What was standing in the way
Abacus Insights had the ambition to become an AI-led organization. What it needed was the structure to get there.
Successful AI pilots are one thing. Building an operating model that scales AI consistently, governs it responsibly, and embeds it into how the organization works over the long term is another problem entirely.
Without a deliberate foundation - governance, operating models, engineering standards, and organizational readiness - AI initiatives would remain isolated. The goal was enterprise-wide capability, not a portfolio of individual experiments.
The solution in production
DCT established a fully operational AI Center of Excellence that gave Abacus Insights the governance structures, operating models, engineering capabilities, and organizational readiness required to scale AI across the enterprise.
The CoE created clear ownership of AI initiatives, defined standards for responsible deployment, and built the internal capability to evaluate, deploy, and optimize AI at scale - without depending entirely on external partners.
Governance was embedded from the start: accountability frameworks, compliance controls, and human oversight mechanisms designed for a healthcare technology environment where those things aren't optional.
The agents behind the deployment
AI Center of Excellence design, operating model development, AI strategy, workforce enablement, and enterprise adoption frameworks.
AI governance frameworks, compliance controls, accountability structures, and responsible AI deployment standards embedded into the CoE operating model.
What changed
- Long-term AI operating model that scales across the enterprise
- Enterprise governance framework enabling responsible AI adoption
- Scalable innovation capability built on internal expertise
- Organizational readiness for sustained AI-led growth