In the first half of 2026, traditional BI market leaders Tableau and Qlik both appointed new leaders and added agent analytics capabilities to their platforms. Meanwhile, former Tableau and Google executives have publicly launched two AI-native analytics startups. At the heart of this movement is the recognition that the work and technology needs of data analysts are fundamentally changing in the AI era.
BI and analytics vendors as a whole are adapting to a new reality where AI models can generate insightful analysis and high-quality data visualizations from a few well-written prompts, and where AI agents can autonomously analyze data and take actions based on the results. But the changes in Tableau and Qlik are particularly noteworthy from both a management and strategic perspective.
Mike Capone, who served as CEO for eight years after Qlik was acquired by private equity firm Thoma Bravo, resigned rather abruptly in April. It took several weeks for Qlik to announce a replacement. Saugata Saha will assume the role of president and CEO on July 31.
Mr. Saha joins Qlik from the buy side of S&P Global, leading the S&P Global Market Intelligence business unit and serving as the company’s first Chief Enterprise Data Officer. But Saha is certainly familiar with AI-related data issues, given his role as a CDO and his market intelligence arm providing clients with AI tools and AI-enabled financial datasets. “The critical challenge in enterprise AI is to make data reliable, connected, and adaptable so that it can operate in any environment,” he said as part of the Qlik hiring announcement.
Tableau’s leadership changes were even more fundamental. Salesforce, which has owned Tableau since 2019, eliminated the BI and data visualization vendor’s sole CEO role in February after former leader Ryan Aytay left to join an AI code translation startup backed by Salesforce’s venture arm. Instead, 12-year Salesforce veteran Mark Recher has been named executive vice president and general manager of Tableau.
Similarly, AI-driven changes in the analytical process, particularly the rise of agent analytics, are less pronounced for Qlik and its customers than for Tableau and its users.
Strategic transition to agent analytics
Qlik released Agent Experience in February and enhanced agent analytics capabilities in April. However, under Capone’s leadership, the company expanded dramatically through acquisitions and built a full-featured data management and analytics platform with AI as a strategic focus. Qlik Cloud Analytics and Qlik Sense on-premises analytics software are on the front end, but by no means dominate the stack. As Saha’s comments demonstrated, Qlik data analysts already work in environments primarily focused on providing semantically rich, high-quality data to AI models and agents.
Tableau’s business risk is greater because much of its success is based on its loyal and dedicated BI user base. This is informally called of data fam: A community of users who primarily define the way they work by the features Tableau provides, especially 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 evident at industry events and online forums.
Now, Tableau is repositioning its software as an agent analytics platform. In the vendor’s words, it’s no longer just an analytical tool, but an “advanced knowledge and decision-making engine for agent enterprises.” In a May Q&A with TechTarget, Recher looked forward to the role of DataFam members, saying the role of Tableau users is evolving “from data analyst to knowledge architect to decision architect to agent analytics architect.” In the vendor’s view, analysts are essentially moving from creating visualizations to building trusted AI knowledge that can drive large-scale business decisions.
But will users remain loyal to Tableau through this tipping point? Another potential point of contention for Salesforce is that, by revoking the CEO title and incorporating Tableau into its broader data and AI organization, Salesforce has signaled that the future of the Tableau platform will likely be more integrated into its Agentforce agenttic AI environment.
AI-native analytics alternatives
New AI-centric analytics options are emerging as potential alternatives.
Francois Agenstad, former chief product officer at Tableau, was the most prominent executive DataFam turned to for guidance before retiring in 2023, becoming CPO of product and web analytics vendor Amplitude. After leaving Amplitude at the end of 2025, Ajenstat brought his new business, 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 investment, bringing its total seed funding to $21 million.
Golden CEO Ajenstat clearly sees an opportunity to develop a new community, an alternative DataFam, including 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, who previously worked at Google and BI vendor Looker, which Google acquired in 2020. The startup offers Orion, an autonomous AI analyst built on a semantic layer that incorporates the unique thinking behind Looker into a new generation of software.
Balance traditional and AI-driven analytics
Incumbent vendors like Tableau and Qlik have broad and deep integrations with data platforms and operational applications that remain, as industry insiders often say, “locked” within existing user accounts. Migrating to a new platform is also costly and disruptive for customers.
However, the need to maintain their existing user base makes it difficult for Tableau and Qlik to completely transform their UX to support modern AI-driven analytics. You need to maintain the commitment of current enterprise buyers while enabling data analysts and business users to use new AI-focused tools in self-service BI environments.
This is a difficult balancing act that gives new vendors like Golden and Gravity an opportunity to capture experienced BI specialists who are dissatisfied with the direction of their current platform, as well as new analysts who want to develop their skills and careers in an AI-native environment.
However, all BI and analytics vendors today face the same fundamental challenges. In other words, can we move beyond AI models that can reproduce more functionality with each new iteration? The answer for each vendor, in its own way, is to become the tool or platform of choice and participate in a collaborative community of users. This creates new opportunities for analytics leaders to reevaluate vendor commitments and select the right technology to lead their organizations into the AI era.
Donald Farmer is a data strategist with over 30 years of experience, including leading product teams at Microsoft and Qlik. He advises clients around the world on data, analytics, AI and innovation strategies, leveraging his expertise across technology giants and startups.
