Self-service BI fell short for modern businesses
For years, we heard a lot about Self-Service Business Intelligence (BI) being the path forward. It wasn’t a bad idea, build tools that let any business user access and analyze data without always needing an analyst or data scientist. The goal was solid: remove bottlenecks and speed up decision-making.
But in execution, it left a lot on the table.
Self-service BI didn’t break down the real barriers. It assumed that non-technical teams could make immediate use of complex data tools. But most of those solutions, catalogs, dashboards, and portals, never truly met users where they are. Interfaces were clunky. Data wasn’t always up-to-date, and many users had to wait anyway or guess their way through reports they didn’t fully trust.
This broke the original promise. Data was supposed to be democratized, available to marketers, product leads, and frontline managers instantly and clearly. But what many got instead was another layer of confusion, or worse, a new kind of delay. Without highly specialized support, most users weren’t able to extract the insights they needed fast enough to act.
David Seidl, a CIO who tracked these problems in real-time, noted that success in BI hinges on how well casual users, not just data experts, can discover and make sense of information in context. When platforms failed to offer this, the “self-service” part became a misnomer.
If you’re leading at the executive level, it’s important to recognize this: access isn’t enough. Real value comes from rapid, clear insights that shift decision-making speed in competitive markets.
AI has amplified the demand for data-driven decision-making
Artificial Intelligence didn’t start the pressure, it escalated it. Today, AI’s influence across marketing and customer-facing roles has made data-driven decision-making non-optional. Most marketing and customer experience leaders already feel it.
According to Salesforce Tableau, 93% of customer service and 83% of marketing leaders say AI has made them even more reliant on accurate data. There isn’t room anymore to make decisions based on instinct alone, especially when your competitors are automating, optimizing, and iterating at scale. Leaders are expected to justify their decisions quickly and with evidence.
But here’s the conflict: Despite the growing dependency on insight, only a minority of leaders feel their data strategies actually match their priorities. Less than half say the way they collect, manage, and access data aligns with their business needs. So you end up with a paradox. A high-tech environment demanding more agility and precision, while leadership is stuck waiting, unsure, or competing internally just to defend a proposal with facts.
Tableau’s Chief Product Officer, Southard Jones, summed it up clearly. He said leaders are under increasing pressure to deliver value with data, but disconnected systems and heavy tools are hurting their confidence. In fact, 75% of business users feel they must prove their worth using data, and 57% feel like they’re in direct competition with peers for data-driven validation. That sense of internal rivalry was even stronger at the executive level.
If you’re sitting on the executive team, that should catch your attention. The demand for data isn’t slowing down. It’s not enough to ask your teams to “be more data-driven.” You need to invest in streamlined systems that make reliable insights easy to access and use. Otherwise, the data you have quickly becomes a source of delay, rather than a driver of action.
Data literacy gaps and misaligned data strategies
The value of data has never been higher. But when most leaders still don’t trust the information in front of them, or their ability to use it, it points to a deeper failure in strategy and education.
Research from Tableau shows this clearly: while 63% of business leaders are expected to find, analyze, and interpret their own data, 54% are not confident doing so. These are experienced professionals working inside mature companies, yet they feel unequipped to extract actionable insights. That gap slows teams down and weakens core decision-making at every level.
The problem isn’t just technical, it’s strategic. Many organizations have data strategies that don’t align with how decisions actually get made. That includes how they collect data, how it’s stored, who has access, and whether that access comes with any guidance. Without trust in the data’s relevance, accuracy, or timeliness, leaders are left guessing. That guesswork impacts speed, clarity, and long-term outcomes.
C-suite leaders must treat this as a structural issue. It’s not enough to warehouse large volumes of data or adopt advanced tools. If the culture doesn’t support data literacy, and if systems don’t close the loop from data capture to usable insight, then you’re not really data-driven. You’re just collecting.
This is the point where leadership makes the difference. Fixing the disconnect between data capabilities and business priorities requires attention at the top. Executives need to champion data education and push for tools that foreground clarity, not complexity.
Agentic AI offers a promising solution
We’re now entering a new phase. Agentic AI is a shift in how businesses access and activate insight. These AI agents aren’t static dashboards or pre-defined reports. They’re built to search, reason, and respond. That’s critical when you’re working in a market that doesn’t wait.
Agentic AI draws from structured and unstructured data, connects it with operational context, and returns answers in real time, often in plain, natural language. This means executives, marketers, operations leads, any decision-maker, can ask questions and get immediate, accurate feedback without relying on a specialist to translate the data. Errors shrink. Waiting disappears. Insight quality improves.
Southard Jones, the Chief Product Officer at Tableau, pointed out that AI agents can now identify patterns humans might miss, and surface trends before they become obvious. The product Tableau launched recently takes steps in that direction, focusing on real-time, trusted insights for all users, not just analysts or engineers.
This evolution matters for CMOs and other frontline leaders. Agentic AI can support highly personalized marketing, real-time adjustments in customer engagement, and data-backed decisions that tie directly to ROI. It doesn’t require users to understand how the data is modeled on the backend. What it provides is clarity, at speed, and at a scale that traditional BI tools couldn’t deliver.
This changes the entire conversation. Instead of building better dashboards, you’re deploying agents that act more like operational partners, running in the background, enhancing awareness, and accelerating actions. For companies that move fast and scale under pressure, this is a critical advantage.
Successful AI depends on executive support and data literacy
New tech doesn’t scale itself. Agentic AI has the potential to change how companies work with data, but without executive backing and education, it stalls before it starts. Many organizations make the mistake of rolling out advanced tools without preparing teams to actually use them. That creates resistance, misalignment, and missed ROI.
Adoption will only succeed with strong leadership and a data-literate workforce. You don’t need everyone to be a data scientist. But you do need teams that can ask the right questions and trust the answers. That trust comes from two things: a culture that understands data fundamentals, and leadership that makes smart, visible decisions using those same systems.
When people at the top don’t use the tools that drive decisions, or can’t explain how AI fits into company priorities, it undermines credibility. The best systems in the world won’t deliver results if the organization doesn’t know how to interpret, apply, and scale the insights.
This is a leadership challenge, not just a systems upgrade. Frances Frei and Anne Morriss pointed this out in their book, Move Fast and Fix Things. According to them, the most effective leaders solve problems at speed, but also carry the responsibility to ensure employee and customer success during change. That balance is central now. You’re not only implementing AI, you’re setting expectations for how people across departments trust and act on its output.
To be clear: Agentic AI isn’t optional if your competitors are already using it. But successful implementation means putting the right foundation in place. Executive sponsorship, clear goals, and internal training aren’t side efforts, they’re what make the tech stick. Without those, even the most advanced AI ends up underused and undervalued.
Main highlights
- Self-Service BI hasn’t delivered on speed or accessibility: Despite early hype, self-service BI tools failed to provide timely, user-friendly access to data, especially for non-technical users. Leaders should reassess reliance on legacy BI systems that reinforce bottlenecks rather than remove them.
- AI elevates pressure on marketing and CX leaders to be data-driven: The rise of AI has increased demand for accurate, fast decision-making, yet most data strategies don’t match business needs. Executives must align data infrastructure with real-time operational demands to stay competitive.
- Data literacy and strategy misalignment undermine performance: Over half of leaders lack confidence in interpreting their own data, despite being expected to do so. Companies should invest in organization-wide data literacy and ensure their data strategy is directly tied to decision workflows.
- Agentic AI enables faster, broader access to business insight: Agentic AI integrates complex data and delivers real-time insights in natural language, making advanced analytics accessible to more users. Leaders should explore Agentic solutions to reduce friction and speed up critical decisions.
- Without executive backing, Agentic AI adoption will stall: Advanced tools require cultural readiness and leadership buy-in to succeed. C-suite executives must champion data literacy, model usage, and set clear objectives to unlock the full value of AI-driven decision support.
