytics world. The answer is less about dashboards and more about its evolving role: Tableau as the “last mile” where business logic lives, decisions get shaped, and data becomes usable.

Cristian talks with Keith on the real costs of direct-to-warehouse querying, the continued advantage of Hyper for performance, and how AI tools like LangChain and MCP servers extend rather than replace Tableau. The future analyst, in Cristian’s view, isn’t purely technical or business-focused, but a generalist who can bridge both with AI as powerful leverage.

What to Look For at Tableau Conference 2026

Last year’s pre-conference episode of The Sensemakers unexpectedly became one of our biggest TC moments, pulling in more than 11,000 views and sparking conversations online and on the conference floor.

Keith Helfrich, Jonathan Drummey, Robert Rouse, and Stephen Price wrestle with what may be the biggest question facing Tableau right now: can it evolve into an AI-ready platform, or are agents and code-native tools pulling the industry somewhere else?

This fascinating, far-ranging conversation covers AI agents, governance, ontology, APIs, dashboards, metadata, and the growing “augment vs. replace” tension happening inside analytics teams everywhere. It’s part strategy discussion, part future-casting session, and part live processing of an industry that suddenly feels very different than it did even a year ago.

Jonathan Drummey’s Sessions (and More) at TC26

Actionaut and Tableau rockstar, Jonathan Drummey will be giving two presentations at this year’s Tableau Conference.

What is Tableau Good For?

What is Tableau Good For? offers a reframing of the Tableau question in the age of AI. As the barrier to analysis disappears, Keith Helfrich outlines the real choice facing data leaders: up-level Tableau into a structured, governed system, or transition to a code-first analytical operating model.

Actionauts Are on the Ground!

Keith Helfrich and Jonathan Drummey wasted no time after getting to San Diego over the weekend. They have already done interviews with Technology Architect and Tableau Visionary Cristian Saavedra Desmoineaux and Tableau’s Marketing Manager, Matthew Miller. Look for those videos soon. They are both eye-opening and informative conversations.

Data+Women Pre-Game TC26

Action is proud to be a sponsor of The Moxy Foundation’s Data+Women Pre-Game TC26 on Monday, May 4, at the San Diego Wine & Culinary Center, 7pm – 9pm.

“The Data+Women Pre-Game is a joyful, community-led, annual tradition that kicks off Tableau Conference with heart. Over 200 data professionals gather to (re)connect and celebrate the women shaping the future of data. It’s an evening for laughter, inspiration, and treasured face-to-face moments. It’s joyful. It’s affirming. And it matters”

Keith and a href=”https://www.linkedin.com/in/jonathandrummey/”>Jonathan will be there. If you’re there, find them and say “hi.”

Tableau: The Business Logic Gray Box

As AI reshapes the analytics landscape, Actionauts will be using Tableau Conference 2026 as an opportunity to reflect not just on Tableau, but on where analytics is heading and where The Action Company believes modern data organizations need to go next.

In Tableau: The Business Logic Gray Box, Jay Farias explores a growing shift in analytics architecture: moving business logic out of Tableau dashboards and into governed, testable code layers.

Documentation First

What if the real AI advantage has less to do with prompts and more to do with structure?

In this piece, Robert Rouse argues that the teams getting the most from AI aren’t simply using better tools. They’re documenting how they think. Style guides, business logic, SQL patterns, governance rules, definitions of “done,” all of it becomes the upstream structure that makes AI outputs reliable instead of chaotic.

The result is a shift from experimenting with AI to building systems that can actually scale, sustain, and be trusted.