In the first half of 2026, Tableau and Qlik - two traditional BI market leaders - both named new top executives and added agentic analytics capabilities to their platforms. At the same time, former Tableau and Google executives publicly launched AI-native analytics startups, signaling a fundamental shift in how data analysts work and what technology they need.
Management upheaval at Qlik and Tableau
Mike Capone, who had been Qlik's CEO for eight years after its acquisition by private equity firm Thoma Bravo, resigned abruptly in April. The company took several weeks to name Saugata Saha as his successor; Saha will start as president and CEO on July 31. He joins from S&P Global, where he led the Market Intelligence business unit and served as the company's first chief enterprise data officer.
Saha's background in AI-related data issues is clear. "The defining challenge in enterprise AI is making data trusted, connected and adaptable enough to work across any environment," he said in Qlik's hiring announcement.
At Tableau, the change was more radical. Salesforce, which has owned Tableau since 2019, eliminated the BI vendor's standalone CEO role in February after former leader Ryan Aytay left to join an AI code-translation startup backed by Salesforce's venture arm. Mark Recher, a 12-year Salesforce veteran, was named executive vice president and general manager of Tableau.
A strategic shift toward agentic analytics
Qlik released an agentic experience in February and expanded its capabilities in April. Under Capone, the company had built a full-featured data management and analytics platform through acquisitions, with AI as a focal point. The AI-driven changes in the analytics process - in particular, the rise of agentic analytics - are less marked for Qlik and its customers than for Tableau and its users. Qlik data analysts already work in an environment focused on delivering semantically rich, high-quality data to AI models and agents.
The business risk is greater for Tableau because its success rests on a deeply loyal user base. Many users feared that the Salesforce acquisition would dilute Tableau's core value, and that discomfort persists. Now, Tableau is repositioning its software as "a high-scale knowledge and decision engine for the agentic enterprise," in the vendor's words. In a May Q&A, Recher said the role of Tableau users is evolving "from a data analyst to a knowledge architect to a decisions architect to an agentic analytics architect."
But whether users stay loyal through this shift remains an open question. By retiring the CEO title and folding Tableau into Salesforce's broader data and AI organization, the company signaled deeper integration with its Agentforce environment - a move that could unsettle the existing community.
AI-native analytics alternatives
New AI-centric options are emerging. François Ajenstat, Tableau's former chief product officer, launched his venture Golden Analytics out of stealth in April. This month, the startup opened a public beta of its AI-native analytics software and announced additional venture capital investments, bringing total seed funding to $21 million. Ajenstat, Golden's CEO, aims to build a new community - an alternative to the Tableau DataFam - for users who want a modern BI platform unencumbered by legacy architecture.
Similarly, a startup named Gravity raised $7 million in new seed funding in April, for a total of $10 million. Co-founded by former Google and Looker executives Lucas Thelosen and Drew Gillson, Gravity offers Orion, an autonomous AI analyst built on a semantic layer that brings the original thinking behind Looker into a new generation of software.
Balancing traditional and AI-driven analytics
Incumbent vendors like Tableau and Qlik have deep integrations with data platforms and operational applications that keep them embedded in existing accounts. Migration to a new platform is expensive and disruptive. Yet the need to retain their current user base makes it hard for them to fully transform their user experience for AI-driven analytics. They must keep enterprise buyers committed while also enabling data analysts and business users to work with new AI tools.
This balancing act gives new vendors like Golden and Gravity an opening to win over experienced BI specialists frustrated with the direction of their current platforms, as well as new analysts looking to build careers in an AI-native environment. All BI vendors now face the same challenge: staying ahead of AI models that can replicate much of their functionality with each new iteration. The answer for each is to become a tool of choice and engage a supportive community of users.
Why this matters for executives and strategy
For executives overseeing data and analytics teams, the transitions at Tableau and Qlik signal that the BI tools their organizations rely on are being reshaped by AI. The emergence of AI-native startups like Golden and Gravity introduces new options for building analytics capabilities without legacy constraints. Staying informed on these shifts is critical for making sound technology investments. Resources on AI for Executives & Strategy can help leaders track these developments, while the changing role of data analysts connects directly to the broader evolution covered in Data Analysis.
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