We have been saying it for years. Business analysts are the bridge between business and technology.
And honestly, it has always been true. BAs translate business needs into something delivery teams can act on. They sit in the middle and make sure the two sides understand each other. That matters. It has always mattered.
But here is what has changed: the nature of what sits on the technology side of that bridge just shifted fundamentally, and most organizations have not caught up to what that means.
For decades, the “technology side” was human developers, architects, and engineers. BAs learned to translate between business language and technical language. They learned to work across that divide. That was the skill.
Now there is AI on the technology side. Not just as a tool the developers use, but as an active participant in how organizations design, build, and deliver. AI is co-creating with business teams. It is generating options, drafting outputs, making decisions, and executing tasks. And the way humans and AI work together, the quality of that collaboration, the clarity of the handoffs, the design of the oversight, the alignment of the AI’s behavior with actual business intent, none of that is happening well in most organizations right now.
There is a massive gap. And BAs are almost perfectly positioned to fill it. So why are so many organizations not seeing that?
The Co-Creation Gap Is Real and It Is Growing
Let me describe what I am seeing in organizations that are moving seriously into AI.
They have teams deploying AI tools faster than anyone anticipated. Generative AI for content, agentic systems for process automation, AI-assisted development, AI-powered analytics. The technology is moving. But the organizational capability to work with that technology effectively, to define what the AI should do, how it should behave, where humans need to stay involved, what good output looks like and how to evaluate it, that capability is lagging badly.
This is the co-creation gap. It is not a technical gap. The engineers and data scientists are largely handling the technical side. It is a gap in the human-AI collaboration layer. Who is defining how the business and the AI system are going to work together? Who is designing the workflow where a human does part of the work and the AI does part of the work, and the handoffs between them are thoughtful and intentional? Who is establishing what the AI is supposed to optimize for, and checking whether it is actually doing that in practice?
In most organizations, the honest answer is: nobody is doing this well. It is getting patched together by IT teams who understand the technology but not the business context, or by business units who understand the context but not how to design human-AI collaboration effectively, or by consultants who drop in, produce a framework, and leave before it gets tested against reality.
The skill set that this gap actually requires is business analysis. Understanding what the business needs. Translating that need into something a system can act on. Designing the collaboration between humans and technology. Defining what success looks like and how to measure it. Managing stakeholder alignment around a changing process.
That is BA work. It has always been BA work. The context is new, but the core competency is not.
Tip 1: Understand What Co-Creation Actually Means and Name It
The first thing BAs need to do is get clear on what co-creation means in an AI context, because it is more specific than it sounds.
Co-creation is not just using AI tools to do your work faster. It is not AI generating a draft and a human editing it. Those are useful productivity gains, but they are not what I am talking about.
Co-creation, at the organizational level, is the design of how humans and AI systems work together to produce outcomes neither could produce as effectively alone. It involves defining what the AI contributes, what humans contribute, how the outputs of each feed into the other, where oversight happens, where decisions require human judgment, and how the system learns and improves over time.
Designing that well is complex. It requires understanding the business process deeply enough to know which parts benefit from AI and which parts require human judgment. It requires understanding the AI’s capabilities and limitations well enough to set realistic expectations and appropriate guardrails. It requires working with stakeholders to build trust in the AI-human collaboration, which is as much a change management challenge as a technical one.
When a BA walks into that work and can name it, can say “this is a co-creation design challenge and here is how I approach it,” they are positioning themselves in a way that is immediately legible to business leaders who are feeling that gap acutely. Leaders know the gap exists. They often do not know what kind of help they need. A BA who can name the gap and explain how they are equipped to close it is going to get attention.
It is a communication strategy. The BAs who learn to articulate their value in co-creation terms are the ones who will be invited into the conversations where that work is being figured out.
Tip 2: Step Into the Design of Human-AI Workflows Before Someone Else Does
Here is the uncomfortable reality. The co-creation gap is being filled. Just not by BAs in most organizations.
IT teams are making human-AI workflow decisions as implementation choices. Business leaders are making them as policy decisions. Vendors are making them as product decisions. In each case, the decisions are being made by people who are optimizing for something other than the alignment between business intent and AI behavior. And in each case, BAs could be adding more value than whoever is currently in that role.
The practical tip here is to stop waiting to be invited and start showing up with something useful.
If your organization is deploying an AI system of any kind, offer to map the human-AI workflow. Not the technical architecture, not the vendor evaluation, but the actual work: what does a human do, what does the AI do, where do they hand off to each other, what does the human need to know to evaluate the AI’s output, and what happens when the AI gets it wrong? That analysis is not being done rigorously in most organizations. A BA who produces it is immediately valuable.
If your organization is dealing with confusion about what the AI is supposed to do, which is nearly universal, offer to facilitate a session that clarifies the AI’s intended purpose, the business outcomes it is meant to support, and the criteria for evaluating whether it is achieving them. That is a requirements and alignment problem wearing an AI costume. You know how to solve it.
If your organization is struggling with stakeholder trust in AI outputs, offer to design a validation and oversight process. Define what human review looks like, what triggers escalation, what quality signals the team should be monitoring. That is governance and process design. You know how to do that too.
The point is not to claim expertise you do not have. It is to recognize that the analytical and facilitation skills you already have are exactly what these problems require, and to stop waiting for someone to formally invite you to apply them.
Tip 3: Make the Case to Your Organization That This Is a BA Role
The third tip is harder, and more important, than the first two.
Organizations are not automatically going to recognize that the co-creation gap is a BA problem. In fact, many organizations will continue to hand it to IT, or hire consultants, or treat it as a project management issue, unless a BA makes a clear and compelling case that this work belongs to them.
So make the case.
Not defensively, not as a turf argument, but as a genuine value proposition. The BA role has a set of capabilities that are specifically suited to the human-AI collaboration challenge. The ability to work across the business-technology divide. The ability to translate intent into operational design. The ability to facilitate alignment between stakeholders who have different mental models of what the AI should do. The ability to define success criteria and build monitoring mechanisms that tell you whether the AI is actually delivering value.
Those are not generic skills. They are BA skills. And they are exactly what the co-creation gap requires.
Part of why organizations are not seeing this is the visibility problem I mentioned earlier. BAs are often heads-down in documentation and traditional requirements work, doing what they have always done, while the AI strategy conversation is happening in a different room with different people. Getting into that room requires making the case proactively, which means having a clear articulation of why the BA perspective is essential to AI success.
Part of it is also a perception problem. Many business leaders still think of BAs primarily as requirements writers and process documenters. That perception is outdated, but it is sticky. Changing it requires BAs to show up differently, to lead with the co-creation framing, to demonstrate the broader analytical and facilitation value they bring.
This is leadership work. It is advocacy for the profession, done at the level of your own organization, in your own context. It is not comfortable for everyone. But the BAs who do it consistently are the ones who will still have growing, high-impact careers when the dust from AI disruption settles.
The Bridge Has Never Been More Necessary
Here is the thing about bridges. They become more important, not less, when the gap they span gets wider.
The gap between business intent and AI behavior is enormous right now. Organizations are deploying systems they do not fully understand, in service of outcomes they have not fully defined, with oversight mechanisms that are often insufficient for the stakes involved. The consequences of that gap are showing up everywhere: AI projects that do not deliver, stakeholder distrust in AI outputs, compliance exposure, customer experience degradation, and massive amounts of rework.
A skilled BA who positions themselves as the bridge across that gap, who can work with business leaders on what they actually need the AI to do, translate that into clear operational design, and then stay connected to whether the AI is delivering, is solving a real and urgent organizational problem.
This is the BA’s moment. Not because the profession is under threat and needs to find a new angle. But because the core work of business analysis, understanding needs, designing solutions, aligning stakeholders, measuring outcomes, is exactly the work that organizations need most right now in relation to AI, and most of them have not figured that out yet.
BAs who figure it out first will not have a hard time finding a seat at the table. The table will come looking for them.
Build Your AI Co-Creation Capability
If you want practical guidance on how to position yourself as a BA for the AI era, including frameworks for human-AI workflow design, co-creation facilitation, and making the organizational case for BA leadership in AI projects, I cover this in depth in my Maven course series.
This is where the BA profession is headed. I want to help you get there ahead of the curve.
Visit www.maven.com/angela-wick to explore current courses and upcoming cohorts.
The bridge has always been your role. It just got more important than it has ever been.