LEAP Consulting Group, a technology advisory and delivery firm specialising in regulated industries, announced the expansion of its enterprise AI practice. The firm is deepening its capabilities across Revenue Operations, Finance Operations, Customer Success Operations, and regulated-industry AI applications with a structured approach that ensures organisations build AI on a foundation that can actually support it at scale.

The AI Maturity Assessment: Know Exactly Where You Stand

At the centre of LEAP’s AI practice is a proprietary AI Maturity Assessment - a free, structured diagnostic that evaluates organisations across seven core dimensions: data readiness, strategic alignment, AI usage modes, technology infrastructure, governance and risk, talent and culture, and investment value realisation. The assessment produces a scored, staged maturity profile across five levels - Foundational through Leading and a prioritised investment roadmap calibrated to each organisation’s industry and functional depth.

“Most organisations are earlier in their AI journey than they believe,” said Josh Kramer, Managing Partner at LEAP Consulting Group. “The challenge is not access to models - it’s whether the underlying data, systems, and operating models can support AI at scale. Our free maturity assessment gives clients a scored, honest baseline before capital is committed.”

Enterprise AI Capabilities: Where Automation Delivers the Highest Return

LEAP’s AI practice is built around the enterprise functions and industries where AI-driven automation delivers the most immediate operational and financial return. Capabilities include:

Agile Product Development: sprint planning and Program Increment (PI) implementation, backlog refinement, CI/CD pipeline automation, MVP scope definition and build enablement, and Agile governance with compliance-aligned SDLC

CloudOps / DevOps / SecOps / RiskOps: cloud migration across AWS, Azure, and GCP; infrastructure-as-code and containerization; CI/CD orchestration; observability and monitoring; SOC2, HIPAA, and HITRUST compliance readiness; and automated risk and compliance reporting

Revenue Operations (RevOps): pipeline automation, forecasting, and AI-driven sales intelligence

Customer Success Operations (CS Ops): retention modelling, health scoring, and proactive intervention workflows

Finance Operations (FinOps): automated close cycles, cloud cost governance, and real-time board reporting

Agentic AI for risk, compliance, and regulatory reporting automation

AI governance frameworks aligned to SOX, SEC, FINRA, FDA, GxP, SOC2, and HIPAA requirements

MLOps, LLMOps, and modern data architecture to support production AI deployment at enterprise scale

Computer-assisted diagnostics and AI-augmented workflows for clinical and research environments