Strategies for Developing AI Products Within the Enterprise Sector with Legitimate Growth Potential

In the world of artificial intelligence (AI) implementation, enterprises are moving through distinct phases to leverage the technology for transformative change. ADVISORI, a company with extensive experience in highly regulated financial environments, has been at the forefront of this transition.

The scaling framework for AI in enterprises consists of three phases: Authorized Pilot Adoption, Departmental Expansion, and Enterprise Integration.

Authorized Pilot Adoption (Phase 1)

This initial stage spans months 0-3 and involves partnering with innovation labs or transformation offices for testing new technologies. The goal is to create an internal success story that can navigate the approval process.

Departmental Expansion (Phase 2)

Occurring in months 3-6, Departmental Expansion focuses on work with specific departments with urgent productivity needs and budget flexibility. During this phase, AI is built within the existing security perimeter using the approved cloud infrastructure or on-premises deployment. The focus is on augmenting adjacent work without touching regulated processes, and usage patterns are analyzed to reveal optimization opportunities that don't require policy changes.

Compliance officers may express savings in audit preparation time or the ability to meet new regulatory timelines during this stage. The focus is on preparation and review work that surrounds regulated processes, such as loan applications.

Enterprise Integration (Phase 3)

Enterprise Integration, occurring after 12+ months of proven value and deep regulatory understanding, is when core processes are transformed. This transformation is evolutionary, not revolutionary, and maintaining the old process should feel more risky than adopting the new one.

In the initial stage of adaptive integration, AI must mirror existing workflows exactly, even when they're inefficient, to prove understanding of the enterprise's world and constraints. As the transformation progresses, AI must add enterprise features such as data residency controls, role-based access with the identity provider, and detailed audit logs that integrate with SIEM systems.

Partnership with the compliance team is crucial in this stage for co-developing new compliant and transformative processes. This partnership is a deposit in the trust bank, demonstrating serious partnership and understanding of the enterprise's reality.

A business case for transformation in Stage 3 includes risk mitigation, not just efficiency gains. Data from earlier stages is used to build this case. The paradox in implementing AI in enterprises is that you cannot change processes in the short term, but AI delivers transformative value when processes change.

ADVISORI has collaborated for more than twelve months with companies in highly regulated financial environments to improve core processes using AI technology aimed at transformative change. This collaboration has resulted in a partner team in the compliance department to ensure secure and compliant AI implementation aligned with CRR-2 requirements.

In conclusion, enterprises don't need better AI, they need AI that scales from individual productivity to group effectiveness without losing its initial value. The journey towards AI transformation in regulated industries is a strategic one, requiring a deep understanding of the enterprise's unique constraints and a commitment to compliance at every step.

Strategies for Developing AI Products Within the Enterprise Sector with Legitimate Growth Potential