Loading…
270
Employees enabled
5
Program phases
6
Core workshops & learning experiences
15–20
AI Champions
12 Months
Transformation roadmap
90 Days
Pilot planning framework
The Challenge
What was happening before Synottic
The organization was already experimenting with AI — different teams trying different tools, some employees becoming advanced users while others had barely started. The problem was not a lack of interest. The problem was fragmentation.
- No common AI language across the organization
- No enterprise view of capability or department-level differences
- No consistent way to identify and prioritize use cases
- No coordinated adoption roadmap
- No organization-wide approach to responsible AI, data privacy, and risk in a financial services environment
The Synottic Approach
What had to change
Synottic did not start with training — it started with the organization itself. A five-phase Enterprise AI Enablement Program combined assessment, capability building, leadership alignment, functional application, and internal adoption infrastructure, treating AI adoption as an organizational transformation effort rather than a single learning intervention.
Assess → Align → Enable → Apply → Scale
01
Assess the Starting Point
An Enterprise AI Readiness Assessment and Executive Alignment Workshop surfaced capability gaps, department-level differences, priority opportunities, and governance risks — producing a baseline instead of a guess about what training everyone needed.
02
Create One AI Foundation
Two enterprise-wide cohorts brought all 270 employees onto a shared starting point: AI and Generative AI, AI in financial services, everyday tools like Copilot and ChatGPT, prompting, and responsible AI. Each participant received a Personal Prompt Library, AI Productivity Toolkit, and Responsible AI Commitment Checklist.
03
Turn Leadership Into the Transformation Engine
HODs, Center Heads, and Team Leads moved the conversation from 'how do I use AI' to 'where should this organization place its AI bets.' An AI Innovation & Opportunity Workshop mapped opportunities, assessed impact versus effort, and translated priorities into a 12-month AI Transformation Roadmap with quick wins, a 90-day action plan, governance structure, and success metrics.
04
Connect AI to Real Business Work
The program was adapted to Research & Investment Advisory, Marketing & Growth, Operations & Customer Support, HR & Corporate Functions, and Technology. Teams mapped processes, identified pain points, and prioritized use cases by impact and effort — the highest-priority ideas became 90-day pilot plans with ownership and success metrics.
05
Build the Internal AI Adoption Engine
Because transformation could not depend on an external trainer, Synottic created an AI Champions Network of 15–20 Team Leads and Center Heads, equipped to use AI more effectively, coach colleagues, identify new use cases, support adoption, and measure progress.
Signature Moment
An adoption engine that runs without an external trainer
The most important design decision was not a workshop — it was building an internal AI Champions Network of 15 to 20 Team Leads and Center Heads, equipped with advanced prompting, AI coaching, use-case discovery, and adoption measurement. That network, alongside Department Adoption Plans and a growing AI Use Case Repository, was the mechanism designed to keep adoption moving after the formal program ended.
Evidence
Program scope, not a satisfaction score
The engagement reached all 270 employees through a five-phase program, producing a readiness baseline, a leadership roadmap, and an internal structure built to sustain adoption.
5-phase Enterprise AI Enablement Program reaching all 270 employees
Differentiated tracks for employees, leaders, functional teams, and AI Champions
12-month AI Transformation Roadmap with a 90-day pilot planning framework
15–20 AI Champions equipped to coach colleagues and sustain adoption
Before → After
What actually changed
| Before | After |
|---|---|
| Fragmented AI experimentation | Enterprise-wide AI alignment |
| Uneven capability | Shared AI foundation |
| Department-level exploration | Cross-functional AI opportunity discovery |
| Ad hoc use cases | Prioritized use-case portfolio |
| Limited governance | Responsible AI built into the adoption model |
| No coordinated roadmap | 12-month AI Transformation Roadmap |
| Reliance on individual enthusiasts | Internal AI Champions network |
| Unclear path from ideas to action | 90-day pilot planning framework |
Artifacts
What the engagement actually produced
- Enterprise AI Readiness Report and department capability heatmap
- Capability gap analysis and prioritized use-case list
- 12-month AI Transformation Roadmap with 90-day pilot plans
- Personal Prompt Library and AI Productivity Toolkit for every employee
- Responsible AI Commitment Checklist
- AI Champions Network, Department Adoption Plans, and a growing AI Use Case Repository
Human Impact
What changed for people, not just process
The organization moved from individual enthusiasts carrying AI adoption informally to a coached, coordinated workforce. Leaders can now ask 'where should this organization place its AI bets' instead of 'how can my team use AI,' and every function can answer what AI actually means for its own work.
The Synottic Lens
What this demonstrates about AI transformation
Most enterprises are already experimenting with AI. The real challenge is what comes next: moving from experimentation to strategy, from individual users to organizational capability, from ideas to prioritized use cases, and from pilots to adoption — responsibly.
