AI enablement

Redesign real workflows with AI. Measure what changed.

Redesign real workflows using AI, helping people save time, improve quality and create credible evidence of productivity gains.

Discuss your challenge Start with the complimentary challenge

AI Productivity Enablement

Workflows, not demonstrations

Most AI training shows people what the tools can do. We work on the workflows they already run: reports, analysis, planning, communications, research and review. Each workflow is redesigned with AI in the loop, tested on live work and measured against a baseline.

The result is a set of documented, governed workflows the organisation can reuse, a group of champions who can extend them, and evidence that a sponsor can put in front of a board.

Documented, governed AI workflows in use
Measured time and quality gains against a baseline
Champions who extend the work
A leadership position on AI adoption and governance

1
Baseline
Pick a real workflow. Time it. Note the quality problems and the hand-offs.
2
Redesign
Rebuild it with AI in the loop: where it drafts, where it analyses, where a person checks and decides.
3
Test on live work
Run the redesigned workflow on this week’s real tasks, not a demo scenario.
4
Measure and document
Time saved, quality change, errors caught. The workflow written up so a colleague could run it.
5
Govern and share
Information-handling rules applied, sources checked, the workflow added to the organisation’s library.

Complimentary

Complimentary 90-Minute AI Productivity Challenge

A working session on one real workflow. Your team leaves with a redesigned process, a measured before-and-after, and a view of what a wider programme would deliver.

→ One real workflow from your team
→ Redesigned with AI in the loop, live
→ A measured before and after
→ A view of what a sprint would deliver

Who it suits

Learning, transformation and AI adoption leaders who need evidence before committing budget, and team leads with a workflow they are tired of.

What we need from you

Ninety minutes, four to eight people, one workflow, and access to the AI tools your organisation has approved.

Request the 90-minute challenge

Programmes

From one team to an organisation

AI Productivity Sprint

2 to 4 weeks

A sprint on a set of priority workflows for one team or function: baseline, redesign, test on live work, document, measure and hand over.

AI Champions Programme

6 to 12 weeks

Develop a cohort of champions who redesign workflows in their own areas, coach colleagues and maintain the organisation’s library of governed AI workflows.

AI Leadership Alignment Workshop

1 day

A senior team agrees where AI creates value, what the governance and information-handling rules are, and which workflows and teams go first.

Evidence the work produces

Workflow baselines and redesigns
Before-and-after measures
Prompt and workflow library
Governance and information-handling guidance
Champion portfolios

AI across the pathway

Embedded in every stage of the Innovation Capability Pathway

AI is not a separate module. It is a working tool at every stage, and the design of each programme changes to use it well without losing the judgement that makes the output worth having.

Aware

Guided challenge framing
Diagnostic summaries for sponsors

People decide. Participants choose the challenge. AI helps them describe it clearly.

Align

Research planning and evidence synthesis
Insight generation
Ideation and concept development
Rapid prototyping
Experiment design

People decide. Teams check sources, decide which insights matter and own the concept they take forward.

Apply

Evidence synthesis across interviews and data
Rapid prototyping
Test analysis
Decision pitch drafting
Benefits tracking

People decide. Validation with real users stays human. AI speeds up analysis; the team judges what the evidence supports.

Deliver

User-story and backlog development
System mapping
Process analysis
Risk and stakeholder analysis
Change communications
Benefits tracking

People decide. Priorities, trade-offs and commitments are made by accountable people with the analysis in front of them.

Sustain

Workshop design
Output capture
Scenario analysis
Portfolio decision support

People decide. Facilitators design for the room in front of them. Leaders make portfolio decisions with AI-generated scenarios as input, not instruction.

Human judgement and governance

Human ownership of decisions
AI produces options, drafts and analysis. People decide, and the decision record names who.
Source checking
Every AI-generated claim that informs a decision is checked against a source the team can cite.
Evidence traceability
Work products in the Capability Portfolio show what came from research, what came from AI and what the team concluded.
Appropriate information handling
Participants learn which information may be used with which tools, and how to work within their organisation’s classification and data rules.
Bias awareness
Teams test AI output for the assumptions and gaps it carries, especially about users who are under-represented in the data.
Ethical use
AI is used to improve the quality and speed of work for people and the public it serves, not to obscure accountability.
Organisational security requirements
We work with approved tools and configurations, including enterprise Copilot, private deployments and offline methods where required.

Sixteen practical applications across the pathway

Research planning and evidence synthesis
Insight generation
Ideation and concept development
Rapid prototyping
Experiment design
Test analysis
User-story and backlog development
System mapping
Process analysis
Risk and stakeholder analysis
Change communications
Benefits tracking
Workshop design
Output capture
Scenario analysis
Portfolio decision support

Governance

Seven rules built into every programme

AI does not replace human judgement. These rules are what allow a sponsor to trust the output enough to act on it. In defence and government settings they extend to the specific tools, configurations and offline methods the organisation requires.

Read: AI in the innovation process, with judgement intact

01
Human ownership of decisions
AI produces options, drafts and analysis. People decide, and the decision record names who.
02
Source checking
Every AI-generated claim that informs a decision is checked against a source the team can cite.
03
Evidence traceability
Work products in the Capability Portfolio show what came from research, what came from AI and what the team concluded.
04
Appropriate information handling
Participants learn which information may be used with which tools, and how to work within their organisation’s classification and data rules.
05
Bias awareness
Teams test AI output for the assumptions and gaps it carries, especially about users who are under-represented in the data.
06
Ethical use
AI is used to improve the quality and speed of work for people and the public it serves, not to obscure accountability.
07
Organisational security requirements
We work with approved tools and configurations, including enterprise Copilot, private deployments and offline methods where required.

Which workflow should go first?

Tell us about the team, the tools you have approved and the work that takes too long. We will propose the first sprint and what it should measure.

Discuss your challenge Explore the pathways