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DeVries Technology Advisory Siamo Back to Paired Readiness

Paired Readiness scorecard

Can the operating model and the organization move together?

Most established companies already have AI activity. This five-minute check looks at whether the work, operating conditions, leadership signals, and human capacity can turn that activity into durable change.

Use observable conditions, not aspirations. This scorecard measures what is true today. It is a conversation starter, not a maturity certification or a prediction of transformation success.

How to complete it

Choose one answer for every statement.

Select True today only when you can point to current evidence. Select Not yet when the condition is planned, partial, or unsupported.

01

Customer-Backward Work Redesign

AI creates durable value when the work is redesigned from the customer or business outcome backward.

— / 3
We have identified where AI changes the shape of the work, not only its speed.
At least one core workflow has been redesigned starting from the customer or business outcome.
Leaders can name work we stopped, removed, or materially recomposed because AI changed what was possible.
02

Human + AI Workflow Architecture

The operating model needs explicit choices about what people own, what AI supports, and where judgment sits.

— / 3
We have defined what humans own, what AI assists, and what AI executes in key workflows.
Roles, handoffs, and judgment points have been redrawn for at least one team.
People know when to trust an AI-supported result and when to escalate it.
03

Data and Knowledge Foundations

AI depends on trustworthy data and knowledge even when the interface looks simple.

— / 3
Important enterprise knowledge is accessible to the systems and people who need it.
We have addressed data quality and retrieval where AI-supported work depends on them.
We can trace the important information behind an AI-supported answer or decision.
04

Governance That Enables

Useful governance gives people clear lanes to learn, build, and operate safely.

— / 3
We have distinct, named lanes for experimentation, permissioned build, and production use.
People have a timely decision path for using AI responsibly.
We know where unapproved AI use exists and have a path to bring useful work into managed lanes.
05

Measurement and Value Capture

AI activity becomes defensible when it connects to outcomes the business already values.

— / 3
We measure AI impact in cycle time, throughput, quality, revenue, margin, risk, or customer outcomes.
A CFO or COO could point to a business measure that AI has moved with credible attribution.
We can distinguish AI activity, such as pilots and usage, from AI value.
06

Human Readiness and Reinforcement

Change holds when people understand what shifts, can learn safely, and see the new way reinforced in daily work.

— / 3
We have named what people need to stop doing, start doing, or do differently because of AI.
Managers reinforce the new way of working through routines, coaching, and expectations.
People can safely report what is not working, not only showcase successful AI use.
07

AI as an Operating Layer

AI becomes durable when leaders align around the work to change and govern it through a recurring operating rhythm.

— / 3
Leaders can name the work AI is meant to change and agree on success in business and operating terms.
Someone clearly owns the AI operating model across business, technology, finance, people, and operations.
Our roadmap is built around how work evolves, so it can survive the next model or tool release.
08

Change Capacity

Every AI move adds pressure to roles, routines, decisions, and expectations. Capacity determines whether the organization can absorb the shift.

— / 3
We know how much change load the affected teams are already carrying.
We have made room for AI-enabled work by changing priorities, expectations, or capacity.
Teams have time and support to learn, adapt, and stabilize new ways of working.

Your current read

The pattern across dimensions matters more than one total.

Complete all 24 statements to see the provisional range and the conditions worth investigating first.