Prepare the human side of AI-driven marketing personalisation: who is retrained, who is redeployed, and when they are told.
Artificial Intelligence in Digital Marketing and Customer Experience Personalisation
A working programme in AI-driven marketing personalisation for managers who have to deliver with existing resources.
Course Overview
Most organisations now hold more data about AI-driven marketing personalisation than they can actually act on. The distance between a working prototype of the practice within digital and data-driven work and a system the business can depend on is where most budgets disappear. Buying a tool rarely fixes the digital and data-driven work discipline; the underlying capability has to be built internally first. Where AI-driven marketing personalisation is measured, it improves; where it is only discussed, it drifts. The result is the confidence to make and defend decisions about the digital and data-driven work capability under scrutiny. The method assumes participants will be challenged on their handling of this strand of digital and data-driven work and prepares them for it. Participants leave with a method for AI-driven marketing personalisation, not a set of opinions about it. The level assumes working familiarity with the transformation programme but no prior formal training in this aspect of digital and data-driven work. Participants finish with a short, specific brief on this part of digital and data-driven work ready to put in front of a decision maker.
Expected Learning Outcomes
Build a concise delivery roadmap for AI-driven marketing personalisation that colleagues can follow without further explanation.
Distinguish the parts of AI-driven marketing personalisation that must be standardised from those that require judgement.
Quantify the running cost of AI-driven marketing personalisation — compute, licensing, and the people who keep it alive.
Establish monitoring that detects model or service degradation in AI-driven marketing personalisation before users report it.
Define success criteria for AI-driven marketing personalisation in business terms before any technology is selected.
Estimate what AI-driven marketing personalisation costs to run properly, and what is lost when it is not.
Who Should Attend
Product owners prioritising the roadmap for AI-driven marketing personalisation.
Officers preparing reports on AI-driven marketing personalisation for boards or oversight committees.
Information security officers reviewing the exposure created by AI-driven marketing personalisation.
Chief information officers accountable for the investment in AI-driven marketing personalisation.
Department heads accountable for the results of AI-driven marketing personalisation.
Operations managers whose processes are changed by AI-driven marketing personalisation.
Course Modules
AI-driven marketing personalisation: measuring benefit and retiring what it replaces
2 sessions · 8 pointsSession 1Choosing a supplier for AI-driven marketing personalisation without being captured
- Record the reasoning behind each architectural choice in AI-driven marketing personalisation.
- Measure the current quality of the data feeding AI-driven marketing personalisation before assuming it is usable.
- Verify six months later that changes to AI-driven marketing personalisation have held.
- Check that AI-driven marketing personalisation still works when volumes rise unexpectedly.
Session 2Reading the current state of AI-driven marketing personalisation honestly
- Define the exit route from the supplier supporting AI-driven marketing personalisation.
- Review whether AI-driven marketing personalisation is aligned with the objectives of the transformation programme.
- Classify the data in AI-driven marketing personalisation and apply access controls that match the classification.
- Build the internal briefing that explains AI-driven marketing personalisation to those affected.
AI-driven marketing personalisation: architecture, integration and the existing estate
2 sessions · 8 pointsSession 1Who owns AI-driven marketing personalisation once the project team disbands
- Build the competence framework that supports AI-driven marketing personalisation.
- Rank the weaknesses in AI-driven marketing personalisation by consequence rather than by ease of fixing.
- Distinguish symptoms from causes when AI-driven marketing personalisation underperforms.
- Set out how exceptions to AI-driven marketing personalisation are requested and approved.
Session 2Closing out AI-driven marketing personalisation and capturing what was learned
- Design the pilot for AI-driven marketing personalisation so that a negative result is still useful.
- List the data sources AI-driven marketing personalisation consumes and confirm each has a named owner.
- Agree what will be standardised in AI-driven marketing personalisation and what will not.
- Estimate compute and licensing cost for AI-driven marketing personalisation at expected and at peak load.
AI-driven marketing personalisation: vendor selection and avoiding lock-in
2 sessions · 8 pointsSession 1Where AI-driven marketing personalisation touches systems nobody wants to change
- Confirm the retention and deletion rules applied to data inside AI-driven marketing personalisation.
- Agree the smallest change to AI-driven marketing personalisation that would be visibly useful.
- Establish the boundary of AI-driven marketing personalisation and record what sits outside it.
- Build the user briefing that explains what AI-driven marketing personalisation does and does not decide.
Session 2The pilot that actually settles the argument about AI-driven marketing personalisation
- Rehearse the briefing on AI-driven marketing personalisation that would follow an incident.
- Test AI-driven marketing personalisation against edge cases drawn from real historical records.
- Verify that AI-driven marketing personalisation still performs when input volume doubles unexpectedly.
- Assess the regulatory obligations AI-driven marketing personalisation triggers in each jurisdiction.
AI-driven marketing personalisation: governance, ethics and explainability
2 sessions · 8 pointsSession 1Sizing AI-driven marketing personalisation honestly before committing budget
- Plan the sequence in which improvements to AI-driven marketing personalisation will be introduced.
- Close out actions on AI-driven marketing personalisation rather than leaving them open indefinitely.
- Decide which legacy process AI-driven marketing personalisation retires, and set the date.
- Identify the skills the team lacks to operate AI-driven marketing personalisation independently.
Session 2Building lasting competence in AI-driven marketing personalisation
- Assign responsibility for keeping documentation of AI-driven marketing personalisation current.
- Identify every system AI-driven marketing personalisation must read from or write to.
- Confirm that reporting on AI-driven marketing personalisation reaches the people who can act.
- Define the service level AI-driven marketing personalisation must meet and what happens when it is missed.
Choose the package that suits you
Silver Package
At least 3 people
- Workshop or Program Participation
- Airport Transfers
- Customized Badge
- Expert Mentorship (Private Sessions)
- Supervision & Secretarial Services
- Accredited Certificate of Participation
- Complete Training Kit
- Coffee Break
- Closing Ceremony
Gold Package
At least 3 people
- 5-night stay in a 5-star hotel
- Workshop or Program Participation
- Airport Transfers
- Customized Badge
- Expert Mentorship (Private Sessions)
- Supervision & Secretarial Services
- Accredited Certificate of Participation
- Complete Training Kit
- Coffee Break
- Closing Ceremony
Complete your registration
We will contact you within one business day to confirm.