Three Out of Four Enterprises Admit They’re Making Crucial Business Decisions in the Dark, New Sisense Research Shows

Sisense, the leader in AI-driven analytics that transforms enterprise data into a competitive edge, released a new study that reveals a dramatic shift toward embedded analytics as organizations struggle with current data solutions. The research, in conjunction with UserEvidence, shows that while 78% of professionals lose up to half their workday to digital friction, 80% now see invisible, embedded analytics as critical to their organization’s future success.

The findings, included in the Sisense 2025 State of Analytics report, uncover a pivotal moment for enterprise data strategy: despite significant investments in analytics infrastructure, businesses are pivoting toward more seamless, user-focused solutions that integrate directly into workflows. This move comes as 53% of organizations expect more than half of their workflows to be AI-assisted by 2026, creating urgent demand for analytics that work invisibly alongside employees rather than requiring specialized expertise.

Marketing Technology News: MarTech Interview with Adam Brotman, Co-Founder and Co-Ceo @ Forum3

Key Findings: The Data Disconnect

• Digital Friction Wastes Time, Energy, Resources: Over three-quarters (78%) of respondents report losing 10–50% of their workday to digital friction. In a typical 1,000-employee organization, up to 10,000 hours are lost each week simply searching for the right data.
• Decisions Made in the Dark: 76% admit they’ve made business decisions without consulting available data because it was too difficult to access, creating a concerning gap between data availability and data-driven decision-making.
• Confidence Outpaces Reality: While 81% of organizations believe they have good or full control of their data, nearly two-thirds (64%) acknowledge they can’t reliably access it for decision-making.
• Innovation on the Backburner: Analytics-related bottlenecks delayed product releases for more than half (56%) of organizations in the past year. Nearly half (46%) report that three to five potential product innovations were delayed or abandoned due to analytics integration challenges.
• AI Initiatives Stalled: Two-thirds (66%) have identified AI use cases that remain unimplemented due to integration challenges (32%), cost concerns (24%), or data quality issues (21%).

The Future: Embedded, AI-Driven Insights Unlock New Potential
The survey reveals that organizations are rapidly moving toward more accessible, integrated analytics solutions:

• 80% say invisible or ambient analytics will be very important or critical to their organization’s future
• 70% believe no-code analytics development is essential for business growth
• 77% consider white-label analytics capabilities critical for maintaining brand experience
• When asked what they would focus on if analytics were seamlessly integrated, organizations identified improving customer service (30%), developing new products (27%), and pursuing strategic initiatives (23%)

Marketing Technology News: Drip Marketing: What it is – A Complete Breakdown

“While companies have invested millions in data infrastructure, they’re now recognizing that value isn’t created by having data — it’s created when insights are seamlessly available at the decision point,” said Andrew Loomis, Sr. Director of Global Field Services at Sisense. “The more people have to find the insights, the less likely they are to succeed. Embedded analytics should be as effortless as checking your phone’s battery — when it’s low, you get an alert. The same should be true for your business: decision-makers need timely notifications when something needs attention, not hope they can find it during their next business review.”

The massive shift towards an integrated solution underscores the growing need for Analytics Platform as a Service (AnPaaS) — which combines business intelligence (BI) with advanced AI, robust APIs, and flexible data tools within a modern architecture to deliver personalized insights and intuitive analytical experiences within products and workflows.