What is repeated?
Find the tasks people do again and again: updates, checks, triage, reports, reminders, and handovers.
useful
AI-enabled service improvement
Make tools earn their place.
New tools should save time, not create another place to check. Clare helps organisations identify where AI and automation genuinely improve service delivery — and where judgement should stay with people.
Connect with Clare ↗Follow the thread to see where the work starts, what changes, and how the evidence becomes useful.
How service improves, in four stages:
01 Notice02 Connect03 Change04 Prove
Better tools, fewer detours
A tool is only useful if people use it.
What still needs judgement?
Keep people in charge where empathy, context, risk, or customer trust matters.
Will people understand it?
Use UI and web experience to make the tool feel clear, useful, and easy to adopt.
Did it actually help?
Measure whether people use the tool, whether time is saved, and whether customers notice the difference.
Where AI adoption gets hard
It looks simple until the data doesn't cooperate.
Data has to be trustworthy before it's useful.
AI can only work with what it's given. Messy, duplicated, or inconsistent data has to be cleaned and structured before it's worth connecting to anything.
Format it so AI can actually read it.
Information that makes sense to a person doesn't automatically make sense to a system. Getting content AI-ready often means restructuring it, not just switching on a tool.
Permissions matter more than people expect.
Who can see what has to be reviewed properly. AI makes existing access gaps visible fast, and the wrong person seeing the wrong answer is a real risk, not a hypothetical one.
The same question needs the same answer.
If two people ask the same question and get two different results, trust disappears immediately. Findings like that get reported up, not quietly patched over.
Practical automation
Automation should make the day easier.
Start with repeated work.
Status updates, routing, reminders, triage, reporting, and routine checks are often better starting points.
Keep judgement with people.
AI can help prepare, summarise, suggest, and speed up. It should not take over moments where trust matters.
Measure whether it saves time.
The test is whether work moves faster and teams stop doing the same task twice.
Improve how knowledge moves, not just how tickets move.
The biggest gains are often about getting the right information to the right person faster — not automating the click at the end.
Outcomes & evidence
Judged by whether it actually saves time.
Less repeat work, not more dashboards.
The test of any tool is whether teams stop doing the same task twice.
Hands-on AI-assisted build experience.
Clare has used AI-assisted development to design and build a working product prototype — applying the same problem-first thinking to code as to strategy.
Twenty years of judgement about where automation belongs.
Knowing what to automate matters more than the tool itself.
Part of a wider evidence base.
This thinking connects directly to the service transformation and customer experience work it supports.
Customer experience
Are You Automating Customer Effort or Removing It?
It's possible to reduce internal effort while increasing customer effort at the same time. Automation should be judged by the experience it creates, not just the work it removes.
Read Briefing ↗AI and digital changeBefore You Build an AI Agent, Get Your Information in Order
Building an agent is the easy part. The harder work is making sure the information behind it is current, clearly structured, properly owned and correctly permissioned.
Read Briefing ↗AI and digital changeBefore You Automate the Service, Make Sure It Works
Automating a broken process just makes it fail faster. Understanding how a service really works has to come before deciding what to automate.
Read Briefing ↗Keep following the service story.
The work should be easy to explain and easy to trust.
Transformation only means something if it can be shown. This is where customer evidence, operational insight, governance, and measurable improvement come together, alongside independent industry recognition earned during Clare's career.
AI makes a good process faster. It makes a bad process faster too.
The teams who get real value from AI aren't the ones with the most tools. They're the ones who fixed the process first, then let AI remove the repeatable parts of what was left.
Service transformation is a long game.
When customers are frustrated and teams are stretched, the problem is rarely one person or one ticket. Clare helps leaders stay with the work long enough to see the pattern, fix the handoffs, and show what has improved.