Get your AI house in order before you spend another pound on tools
You have ChatGPT licences. Someone’s experimenting with Midjourney. The result? Inconsistent outputs, no quality control, and a team producing wildly different results from the same tools.
The problem
Tools without foundations
Most businesses bought AI tools before they built AI capability. The tools are powerful. The usage is chaotic.
One person produces decent content. Another produces something that reads like a chatbot wrote it. A third is using AI for client-facing work with no review process. Nobody is tracking what works, what does not, or what is compliant.
You are spending money on AI. You do not have AI operations.
Before and after
What changes in the first week
This is not a strategy deck that sits in a drawer. By the end of week one, your team’s daily workflow looks different.
Monday morning now
Marketing opens ChatGPT. Everyone prompts differently. Some outputs are good. Some are embarrassing. Nobody reviews before publishing.
Sales uses AI for proposal drafts but the tone is inconsistent. Client-facing documents sound like a chatbot wrote them.
Leadership has no visibility into what AI is producing, whether it is compliant, or what the return on the investment looks like.
Monday morning after week one
Every team member follows standardised prompting frameworks. Outputs are consistent and on-brand. A four-point quality check runs before anything goes out.
Proposals use your approved templates and voice guidelines. AI drafts sound like your business, not like a language model.
Clear audit trails show what AI produced, who reviewed it, and what was published. Leadership sees the operational picture.
What we install
The six foundations
Every AI Operations engagement installs these six elements. We customise each for your industry, team structure, and existing tools. You own the system when we leave.
Foundation 1
Standard operating procedures
12 foundational AI SOPs customised for your business. Prompting standards, output formats, review workflows, and escalation paths. Your team knows exactly what good looks like.
Foundation 2
Brand voice consistency
Your business sounds like your business, not like ChatGPT. We build the prompt frameworks and quality gates that enforce consistent voice across every AI-generated output.
Foundation 3
Quality control framework
Four-point quality check for every piece of AI output. Accuracy, brand alignment, compliance, and human review. Zero client-facing embarrassments.
Foundation 4
Team training programme
Seven-day structured programme. Everyone from the CEO to the junior marketer producing consistent, useful AI output by the end of the week.
Foundation 5
Compliance and audit trails
EU AI Act readiness. Risk management protocols. Clear documentation of what AI produced, who reviewed it, and what was published. Your legal team will thank you.
Foundation 6
AI/human boundaries
Clear protocols for when AI works and when humans must take over. Not everything should be automated. We define the lines so your team does not have to guess.
Relevance
Who needs this
CEOs who have spent on tools with nothing to show
You approved the AI budget. The team has licences. Six months later, output quality is uneven and nobody can quantify the return. This is the foundation that was missing.
CMOs inheriting inconsistent AI usage
Half the team uses AI well. The other half produces content you would not put your name to. You need consistency without slowing everyone down.
COOs tasked with “implementing AI”
You have been told to roll out AI across the business. You are drowning in vendor pitches and have no framework for evaluating what actually matters. Start here.
Timeline
What the engagement looks like
Week 1
Audit and customise
We assess your current AI usage, identify gaps, and customise the 12 SOPs for your specific workflows, tools, and industry requirements.
Weeks 2–3
Train and install
Seven-day training programme delivered. SOPs installed into daily workflows. Quality control framework operational. Everyone producing consistent output.
Weeks 4–6
Embed and measure
AI integrated into daily operations. Compliance frameworks live. Measurable time savings documented. Your team runs it independently from here.
What comes next
Once your team is operational, most clients expand into the AI Growth Engine — turning consistent AI capability into consistent pipeline generation.