Navigating Change Management in the Modern Commerce Era

For years, global brands approached digital transformation like a software install: Buy the platform, flip the switch, declare victory. Migration complete, box checked, on to the next initiative.

But ecommerce isn't a side channel brands dabble in alongside "real" retail anymore. It's often the main growth engine.

At the same time, AI is rewriting how shoppers discover, evaluate, and buy products, from agentic shopping assistants to AI-generated search results that bypass the traditional storefront altogether. The result is that digital transformation is now a continuous, organization-wide change, where the tech stack is actually the easy part.

The harder part is the people and process work behind it: how teams align, how decisions get made, how change actually sticks. Where change management used to be a tack-on to digital transformation, it’s now becoming the determining factor in whether transformation works at all.

The Digital Transformation Finish Line Doesn't Exist Anymore

The legacy approach to digital transformation followed a familiar arc: Scope the project, select the platform, migrate the data, train the team, go live. Transformation was “complete” once the new system was up and running

That model worked fine back when technology only changed every so often, in big, clearly defined jumps. It doesn't make sense anymore.

AI capabilities are advancing on a near-continuous basis, which means there's no single finish line to cross. The platforms brands adopt today will look different in six months, and the workflows built around them will need to evolve right along with them.

That changes what actually separates winning brands from the rest. As Lauren Livak Gilbert, executive director of The Digital Shelf Institute (DSI), put it, if every brand has access to the same technology, what differentiates you is "the decisions you make and how you execute them."

In other words, the software was never the advantage. Buying the same AI tools as your competitors gets you to the same starting line. What separates the brands that pull ahead is how well their people and processes can absorb continuous change, make good calls quickly, and actually execute on them.

Why Change Management Is Now Mission-Critical

If technology isn't the differentiator, what is?

Increasingly, it's how well an organization manages the human side of change. At the 2026 Digital Shelf Summit (DSS), Livak Gilbert was direct about this: Change management isn't a nice-to-have as brands roll out AI; it's a must-have.

Her guidance for leaders is practical and people-first:

• Share real examples of what's working;
• Open up honest dialogue about how roles are evolving;
• Identify change champions inside the organization who can model adoption for their peers; and
• Actually measure whether adoption is happening rather than assuming it will.

It's easy to roll out a new tool and call the rollout itself a success. It's harder (and more important) to track whether people are actually using it, trusting it, and changing how they work as a result.

This is also where alignment becomes a competitive advantage in its own right. Ashley Becker, vice president of global ecommerce capabilities at Kraft Heinz, described it well during a DSS panel: Momentum and alignment create the pathway for teams to move forward with “speed, direction, and focus."

Without that alignment, even the best technology will be implemented badly and unevenly across teams, or everyone will revert to the old way of doing things.

In other words, this is a culture problem, and it takes ongoing, deliberate effort to keep everyone aligned before transformation actually sticks.

Feeding the Machines: Why Content Needs Are About To Explode

There's another change coming, too: The sheer volume of content needed to compete.

As AI agents become a bigger part of how shoppers discover and evaluate products, brands need to feed those systems far more detailed, structured product information than a typical product detail page (PDP) ever needed.

Livak Gilbert put a number on it at DSS: She expects content needs to grow 5x to meet the demands of agentic systems.

This increase in content volume can't be solved by simply asking existing teams to do more of what they're already doing. It requires a total rethink of how content gets created, approved, and distributed in the first place.

That means putting together cross-functional teams now, before the demand fully hits, rather than scrambling to restructure once it does.

It also means leaders need to get ahead of a narrative that can otherwise breed anxiety: AI isn't here to replace the people doing this work. As Livak Gilbert noted, the real threat isn't replacement; it's that the work itself changes.

People, Process, Technology: The Framework That Holds It Together

If all of this sounds like a lot to coordinate, it is, which is why having an explicit framework is key.

Jason O'Toole, head of connected commerce and media at Gildan, offered one: people, process, and technology, in that order.

• People come first. For O'Toole, that means being deliberate about hiring and upskilling as AI changes what the job actually requires, rather than assuming existing teams will absorb new responsibilities by osmosis.
• Process comes next. Building workflows that can actually function across competing departmental priorities, multiple brands, and both internal teams and external agencies.
• Technology comes last because it only works once the people and process pieces are in place. Tools are enablers of a strategy, not a substitute for one.

O'Toole also offered a useful reframe of where AI fits into all of this. Rather than treating it as a threat to human judgment, he argued AI will actually force organizations to become more human by freeing people from repetitive manual work so they can focus on the kind of thinking machines can't do.

And he was candid about what actually drives adoption: It's not messaging or mandates. It's visible, in-market use cases that show teams exactly what AI can do and what kind of output it produces.

5 Things To Do This Year To Get Ahead

None of this needs to stay abstract. There are concrete steps you can take to put people-first change management into action:

1. Start by naming change champions, aka people on each team who are early adopters, well-respected by their peers, and willing to model what good AI adoption looks like in practice.
   
   
2. Create an ongoing feedback loop. A recurring forum, office hours, or even a simple Slack channel where teams can ask questions, flag friction, and see issues actually get addressed.
   
   
3. Set adoption metrics. Knowing how many people logged into a new tool says little about whether it's actually changing how work gets done. Track whether teams are using it to make better or faster decisions.
   
   
4. Build a context layer of clean, structured product content. As content needs scale toward that 5x mark, brands need product data that's organized and detailed enough for both humans and AI agents to act on it accurately.
   
   
5. Before rolling anything out org-wide, pilot it. Pick one team, one workflow, one use case, and let the results speak for themselves. As O'Toole's experience suggests, adoption follows proof.

It Was Never About the Software

Digital transformation was never really about the software. It succeeds or fails based on how well an organization manages the human side of change: whether people trust the new way of working, understand why it's happening, and have a clear path to get there.

The new agentic era is the biggest test yet. It means preparing your product data and your teams for what's next in AI-fueled growth. And the brands that treat it as a people and process challenge, not just a technical one, will be the ones that come out ahead.