Solution
Practical AI in the workflows that are costing you hours
Intake, qualification, summarisation and reporting — automated where accuracy allows, with a human in the loop wherever a mistake would matter.
Why this exists
The business problem
Most AI initiatives in marketing operations fail for the same two reasons: they are pointed at tasks where errors are expensive, or they are bolted onto processes that were never documented in the first place.
Meanwhile the genuinely suitable work goes untouched — transcribing and summarising enquiry calls, extracting structured detail from documents and screenshots, drafting first-pass responses, categorising incoming requests, and turning raw campaign data into a readable weekly summary.
The value is in reclaimed hours and faster response, not in replacing judgement.
Fit
Who this is for
A good fit if
- Teams doing high-volume repetitive processing of enquiries or documents
- Businesses where response speed is a competitive advantage
- Operations still re-keying data between systems and spreadsheets
- Companies wanting to evaluate AI without an open-ended experiment
Probably not a fit if
- Anyone wanting AI to publish customer-facing content without review
- Regulated processes where automated decisions are not permissible
- Organisations without documented processes — we would have to fix that first
Scope
What is included — and what is not
Scope written plainly, so there is no argument later about what was assumed.
Opportunity assessment
Which workflows are suitable, which are not, and what each is realistically worth in hours or response time.
Intake automation
Voice, text, document and screenshot capture converted into structured records with confidence scoring.
Qualification assistance
Enrichment and scoring that recommends rather than decides, with the reasoning visible to the human reviewing it.
Summarisation
Call notes, thread summaries and account digests generated automatically and attached to the CRM record.
Response drafting
First-pass replies for common enquiry types, always reviewed before sending.
Reporting automation
Narrative summaries of campaign performance that explain the change rather than restate the numbers.
Human-in-the-loop design
Explicit review checkpoints wherever an error would reach a customer or a decision.
Governance
Data handling rules, retention, access control and a written record of where AI is used and how it is checked.
Explicitly not included
- Autonomous customer-facing agents with no human review
- Automated decisions in regulated contexts without qualified sign-off
- Training custom models on your data unless separately scoped and agreed
- Guaranteed accuracy rates — we measure and report them, we do not promise them
- Third-party AI platform licence costs
How it works
The working process
Workflow assessment
Week 1–2Process observation, volume and error-cost analysis, and a shortlist ranked by value and risk.
Pilot design
Week 2–3One narrow workflow, defined success criteria and an accuracy baseline measured before automation.
Build and test
Week 3–6Implementation with review checkpoints, tested against historic cases where the right answer is already known.
Measured rollout
Week 6–10Live use with accuracy monitoring and a clear rollback path if quality drops.
Extend
OngoingAdditional workflows only after the first one has demonstrated its numbers.
Measurement
KPIs we monitor
AI projects need harder measurement than most marketing work, because the failure mode is confident inaccuracy.
Extraction accuracy
Field-level accuracy against human-verified records, sampled continuously rather than once at launch.
Human review rate
Share of outputs requiring correction, tracked over time as the system is tuned.
Processing time saved
Hours returned per week, measured against the pre-automation baseline.
Response time improvement
Change in time-to-first-response for the automated workflow.
Escalation rate
How often the system correctly defers to a human instead of guessing.
Cost per processed record
Total tooling and review cost divided by volume, compared to the manual baseline.
Expectations
Realistic timeline
One workflow at a time, each with a measured baseline. Broad AI programmes without baselines are how budgets disappear.
Assessment and pilot selection, with an accuracy baseline established before anything is automated.
Build and testing against historic cases. Accuracy is usually worse than expected at first — that is why we test.
Live rollout under supervision, with review rates monitored weekly.
Extension to further workflows, justified by the first one's measured results.
Where it applies
Relevant industries
Commercials
Relevant packages
Productised starting points. Every one is confirmed in writing before anything begins.
CRM & Automation Build
Scoped after an assessment of your current stack, data and processes.
View packageScale Engine
Multi-channel acquisition with CRO, automation and growth leadership.
View packageMarket Expansion System
New segments, new geographies and senior leadership across the whole system.
View package- Media spend (Google Ads, Meta, LinkedIn, or any other paid platform) is billed separately by the platform and is not included unless a package explicitly says otherwise.
- Software, hosting, domains, call tracking, review platforms, backlink or placement purchases and other third-party costs are separate unless explicitly included.
- Results are not guaranteed. We do not publish or promise lead volumes, rankings, revenue or ROAS.
- Final scope depends on your market, geography, competition and current baseline. Scope is confirmed after a discovery call.
- “Starting at” pricing represents the minimum typical engagement for that package, not a fixed quote.
Evidence
Related work
Where the reporting has not been verified and approved for publication, we present the engagement as a project showcase and publish no figures.
No published entries for this solution yet. See all work.
Reading
Related insights
How to Qualify B2B Leads Without Wasting Sales Time
BANT is dead. Here's how modern B2B teams qualify leads using signals, scoring, and automation.
Pillar GuideCRM Setup Guide: How to Configure HubSpot or Salesforce for B2B
Your CRM is only as good as your setup. Here's how to configure it for scalable B2B pipeline management.
Pillar GuideMarketing Dashboard Design: KPIs That Matter
Build dashboards that drive decisions, not just display data. The metrics framework for marketing leadership.
Questions
Frequently asked
Assess your AI opportunities
We look at your repetitive workflows, estimate the hours involved and tell you which ones are worth automating — and which ones are not.