Humanizing Business Intelligence in the Age of AI: Defining the Analytics Experience

March 14, 2026 (Happy “Pi” Day)

For years, we treated UI, UX, and CX as separate design disciplines. UI was the interface. UX was the journey. CX was the broader relationship. In analytics, all three still matter, but AI changes the equation. I keep coming back to this idea: AX = (UI + UX + CX) × AI.

To me, AX stands for Analytics Experience. The Analytics Experience is not just about whether a dashboard looks good or whether a report loads quickly. It is the full experience of how analytics is presented, discovered, consumed, trusted, acted upon, measured, and improved over time. I believe AX is more than a design concept. It is also a business discipline.

The Analytics Experience sits at the intersection of marketing, strategy, ownership, and transparency. Marketing shapes how analytics is positioned and made desirable. Strategy determines whether analytics is aligned to business priorities. Ownership forces clarity around who is accountable for the experience, not just the platform. Transparency gives leaders visibility into what is working, what is being ignored, and where value is actually being created. I keep repeating Analytics Experience and AX. AX is the missing layer between analytics investment and analytics value.

This thinking is directly connected to something I have guided by for years: Humanizing Business Intelligence. Most BI programs have historically been built from the inside out: data first, architecture first, tool first, dashboard first. Those things matter, but if the end result is fragmented, confusing, underused, or disconnected from how people actually work, the business intelligence may be technically sound and still commercially weak. Humanizing Business Intelligence means creating an Analytics Experience that feels usable, relevant, transparent, measurable, and valuable.

That is where AI becomes so important. I do not see AI as replacing UI, UX, or CX. I see it as multiplying them. At its best, AI makes the Analytics Experience more adaptive, more personalized, more predictive, and more actionable. A static analytics environment says, “Here is the dashboard. Go figure it out.” A stronger Analytics Experience says, “Here is what matters most right now, what changed, why it matters, and what you may want to do next.” That is not just better reporting. It is a better experience.

I'll admit I haven't fully figured out where that line is yet…  but I know ignoring it is the wrong answer. This is why our AI Agent or “Concierge” is named Pie, with Personal Insights Enabled…

One of the biggest mistakes organizations still make is treating analytics experience as an accidental byproduct of the BI platform they bought, the dashboards they launched, or the AI pilot they announced. But AX should be treated as an operating discipline. The Analytics Experience determines whether people come back, whether trust grows, whether insights turn into action, and whether leaders can defend ROI. In that sense, AX is not soft. It is operational.

If AX matters, it must also be measurable. That is one reason I developed The Analytics Experience Score. The idea is to move beyond vague opinions about adoption and measure the actual quality and momentum of the Analytics Experience. The four dimensions are Recency, Frequency, Consumption, and Monetary. In simple terms: how recently analytics is used, how often it is used, how deeply it is consumed, and what business value may be associated with that usage. That creates a far more meaningful conversation than raw login counts or dashboard vanity metrics.

This is also where Usage360 and MyAnalytics come in. If The Analytics Experience Score provides a framework for measuring AX, then Usage360 provides the telemetry and visibility behind it. It helps answer a question too many organizations still cannot answer clearly: what is actually being used, by whom, how often, and with what potential value? MyAnalytics addresses the other side of the challenge. If Usage360 helps measure the Analytics Experience, MyAnalytics helps package and present it so the experience feels coherent, guided, and personalized rather than like a scattered pile of dashboards, reports, links, and prompts. Measurement without presentation is incomplete. Presentation without measurement is guesswork. AX requires both.

There is also a bigger scenario coming, and I believe it may become one of the most strategic extensions of AX. Today, AI is part of the equation because it helps improve the Analytics Experience. But soon, organizations will also need to understand how consumers are actually using the AI tools now being deployed alongside BI. Once companies begin measuring the usage of copilots, assistants, agents, and embedded AI features alongside dashboards and reports, they will gain a much clearer view of the changing Analytics Experience across the enterprise. That is where AX becomes even more strategic.

All of this is why I keep coming back to PieAX. To me, PieAX is not just a platform name. It is a point of view. PieAX — Defining the Analytics Experience means taking the Analytics Experience seriously as a strategic, measurable, AI-enabled discipline. In my view, the next era of business intelligence will not be defined only by better tools or more AI. It will be defined by better Analytics Experiences.

That is the shift I see coming. Humanizing Business Intelligence means creating analytics experiences that people not only can use but want to use. I believe AX and the Analytics Experience are becoming central ideas for the next era of BI and AI. And I believe AX and the Analytics Experience are becoming central ideas for the next era of BI and AI.

Happy “Pie” Day too! ☺

Jonathan CherisFounder, PieAXPieAX — Defining the Analytics ExperienceHumanizing Business Intelligence

Please note that Usage360®, MyAnalytics®, The Analytics Experience Score™, PieAX – Defining the Analytics Experience and Humanizing Business Intelligence® are all submitted or registered trademarks of PieCart LLC dba PieAX.

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