Visibility is not the same thing as movement
Business intelligence teams often get rewarded for shipping dashboards, automating reports, and improving visibility. Those things matter. But visibility alone does not create value.
A chart is only useful if it changes a decision, clarifies ownership, or speeds up action. Otherwise, it is just a more polished way to observe the business from a distance.
The current market is making this gap more obvious
Wavestone's 2024 Data and AI Leadership Executive Survey found that 87.9% of leaders now see data and analytics as a top organizational priority and 62.3% say the same about generative AI. But the survey also makes an important point: integrating data and AI into traditional business processes and company culture still takes time and real commitment.
The World Economic Forum's Future of Jobs Report 2025 reinforces the human side of that challenge. Analytical thinking remains the top core skill employers want, while AI and big data continue to rank among the fastest-growing skills.
McKinsey's 2025 work on AI in the workplace adds a similar lesson from another angle. The challenge is not mainly technological. It is a business challenge centered on where to deploy the tools, how to redesign work, and how to help people use them effectively.
Put together, the message is clear: organizations do not need more reporting theater. They need better decision systems.
What a decision system looks like
A strong BI function does more than publish metrics. It defines:
- which decisions matter most
- who owns them
- which signals should trigger action
- how often teams review them
- what tradeoffs sit behind the numbers
- what happens next when a threshold is crossed
That is very different from a dashboard graveyard that looks impressive and changes nothing.
AI raises the standard here
As AI lowers the cost of producing dashboards, summaries, and first-pass analyses, reporting output becomes easier to generate.
That does not make analysts less important. It makes weak operating models easier to spot.
If a team still does not know what decisions the dashboard supports, AI will just help them produce misaligned output faster. If a team has clarity on decision paths, ownership, and business context, AI becomes leverage.
What this means for hiring
The strongest analytics and BI candidates will increasingly be the ones who can connect metrics to motion.
They know how to:
- frame a decision before they build a report
- choose the KPI that matters rather than the one that is easiest to show
- explain tradeoffs clearly to stakeholders
- design reporting that leads to action, not passive visibility
- use AI to accelerate work without outsourcing judgment
Why this matters to me
The analytics work I care about most sits close to execution. I like building systems that make it easier for teams to see what is changing, understand why it matters, and decide what to do next.
That is why I think the future of BI is not dashboard production. It is decision design.
Research notes
- Wavestone, 2024 Data and AI Leadership Executive Survey
- World Economic Forum, Future of Jobs Report 2025
- McKinsey, Superagency in the workplace: Empowering people to unlock AI's full potential