Trends in data science and business intelligence software (Q2 2025)

Software companies are on a collision course with AI. We’ve seen this transformation firsthand in data tools. Just a few years ago, the boundaries between tools were clearly defined: SQL-based business intelligence (BI) tools handled visualization and UI-based exploration, python-based notebooks powered data science research, and spreadsheets ran finance.

Those silos are breaking down. Platforms are converging, while simultaneously racing to add AI functionality. We’re increasingly seeing business adoption of text-to-SQL, agentic workflows, even AI generated analyses and visualizations spun from a natural language prompt.

At Ramp, we study how AI can help us build, explore, and ship insights at scale. We believe AI will dramatically reduce the cost of asking a question and tighten the loop from question to answer. As the “post-AI” data stack takes shape, we’re particularly excited about:

• Productivity gains for data teams, analysts, and stakeholders.
• Expanding reporting to include text, conversation transcripts, and other unstructured data.
• Agentic, generative products powered by proprietary datasets.
• Text-to-analysis (beyond text-to-SQL) with curated guardrails.
• A new generation of AI-native and LLM-native BI tools and vendors

We are still very early, of course. But one advantage of working at Ramp is that we have visibility into what’s actually happening in the market. We see, in real time, which vendors startups and incumbents adopt, renew, double down on, or abandon. We’re excited to share what we’re seeing.

Executive Summary

• Hex has more than doubled its share of BI spend since 2023, overtaking Power BI and ThoughtSpot, and is now in third place after Looker and Tableau.
• Incumbents still dominate overall: Looker, Tableau, and Power BI command 34% of total BI dollars, and their share has increased 6 percentage points since 2023.
• Notebook-native tooling and AI copilots are becoming standard features in BI tools, enabling data scientists to run ad-hoc analyses directly within broader dashboarding environments.
• Self-service matters: solutions that enable non-technical stakeholders to answer routine questions will save time for data teams.

1. Total spend flows

Looker and Tableau collect more than half of the total business intelligence dollars on Ramp cards and invoices. Power BI is a small player on dollars but leads on raw customer count thanks to its low effective price per seat. Conversely, Looker holds a disproportionately high share of spend relative to customer count, owing to relatively large contract sizes.

Still, the trend is clear: the combined share of spend for Looker and Tableau increased 6 percentage points from 2023, taking market share from offerings like Domo and ThoughtSpot. Other offerings, like Hex, grew over the same period.

2. Startups are picking Hex and Sigma

Among startups, Hex now takes 25% of BI spend, up from 9% in 2023. Users cite three reasons:

1. One workspace for exploration and dashboarding: Analysts can explore data, draft narrative, and publish an interactive dashboard without switching tools.
2. Lower switching costs: Hex’s notebook style is familiar and portable. Dashboards are markdown. New users can onboard quickly.
3. AI assistance by default: Hex’s built-in AI assistant writes SQL, explains errors, and suggests next queries. Effective usage of AI is fundamental to a data science workflow.

3. Decision framework for buyers

Buyers can evaluate BI tools on these key qualities that differentiate software offerings.

4. Methodology

Ramp analyzed anonymized card and bill pay transactions from 30,000+ businesses using Ramp. Software vendors were tagged using proprietary company models that analyze receipt and invoice data and match them to a vendor. Companies were tagged as startups using proprietary company models that analyze third-party data sources and spending trends.

For more insights, follow Ramp Head of Data Ian Macomber (X and LinkedIn) and Ramp economist Ara Kharazian (X and LinkedIn)

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