How Jasmine Jaco is testing AI business cases against real work

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3 mins

Industry

Healthcare · Medical devices

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How Jasmine is leading Al Work Design

Meet Jasmine Jaco, VP, Organization Transformation & HR Strategy at Boston Scientific

Jasmine spent most of her career in management consulting, leading large-scale global transformations anchored in business strategy and value delivery. Along the way she launched startups and built an experience innovation practice.

At Boston Scientific she leads AI organization transformation, covering work and role redesign, and is building the HR capabilities needed to lead that change across the business.

 

The initial estimate looked promising: AI agents could free up around four hours a week for each sales representative. Then Boston Scientific’s team sat down with the people actually doing the work.


Customer preparation involved information the proposed agent hadn’t accounted for. Some of the administrative work included in the savings calculation wasn’t happening consistently in the first place. For Jasmine, the experience showed why understanding work matters before making promises about what AI will improve.

Getting close enough to understand the work

One early lesson was about scope. Trying to address the entire enterprise at once would stretch limited expertise too thin. A meaningful area of work offered somewhere to learn, refine the approach and demonstrate what redesign could accomplish.

Sales provided a revealing example. The team examined preparing for customer calls, conducting them and documenting interactions in the CRM. But job descriptions and high-level conversations could only take them so far. They described broad responsibilities without revealing the information, systems and individual practices involved.

Letting employees test the assumptions

Working with Reejig, Boston Scientific looked beyond job descriptions to how work actually happened. Breaking the work into tasks and subtasks, alongside the people doing it every day, changed the picture.

Sales reps prepared for calls using information scattered across different places, including their own phones, so the initial agent couldn’t give them everything they needed. Many reps also weren’t consistently recording meetings in the CRM. The estimate had counted savings against work that, in some cases, wasn’t being done, and requiring that documentation could actually add time.

Employees’ knowledge exposed gaps in both the workflow and its business case. The progress was a clearer understanding of what needed to change and which assumptions could withstand scrutiny.

Making room for judgment in the redesigned workflow

Jasmine is also helping teams account for the work AI creates: reviewing outputs, applying judgment, correcting problems and remaining accountable for the result. Under pressure to show productivity gains, those steps are easy to compress or skip.

People also need experience to recognize when an output is wrong, so decisions about what to automate need to consider how employees build that expertise. Research and presentations can generate interest, but practical examples make work design tangible.



Proof points create belief.


 

The transformation story

How Boston Scientific grounded AI investment in real work

Test the assumptions behind AI opportunities
Early AI opportunities raised a practical question: did the proposed changes reflect how people actually worked? The team needed to test both the workflow design and the projected time savings.
Build a shared view of work with Reejig
Reejig’s WorkOS provides a common view of work across business units, roles and regions. Alongside employees’ knowledge of tasks and subtasks, it helps the team assess opportunities and avoid redesigning the same work twice.
Bring the expertise together in one team
An AI transformation pod combines work design, technology, data, AI enablement, business expertise and program management, prioritizing by reach, frequency, effort, risk, employee impact and cost.
“Work redesign and employee support are considered together from the beginning.”
Separate real savings from new responsibilities
The sales review showed why better documentation and time saved must be measured separately, and why teams need to account for the time people spend reviewing AI outputs.
What’s next: connect changes across the workforce
Jasmine wants the shared Work Architecture to connect changes across roles and regions to workforce needs over three to five years. Linking those insights to strategic workforce planning remains work in progress.

What other leaders can take from this

Lessons for leaders

01
Proof points create belief
Redesign a real area of work and show the outcome. That changes minds faster than research.
02
Involve the people who know the work
Bring them in before the business case is approved, not after.
03
Design time for judgment
Build review, correction and accountability into the redesigned workflow so they don’t get squeezed out.

Behind the transformation

How Jasmine worked with Reejig to test AI business cases against how work actually happens.
A platform like Reejig, I think that’s a lot of the value that you bring because it’s really challenging to be able to otherwise surface all of those insights at an enterprise level in a large, complex global organization. Otherwise you’re making those decisions without data.
Jasmine Jaco Boston Scientific
Learn how leaders like Jasmine use Reejig to understand work, prove value and scale AI work design. Book a demo →