AI Strategy & Leadership
Choose a direction worth pursuing.
Explore AI adoption through priorities, capabilities and clear ownership.
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01Purpose
Connect the initiative to an explicit organisational goal.
02Capability
Consider the skills, data and capacity needed to deliver it.
03Ownership
Name who decides, who is accountable and how progress is reviewed.
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New articles, newest first.
Keep quarterly AI strategy reviews focused on value
Review AI marketing outcomes and changed assumptions quarterly, then assess new launches against your roadmap instead of letting announcements set priorities.
Read the articleScale agency AI methods across different clients
Standardize agency AI evaluation and learning while respecting each client’s data, permissions and approval needs, with clear ownership for shared methods.
Read the articleAsk what an autonomous campaign actually completes
Evaluate autonomous campaign claims by the decisions covered, exceptions handled and repeatable outcomes, rather than accepting a broad product label.
Read the articleBuild original research into your AI discovery plan
Create an original-research program from questions your organization can answer credibly, with transparent methods, useful findings and accountable upkeep.
Read the articleBuy an AI platform or improve your current stack?
Write a decision memo comparing a new AI platform with improvements to existing systems, including the actual bottleneck, switching costs and exit path.
Read the articleReward useful marketing work when AI boosts output
Design marketer incentives around accepted quality, customer outcomes and useful learning so faster AI production does not turn raw output into the main goal.
Read the articleDo cheaper AI models change your marketing strategy?
Use a worked hypothetical cost example to see whether model spending or review and integration effort determines the economics of your AI marketing workflow.
Read the articleMake uncertainty visible in an AI business case
Write an AI marketing business case with explicit assumptions about adoption, integration and review, using ranges and a clear next investment decision.
Read the articleSequence small-business AI around one customer need
Choose a practical AI adoption sequence for a small business by fixing one customer bottleneck with existing tools before adding new platforms or complexity.
Read the articleSet the limits of campaign agent autonomy first
Define campaign agent decision rights by financial exposure, reversibility and customer impact, then expand autonomy only where evidence supports the scope.
Read the articleChoose a central or embedded AI marketing team
Compare centralized, embedded and hybrid AI marketing teams by expertise, business context and shared controls, then choose ownership that fits your scale.
Read the articleStress-test AI discovery as a distribution risk
Use explicit scenarios to examine AI referrals, acquisition quality and channel dependence without treating uncertain traffic assumptions as forecasts.
Read the articleBuild AI marketing skills around real role decisions
Create an AI capability plan for creatives, analysts, operations and leaders using practical tasks, review responsibilities and evidence of sound judgment.
Read the articleEvaluate an agency’s AI claims during the pitch
Assess agency AI claims through reproducible work samples, transparent cost assumptions and demonstrated controls before accepting promised marketing savings.
Read the articleRedesign marketing responsibilities around AI agents
Map how AI agents change planning, execution and review responsibilities while keeping clear accountability and avoiding unsupported assumptions about staffing.
Read the articleKeep your brand distinct when AI tools become common
Build differentiation around original evidence, deliberate brand choices and useful customer relationships when competitors can access similar AI tools.
Read the articleGive your 90-day AI pilot a real decision point
Plan a 90-day AI marketing pilot with a baseline, observable outcome and named decision owner, so the final review can scale, change or stop the work.
Read the articleChoose your next AI investment by the bottleneck
Compare data, distribution and creative investments by the constraint limiting customer value, then fund the smallest change that can test your diagnosis.
Read the articleSeparate AI productivity gains from marketing growth
Build distinct business cases for AI productivity and growth, showing where saved time goes and testing commercial outcomes without double-counting benefits.
Read the articlePlan your 2027 AI budget around proven marketing work
Build a 2027 AI marketing budget from evidence collected in 2026, separating reliable workflows, bounded experiments and the data work needed to support them.
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MARKAIGEN / CHOOSE YOUR NEXT STEP A generative AI strategy should explain which marketing problem matters, why AI is suitable and what evidence would justify further investment. Prioritise feasible use cases before choosing a large tool stack. For small businesses, a single useful workflow can be a better starting point than a broad transformation programme. Include maintenance, review and learning costs in the business case.Start strategy with the business problem