Bring direction to AI activity
Connect scattered experiments and individual tools to business priorities. Establish where adoption is useful, what is missing, and what should happen next.
AI-enabled business improvement
Clear priorities. Practical AI. Better delivery.
Understand where AI can help your business, what needs to change, and where to start.
You may already use AI for individual tasks. The next step is to help your teams reduce repetitive work, make better decisions and deliver with greater consistency and control.
CDC helps business leaders make informed decisions about AI, identify worthwhile opportunities and agree practical next steps with their teams.
The opportunity
Make the business work better
When reporting absorbs time, information sits in silos, or teams rely on manual handovers, AI may help. The starting point is understanding the process, the evidence and the outcome you need.
Grow without unnecessary complexity
Find ways to reduce repeated work, strengthen information flow and support teams as delivery demands increase. Address weak processes and data before adding automation.
The approach
Assess, prioritise, prove and plan
The engagement is shaped around your business, from an independent assessment through to pilot definition and a sequenced transformation roadmap.
- 01 AssessUnderstand the gap
- 02 PrioritiseFocus the effort
- 03 ProveDefine a useful trial
- 04 PlanSequence delivery
01 · Understand the gap
AI and process maturity assessment
Agreed stakeholders complete a current-and-target survey before a facilitated leadership workshop. We review the responses alongside process evidence, data readiness, existing tools, skills and governance to identify the gaps that matter.
You receive: a maturity baseline, an agreed target and a clear set of priority gaps.
02 · Focus the effort
Prioritise high-value use cases
Identify opportunities across programmes, PMO and operations. Compare expected benefit, feasibility, data availability, risk and adoption effort so leaders can choose where to invest attention.
You receive: a ranked opportunity shortlist with the assumptions and dependencies behind each recommendation.
03 · Design the change
Redesign workflows and define a pilot
Map the future workflow, including human judgement, approval points and traceability. Define a bounded pilot with a business owner, suitable information, acceptance criteria and a way to compare results with the baseline.
You receive: a proposed workflow and pilot brief with scope, measures and a go/no-go decision point.
04 · Make it deliverable
Build the implementation roadmap
Sequence the work, establish ownership and identify the capabilities, systems and change support required. Set out indicative effort, dependencies and review points for a proportionate programme of delivery.
You receive: a practical roadmap and benefits measurement plan. Any implementation support is scoped separately around your needs.
A useful assessment
The right ambition for each part of the business
AI readiness varies across a business. We agree an appropriate target for each area, based on its objectives and the value that better ways of working could create.
Look across the business, then focus
Begin with a broad view of leadership priorities, customer-facing work, engineering, operations and support functions. Examine the data, skills and controls they depend on, then select the workflows that warrant deeper investigation.
Test the evidence: compare stakeholder views with actual reports, handovers, system records and process ownership. Record uncertainty where evidence is missing.
Choose priorities on business merit
A substantial maturity gap may be worth addressing later. A smaller, achievable improvement may create value sooner. We weigh business importance, expected benefit, readiness and delivery effort together.
Make a decision: agree what to pilot, which foundations need attention first, and what to defer, with a named owner and a reason for each choice.
Start with your own view
Where are you now, and where would better capability help?
Explore 12 business functions, compare current and target maturity, and choose the areas that matter to you. Save a summary to discuss with your team or bring to a conversation with Chris.
Illustrative example: improving a weekly programme review
This hypothetical PMO workflow shows how an assessment can become a practical brief.
01 · Current position
Progress updates arrive in different formats. The PMO manually assembles the pack and chases missing evidence, leaving limited time to examine delivery risks.
02 · Desired outcome
A timely, consistent review pack that makes exceptions visible and links statements to their sources, with programme owners accountable for the final content.
03 · Foundations and pilot
Agree the reporting template, source records and access permissions first. Trial AI-assisted drafting on one programme, with human review before circulation.
04 · Evidence for the next decision
Compare preparation and checking time, factual corrections and missing source references over an agreed trial period. Expand only if the agreed quality and time-saving criteria are met.
Delivery discipline
Business outcomes first
We start with the business objective and the people doing the work. AI is considered alongside simpler process changes, better use of existing systems and clearer responsibilities.
The approach builds in information access, human review and accountable decisions from the outset. Pilot results inform whether to scale, revise or stop.
Led by Chris, CDC brings senior programme leadership experience to AI adoption, helping leadership and delivery teams weigh benefits, costs and risks, and agree a plan they can put into practice.
Potential applications
Where to look for value
Illustrative opportunities to assess against your own processes and data. The right priorities depend on your business, information readiness and delivery goals.
Programme and PMO reporting
Draft status summaries from approved sources, connect risks and actions, and surface exceptions for review. Give programme teams more time to resolve issues and support delivery.
Connected information and decision support
Help teams contribute to and draw from a shared, reliable view of delivery. Use AI to query connected programme, quality and resource information, bringing together the evidence leaders need to understand issues, explore trade-offs and act. Keep updates, decisions and ownership traceable.
Operational workflows
Identify repeated administration, manual handovers and bottlenecks across planning, supply chain and production. Explore simpler workflows and targeted assistance within existing controls.
Quality and traceability
Support retrieval of approved records, preparation of evidence packs and review of missing information. Preserve source references, configuration control and accountable sign-off.
How we measure improvement
Agree a baseline and success measures before the pilot begins. Assess the benefit alongside implementation cost, review effort and the impact on the people using the workflow.
Speed and capacity
Measure reporting lead time, task turnaround and hours spent on repeated administration.
Quality and consistency
Track errors, rework and first-time acceptance, including the effort needed to check outputs.
Decisions and traceability
Assess time to assemble decision evidence, source coverage and completeness of the decision record.
Leaner operations
Compare handovers, process steps and cost per completed task while monitoring adoption and control.
Contact
Where could your business work better?
If you are exploring AI, trying to bring direction to existing activity, or looking for a practical way to improve delivery, let’s discuss the priorities and what a focused first engagement could cover.
Start with the business challenge, the teams involved and the outcome you want to improve.
Connect with Chris on LinkedIn