GenAI
Fast-Track Transformation:
AI Workforce Skilling in < 2 Months

50%

Increase in Use Case Identification

40%

Reduction in AI Hiring Costs

4.8/5

Average Participant Satisfaction Scores

Background

A leading healthcare insurance provider faced increasing pressure to stay competitive in a rapidly evolving digital landscape. While the organization had a highly skilled workforce that was well-versed in existing systems, it was becoming evident that there was a significant gap in expertise related to generative artificial intelligence (GenAI). 

This skills gap created bottlenecks, hindering the company's ability to scale programs and successfully address complex challenges. In an industry where innovation is key, the company was at risk of falling behind and missing out on the transformative potential of AI.

Further compounding this challenge, the federal government issued a Binding Operational Directive (BoD), mandating the organization to enhance its workforce's proficiency in GenAI.

The Challenge

The healthcare insurance provider recognized that maintaining the status quo was no longer sustainable. Acquiring GenAI capabilities became an urgent priority to drive digital transformation and comply with the BoD. 

However, after an in-depth evaluation, the organization found that hiring external talent with specialized GenAI skills would be costly and time-consuming. The onboarding process, from recruitment to full integration into in-house systems, was projected to take six to eight months—time the organization did not have to wait.

Solution

The healthcare insurance provider opted for a more efficient and cost-effective solution: upskilling its existing workforce. The company partnered with Revature, leveraging the company’s proven expertise in workforce transformation.

PHASE 1
Requirement Review
PHASE 2
Training Program Development
PHASE 3
GenAI Training Program Integration

Revature’s GenAI subject matter experts conducted a thorough review of the organization's requirements

PHASE 1
Requirement Review
PHASE 2
Training Program Development
PHASE 3
GenAI Training Program Integration

A six-week, customized training program tailored to the company’s specific business goals. The program included:

  • Development of an intake persona to match the organization’s existing tech stack and operational processes.
  • A comprehensive skills assessment to identify existing gaps and prioritize learning needs for GenAI upskilling.
  • Tailored training consisting of a blend of expert-led and interactive, tech-supported learning experiences, ensuring a dynamic and engaging approach.
  • A capstone project that utilized real-world business scenarios to allow participants to apply their newly acquired GenAI skills in practical contexts.
PHASE 1
Requirement Review
PHASE 2
Training Program Development
PHASE 3
GenAI Training Program Integration

Revature seamlessly integrated the GenAI training program into the organization's learning & development (L&D) platforms to maximize impact. Additionally, dedicated office hours and ongoing support were provided to ensure success.

Results

Revature’s GenAI workforce training program was a game-changer for the healthcare insurance provider. Within six weeks, the organization upskilled more than 40 people across the IT and business teams. By focusing on upskilling its internal teams, the organization achieved significant outcomes such as:

  • A dramatic increase in use case identification across core business functions, allowing the organization to unlock new opportunities for leveraging AI.
  • A significant reduction in costs compared to hiring GenAI experts from the external job market, demonstrating a more sustainable and budget-friendly approach.
  • An impressive participant satisfaction score, reflecting the program’s high quality and relevance to participants’ needs.

According to the organization’s senior IT director – AI: “Revature provided a high-quality, curated and cost-effective solution for skilling our workforce on GenAI so that we are better prepared to unlock the potential.”

50%

Increase in Use Case Identification

40%

Reduction in AI Hiring Costs

4.8/5

Average Participant Satisfaction Scores

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