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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. Meanwhile, former Tableau and Google execs publicly launched two AI-native analytics startups. At the heart of these moves is a recognition that the work of data analysts and their technology needs are fundamentally changing in the AI era.
BI and analytics vendors as a whole are adapting to the new reality in which AI models can generate insightful analyses and high-quality data visualizations from a few well-written prompts, and AI agents can autonomously analyze data and take actions based on the results. But the transitions at Tableau and Qlik are particularly notable, from both management and strategic perspectives.
Mike Capone, who had been Qlik’s CEO for eight years following its acquisition by private equity firm Thoma Bravo, resigned rather abruptly in April. It took Qlik several weeks to announce a replacement: Saugata Saha, who will start as the company’s president and CEO on July 31.
Saha joins Qlik from the buyer’s side of the table at S&P Global, where he has led the S&P Global Market Intelligence business unit while also serving as the company’s first chief enterprise data officer. But Saha is certainly familiar with AI-related data issues, due to his CDO role and the Market Intelligence division’s offerings of AI tools and AI-ready financial datasets to its customers. “The defining challenge in enterprise AI is making data trusted, connected and adaptable enough to work across any environment,” he said as part of Qlik’s hiring announcement.
Tableau’s management change was more radical. Salesforce, which has owned Tableau since 2019, eliminated the BI and data visualization 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 instead named executive vice president and general manager of Tableau.
Likewise, 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.
A strategic shift toward agentic analytics
Qlik released an agentic experience in February and increased its agentic analytics capabilities in April. But under Capone’s leadership, the company expanded dramatically through acquisitions, creating a full-featured data management and analytics platform with AI as a focal point of its strategy. Qlik Cloud Analytics and the Qlik Sense on-premises analytics software are at the front end, but by no means dominate the stack. As Saha’s comment indicated, Qlik data analysts already work in an environment mostly focused on delivering semantically rich, high-quality data to AI models and agents.
The business risk is greater for Tableau because much of its success is built on a deeply loyal and committed BI user base. It informally calls this theDataFam: a community of users who largely define their work practices by the capabilities Tableau provides, especially for data visualization. Many users were concerned that the Salesforce acquisition would dilute Tableau’s core value proposition, at least for them. Their discomfort is still palpable at industry events and in online forums.
Now, Tableau is repositioning its software as an agentic analytics platform — no longer just an analytics tool, but “a high-scale knowledge and decision engine for the agentic enterprise,” in the vendor’s words. In a May Q&A with TechTarget, Recher put a positive spin on that for DataFam members, saying the role of Tableau users is evolving “from a data analyst to a knowledge architect to a decisions architect to an agentic analytics architect.” In the vendor’s view, analysts are essentially moving up from creating visualizations to architecting trusted AI knowledge that can drive business decisions at scale.
But will users remain loyal to Tableau through this turning point? Another possible bone of contention for them: By retiring the CEO title and folding Tableau into its broader data and AI organization, Salesforce has signaled that the Tableau platform’s future is likely to be more integrated into the company’s Agentforce agentic AI environment.
AI-native analytics alternatives
New AI-centric analytics options are emerging as potential alternatives.
François Ajenstat, Tableau’s former chief product officer, was the most prominent executive the DataFam looked to for guidance before his departure in 2023, when he became CPO at product and web analytics vendor Amplitude. After leaving Amplitude in late 2025, Ajenstat brought his new venture, Golden Analytics, out of stealth in April. This month, the startup launched a public beta of its AI-native analytics software and announced additional venture capital investments, bringing its total seed funding to $21 million.
Ajenstat, Golden’s CEO, clearly sees an opportunity to develop a new community — an alternative DataFam, if you will — that includes former users of Tableau and other analytics vendors who want a modern BI platform unencumbered by legacy architecture.
Similarly, a startup named Gravity raised $7 million in new seed funding in April, bringing its total to $10 million. Gravity was co-founded by CEO Lucas Thelosen and CTO Drew Gillson, both formerly of Google and BI vendor Looker, which Google acquired in 2020. The startup offers Orion, an autonomous AI analyst built on a semantic layer that takes the original thinking behind Looker into a new generation of software.
Balancing traditional and AI-driven analytics
Incumbent vendors such as Tableau and Qlik have a breadth and depth of integrations with data platforms and operational applications that keep them “sticky,” as people in the industry often say, within existing user accounts. Migrating to a new platform is also expensive and disruptive for customers.
However, the need to hold on to their existing user base makes it difficult for Tableau and Qlik to fully transform their UX to support modern AI-driven analytics. They must keep current enterprise buyers committed, while also enabling data analysts and business users in self-service BI environments to work with new AI-focused tools.
It’s a tricky balancing act that 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 develop their skills and careers in an AI-native environment.
However, all BI and analytics vendors now face the same fundamental challenge: Can they stay ahead of AI models that can reproduce so much of their functionality with each new iteration? The answer for each vendor, in its own way, is to become a tool or platform of choice and engage a supportive community of user peers. For analytics leaders, this creates new opportunities to reevaluate vendor commitments and choose the right technologies to bring their organizations into the AI era.
Donald Farmer is a data strategist with 30-plus years of experience, including as a product team leader at Microsoft and Qlik. He advises global clients on data, analytics, AI and innovation strategy, with expertise spanning from tech giants to startups.
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