Client Success Story

Background

We partnered with a global Life Sciences company to launch a strategic initiative to drive adoption of a developed AI solution.

The solution was designed to help users better understand and explore data across the company's enterprise data platform. The solution enabled business and technical users use AI to interrogate the data more efficiently.

The company needed support to rollout the solution and drive the adoption across its stakeholders.

Company size

Revenue

Scope

10,000+ employees

$10B+

AI solution adoption

The Challenge

Most users were new to AI-enabled tools and lacked a clear understanding of how to interact with the solution effectively. Users struggled to translate business questions into well-structured AI prompts. Without strong prompting, the solution responded in vague, incomplete, or overly broad requests producing inconsistent or unusable outputs. This eroded trust in the AI solution and reinforced reliance on traditional, manual data request processes.

These adoption challenges were compounded by the complexity of the enterprise data platform. Users were often unsure which data sources to reference, how data was structured, or how to validate AI-generated results.

In addition, stakeholders required clear guardrails around data security, access controls, and responsible AI usage. Without practical guidance, hands-on support, and a clear operating model, users lacked confidence in both the AI solution and their own ability to use it effectively.

Timeframe

Adoption Challenge

Considerations

6 months

Business terminology and complicated data ecosystem

• Compliance

• Security

• Response accuracy

Our approach

We implemented a delivery-led AI adoption program focused on practical usage, skill building, and sustained behavior change. The approach began with identifying high-value ad hoc data use cases and mapping them to real user workflows, ensuring the AI solution addressed day-to-day business needs.

To build user capability, we delivered interactive, role-based workshops that taught core AI concepts and hands-on prompting strategies, including how to structure questions, provide context, reference data sources, refine outputs, and validate results. We created a curated prompt library with reusable templates and examples—such as exploratory analysis, trend identification, data quality checks, and executive-ready summaries—tailored to the company’s data platform and governance requirements.

To reinforce adoption, we established ongoing office hours, coaching sessions, and live use-case support, allowing users to bring real ad hoc requests and receive guided assistance in real time. We also embedded governance and trust guardrails directly into prompting guidance and workflows, helping users understand what data could be accessed, how results should be interpreted, and when escalation was required. Combined with targeted change management and stakeholder alignment, this hands-on approach improved output consistency, increased user confidence, and enabled scalable, self-service adoption of the AI solution.

Approach

Measuring adoption

Solution enhancements

AI adoption program focusing on up skilling and hands on support

Defined adoption key performance indicators to measure progress

Added solution enhancements to drive adoption and value

Key Client Successes

By combining hands-on enablement, structured prompting guidance, and embedded governance, the program increased AI adoption, reduced time to insight, and enabled scalable, self-service analytics for users within the enterprise

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