AI disruption radar
Map competitive threats and value creation opportunities on a Watch / Protect / Accelerate / Transform grid.
ADaSci Masters · For CXOs and business heads
Executive AI masterclasses for enterprise adoption.
Move your leadership team from AI awareness to adoption decisions, portfolio priorities, governance guardrails and a concrete 90-day action plan.
90–120-minute, 4-hour, 1–2-day and multi-cohort formats.
From
Through
To
The leadership problem
AI adoption isn’t a tools problem anymore.
It’s blocked by leadership translation: where AI changes the economics, which opportunities deserve investment, what risks need guardrails, and how teams should act in the next 90 days.
The method
Learn. Apply. Reflect.
Senior leaders don’t need a course. They need a facilitated decision environment. No module ends with only learning — every module ends with an artefact or a commitment.
01 · Learn
Build shared AI leadership language
The three waves of AI, agentic workflows, AI-native competition, value pools and governance — framed for executive conversation, not classroom theory.
02 · Apply
Convert frameworks into business decisions
Teams work on their own functions using the disruption radar, portfolio map, opportunity canvas and 90-day planner — no hypothetical case studies.
03 · Reflect
Commit to accountable 90-day action
Challenge assumptions, surface risks, define owners and leave with a sponsor-ready plan carrying metric, sprint cadence and go/no-go logic.
What your team leaves with
Decisions, not decks.
Every session converts strategic conversation into tangible outputs a sponsor can fund, govern and measure.
AI portfolio map
Score impact, feasibility, risk, data readiness and time-to-value.
Opportunity canvas
Sponsor-ready: user, metric, data, risks, controls, owner.
Governance and risk lens
Data, privacy, hallucination, human-in-the-loop, kill-switch criteria.
90-day action plan
Owner · metric · three 30-day sprints · ask.
Formats
Four ways to run it.
90–120 min
Boardroom AI briefing
Executive committee or board-level orientation
- Strategic narrative
- AI-native risk lens
- Investment questions
4 hours
AI adoption masterclass
CXO teams, senior leaders, business heads
- Shared AI language
- Disruption radar
- 90-day commitment
1–2 daysFlagship
Functional AI adoption lab
One business unit or function (Sales, HR, Finance, Ops, Tech)
- Function opportunity portfolio
- Opportunity canvas
- Pilot plan
2 weeks blended
Enterprise Masters cohort
Multiple cohorts across business and technology leadership
- Cross-functional themes
- Use-case backlog
- Sponsor-ready plans
Run of show
A 4-hour session, choreographed for decisions.
Most time is spent on your business context, not technology demos. Blue blocks are hands-on activities.
30-min pre-read
Shared baseline and 2–3 AI reflections from each function.
Opening and leadership context
Frame AI as enterprise adoption and business-model change.
Module 1 · AI landscape
AI waves and AI-native vs AI-enabled competitive gap.
Activity · Disruption radar
Map competitive threats and value creation opportunities.
Module 2 · Strategy and ROI
From ideas to portfolio prioritization and business value.
Activity · Portfolio mapping
Score and nominate one opportunity to fund.
Module 3 · Governance
Bring risk, guardrails and ownership into the plan.
Activity · Opportunity canvas
Convert one use case into a sponsor-ready canvas.
90-day plan and commitments
Outcome, owner, sprints, risks and the ask.
Built for
The leaders in the room.
CXOs and business headsAI councilsTransformation leadersProduct leadershipOperations leadershipRisk and complianceTechnology leadershipCHRO and L&DChief Data / AI OfficeStrategy and innovationDigital officersBoard members
Quality bar
Vague ambition, out. Fundable plans, in.
We separate ideas that sound good from experiments that can prove value in 90 days.
| Output | Weak version | Masters standard |
|---|---|---|
| AI use case | Reduce repeat customer tickets by 20% using an AI assistant that retrieves policy and case history for support agents. | |
| Value | Save 600 analyst hours per quarter by reducing manual report preparation by 40%. | |
| Data | Named sources, quality issues, access rights, refresh cadence and sensitivity level. | |
| Risk | Named risks, guardrails, human approval points and kill-switch criteria. | |
| Owner | Executive sponsor, working owner and review cadence. |
Figures in the right-hand column are illustrative examples of the standard.
Enterprise engagement
Align your leaders on AI adoption.
Speak to ADaSci to design your first Masters cohort — customised to your industry, function, maturity and leadership audience.