Build content engines
Generate, localise and adapt high-volume content inside approved brand assets, review gates and claims rules.
AI strategy for marketing teams
Build an AI-native marketing function.
Most marketing teams are already using AI. Very few have redesigned how their marketing function actually works. memery helps teams turn scattered experimentation into a practical operating model: where AI can create value, what should stay human, how it should be governed, and what to implement next.
What we do
We help marketing teams turn AI into an operating model.
The problem usually isn’t access to AI. It is deciding where it genuinely belongs in marketing, which use cases are worth backing, what data and guardrails are required, and how the team should work differently.
We work with organisations to diagnose the opportunity, identify and prioritise use cases, design governance and workflows, build capability, and turn that into a practical implementation roadmap.
Your AI Marketing Playbook
A practical plan built around your organisation.
Not a generic trends deck and not a prompt library. We create a bespoke playbook around your customers, marketing model, technology, data, risk environment and commercial priorities.
AI maturity and readiness assessment
Prioritised marketing use-case portfolio
Governance, data and human-control rules
Workflow, automation and agent opportunities
Capability and operating-model recommendations
90-day pilot and implementation roadmap
How marketers are actually using AI
The opportunity is much bigger than faster copy.
From working with marketing teams and AI from the beginning — and studying how some of the world’s biggest organisations are redesigning marketing around it — we keep seeing the same seven building blocks. These are the seven ways we help organisations build genuinely AI-native marketing functions.
Personalise performance
Use AI to choose audiences, bids, creative, offers and messages — then prove incremental lift rather than trusting the dashboard.
Make next-best decisions
Move from fixed journeys and broad segments towards decisions about the best message, offer, timing or action for each customer.
Win the new discovery layer
Improve the likelihood that ChatGPT, Gemini, Claude, Perplexity and AI-powered search systems can understand, cite and recommend you.
Make insight always-on
Compress research synthesis, increase measurement cadence and connect customer evidence to faster marketing decisions.
Build agents around workflows
Connect repeatable tasks to real systems, approved knowledge, explicit checkpoints and accountable human owners.
Buy capability without another salary
For smaller businesses, AI can provide the equivalent of extra marketing, CRM, research, content or development capability without enterprise infrastructure.
What we learned from a global research project into how companies are actually using AI right now
The winners start with a bottleneck, not a tool.
We combined our own hands-on work with marketing teams with a global research project into how organisations are using AI in the real world right now — from major enterprises to growth businesses and lean teams.
The strongest pattern was remarkably consistent: AI creates value when it starts with a genuine business bottleneck, is grounded in good data and context, has clear human accountability, and is tested against measurable outcomes rather than novelty.
40
case studies across enterprise, growth and small-business marketing.
7
practical marketing themes covering production, performance, decisions, discovery, insight, agents and small-business leverage.
A / B / C
evidence grades so readers can distinguish accountable disclosures from vendor-led claims.
Keep / kill / scale
a practical test-and-learn approach rather than assuming every AI pilot deserves to survive.
Get the 40-case-study field guide.
Real case studies from 2026, evidence graded, with practical plays for large organisations and small businesses alike.
Why memery
Marketing experience first. AI expertise applied where it creates value.
We combine senior marketing, customer experience, brand, digital, content, search and communications experience with hands-on AI implementation.
That means we understand the operating reality around the technology: competing priorities, stakeholder risk, brand governance, customer journeys, media investment, organisational capability and the need to prove commercial impact.
Senior marketing leadership
Experience leading complex marketing, customer and communications functions rather than advising from outside the discipline.
Hands-on AI implementation
Practical experience applying AI to marketing workflows, visibility, research, content, customer experience and capability development.
Evidence over hype
We distinguish proven results from vendor claims, build baselines and encourage controlled testing before scaling.
Strategy through execution
From operating model and governance through to workflows, content systems, GEO and implementation planning.
Case study
Spare Keys used AI to strengthen a high-impact social enterprise.
For Spare Keys, AI helped turn a lean communications operation into a more responsive marketing, fundraising and partnership engine.
We used AI to accelerate supporter communications, assist with grant and partnership research, surface new storytelling opportunities, improve donor and stakeholder follow-up, and make it easier to translate mission, impact and need into content that could actually be produced consistently.
The result was a stronger content rhythm, better use of scarce time, clearer fundraising and partnership outreach, and a more disciplined system for turning good ideas and incoming opportunities into action.
Supporter communications
AI-assisted drafting helped turn updates, stories and impact information into newsletters, social content and donor communications faster.
Grant and partner research
Relevant opportunities could be identified and summarised quickly, giving the team a more practical way to respond and follow through.
Media + storytelling
Story hooks, PR angles and case-study narratives became easier to surface, shape and prepare for human review.
Donor and stakeholder follow-up
AI-supported workflows helped reduce the chance of warm relationships, prospective partners and potential donors going quiet or being forgotten.
Questions buyers usually ask
AI marketing FAQs.
Do we need an AI playbook if people are already using ChatGPT or Copilot?
Usually that is exactly when a playbook becomes useful. Individual experimentation can create productivity gains, but it does not automatically create shared priorities, safe data practices, repeatable workflows, measurement or organisational capability.
Is the playbook mainly for large organisations?
No. The level of complexity changes with the organisation. Enterprise teams may need governance, data integration and decision engines; smaller organisations often get faster value from practical workflows that reclaim time, recover leads and add capabilities they could not otherwise staff.
Will you recommend specific AI platforms?
Yes, when tool choice matters. But we start with the marketing problem, data, workflow, evidence and risk — not a preferred vendor.
Can this work in an organisation with strict privacy or governance requirements?
Yes. Governance is part of the playbook: approved tools, sensitive-data boundaries, human approval, disclosure, record keeping, IP considerations and escalation.
How do we know AI is actually improving marketing?
We define the baseline first. Depending on the use case, that might mean cost and hours per asset, cycle time, incremental conversion, AI visibility, research turnaround, customer outcomes or another measure that can be tested against the current process.
What happens after the playbook is delivered?
The playbook includes a practical implementation roadmap with priority pilots, owners, controls, measures and scale-or-kill decisions. memery can also help implement selected workflows and capability changes.
Make AI useful
Build the AI marketing function you actually need.
Tell us what is getting in the way — scattered experimentation, unclear priorities, governance, slow workflows, weak AI visibility or simply not knowing where the real value is.
We’ll help turn it into a practical playbook your team can use.