There is a version of the BA role that organizations will always deprioritize when budgets get tight, headcount gets scrutinized, or AI tools get good enough to automate another chunk of familiar work.
And there is a version of the BA role that leaders protect fiercely, because losing them would create real problems.
The difference between those two versions is not tenure, certification, or even domain expertise. It is positioning. BAs who are seen as documenters will struggle to justify their existence. BAs who operate close to decisions, driving clarity, surfacing evidence, and shaping what gets built and why, become part of the organization’s strategic infrastructure.
Getting from one to the other requires deliberate pivots. Not slow, gradual drift, but conscious decisions to change where you add value and how you show up on a team.
In an AI age and in working with BAs navigating this shift, I have seen three pivots make the biggest difference. They are practical, actionable, and available to any BA who decides to pursue them.
Pivot 1: Use Data Evidence to Drive Intake and Prioritization Decisions
Most BAs enter the picture after prioritization has already happened. The business has decided what it wants. The backlog has been shaped. The BA’s job is to go figure out the details.
That is a legitimate function. It is also a limiting one, especially in the age of AI.
The BAs who become irreplaceable are the ones who shape prioritization conversations. The practical pivot here is about how you frame your work at intake. Before a team starts debating what to build next, there are questions that should be answered: What problem are we actually solving? What evidence tells us this is the right problem to prioritize? How does this initiative connect to the organization’s strategic goals? What does success look like, and how will we measure it?
In practice, this might look like leveraging AI and pulling usage data before a feature enhancement gets prioritized, or synthesizing customer feedback to reframe a vague business request into a specific, measurable problem. It might mean creating a simple one-page brief that captures the problem definition, the supporting evidence, and the connection to organizational strategy, and making that brief a standard part of how intake decisions get made.
Small habit shifts, compounded over time, change how the organization thinks about what BAs are for.
Pivot 2: Use Rapid AI Prototyping to Surface Misaligned Assumptions Early
Rapid AI prototyping is one of the most powerful tools available to a BA who wants to close the assumption gap early. The idea is straightforward: instead of spending weeks in document-based requirements definition, create something the business team can actually see, touch, tap, click, and react to. Get feedback before significant investment has been made. Correct misaligned assumptions when correction is cheap.
AI tools now make it possible to produce working prototypes, interactive mockups, and realistic simulations of system behavior in hours rather than weeks. That changes the economics of early discovery completely. A BA who knows how to leverage these tools can create a concept prototype during an initial discovery session and walk stakeholders through it the same day.
The reaction you get from a stakeholder looking at an actual working prototype is categorically different from the reaction you get reviewing a requirements document. People know almost immediately whether what they are seeing is what they wanted. They see edge cases they forgot to mention. They notice missing functionality. They realize that what they asked for is not quite what they need.
Getting that reaction in week one instead of week eight is the goal.
It also means shifting your mental model of what a BA deliverable looks like during discovery. A functional prototype that generates ten specific pieces of corrective feedback from business stakeholders is more valuable than a polished requirements document that no one argues with because no one can fully visualize what it describes.
The goal of early discovery is not to document what the business said it wants. The goal is to find out what the business actually needs, as fast as possible, so the team can build the right thing.
Pivot 3: Define Performance Signals and Create a Monitoring Rhythm
Most BA work has a clear end point. The project closes, the system launches, the team moves on. The BA’s involvement wraps up right around the time anyone would be able to tell whether the thing that got built is actually working.
That is a missed opportunity on multiple levels.
BAs who build a practice around performance monitoring do something fundamentally different. They define what “working” looks like before a solution is built, ensure the right measurement infrastructure is in place to track it, and then stay connected to performance data over time to guide continuous improvement. They turn their involvement from project-based to outcome-based.
This matters because organizations are increasingly focused on outcomes, not outputs. Shipping a feature is not success. Achieving a measurable improvement in customer satisfaction, process efficiency, decision quality, or business performance is success. A BA who helps define and track those outcomes is part of the value chain all the way through.
The practical pivot here starts at the beginning of a project, not the end. When you are doing intake and discovery work, define the business and user performance signals alongside the requirements.
Over time, this practice positions the BA as a continuous improvement driver. You become the person who brings performance evidence to prioritization conversations, which circles back to Pivot 1.
Why These Three Pivots Work Together
These pivots are not independent skills. They form a reinforcing cycle.
Data-driven intake ensures that work is prioritized based on evidence, not opinion. Rapid prototyping ensures that what gets built actually solves the problem that was prioritized. Performance monitoring ensures that organizations learn from what was delivered and apply that learning to what comes next.
A BA who has built all three into their practice is operating at a fundamentally different level than one who has not. They are upstream of the decisions that matter. They are accelerating learning and reducing rework. They are making the organization smarter about how it invests its delivery capacity.
That is not a commodity function. That is a strategic function, and the BAs who occupy it are very hard to replace.
The Path Forward Is a Choice
None of this requires waiting for permission. You do not need a new job title, a new team, or a formal role change to start making these pivots. You need to decide that this is how you are going to work, and then start making the small, deliberate choices that move you in that direction.
Ask to be part of intake conversations earlier. Start building a prototype during your next discovery session instead of writing a requirements summary. Spend twenty minutes at the end of your next project defining what monitoring would tell you whether it succeeded.
Small moves, made consistently, change what people come to expect from you. And what people expect from you shapes the role you occupy.
The BA profession is not in decline. It is in transition. The BAs who navigate that transition intentionally, who make deliberate pivots toward strategic value, will be the ones who look back five years from now and realize that the disruption was the best thing that ever happened to their career.
Ready to Go Deeper?
If you want structured guidance on building a future-ready BA practice, these pivots and many more are covered in depth in my Maven course series. You will get practical frameworks, real-world scenarios, and a community of BAs working through the same challenges alongside you.
Visit www.maven.com/angela-wick to explore current courses and upcoming cohorts.
The version of the BA role that organizations cannot afford to lose is built on purpose. It starts with a decision to pursue it.