Eugene Mischenko · AI implementation method
AI IN MARKETINGAssessment and implementation.
Where can AI help your marketing team? What needs to change before you introduce it, and how will you know it works? My approach connects an assessment of your processes, data and team with an implementation plan and a review of the results.
Discuss an assessmentA cycle of assessment and change
Processes / People / Decisions- 01
Assess the starting point
Examine existing practices, data, processes and management readiness. Build a profile across nine dimensions and identify the constraints on useful AI adoption.
A baseline profile and an evidence-backed list of gaps.
- 02
Design the changes
Turn the findings into priorities, responsibilities and a roadmap. Connect proposed AI applications to marketing objectives, available resources and evaluation criteria.
An agreed plan, process owners and criteria for pilot decisions.
- 03
Implement and embed
Run bounded pilots, organise the necessary integrations, develop team skills and establish working rules. Scope technical delivery with the people responsible for the systems.
Tested workflows, training and operating documentation.
- 04
Reassess and adjust
Compare the initial and current profiles, review business measures and identify the next constraints. Use the findings to adjust the programme and start the next improvement cycle.
A comparison of changes and the next set of priorities.
Nine assessment dimensions
Strategy / Processes / People / ResultsStrategy and the management system
How AI initiatives connect to marketing strategy and company objectives.
Marketing processes
How workflows, automation and process measures are defined.
Data and integration
How marketing, sales, service and information systems work together.
Organisation and skills
Who owns the work, how responsibilities are shared and how people learn.
Economic efficiency
How costs, marketing resources and commercial outcomes are evaluated.
Risk management
How errors, technology risks and the quality of automated decisions are controlled.
Ethics and legal requirements
How data protection, transparency and applicable requirements are reflected in working practices.
Technology and innovation
How new AI capabilities are tested, introduced and maintained.
Management support and behavioural readiness
Whether leaders support the changes and employees are ready to use AI, trust appropriate outputs and develop their skills.
Implementation stages
The methodology’s implementation roadmap has six stages. The assessment helps determine which work is needed first and which capabilities the business must develop before expanding its use of AI.
- 01
Preparation
Agree objectives, data, responsibilities and controls.
- 02
Piloting
Test selected use cases in a limited setting.
- 03
Scaling
Extend successful pilots to suitable processes and channels.
- 04
Production operation
Establish service levels, operating rules and business measurement.
- 05
Stabilisation
Monitor quality, resolve incidents and review ongoing performance.
- 06
Continuous improvement
Repeat assessment and revise priorities as the business changes.
AI FOR small teams.
For a growing brand or a small e-commerce team, the work can begin with one marketing process. We agree a proportionate assessment, priorities, responsibilities and measures. The scope of this adaptation is documented so it remains clear what has been examined.
The practical output can include a readiness profile, a gap map, a pilot plan, working instructions and a repeat assessment. We agree the required deliverables for your project.
AI implementation practiceHow the assessment works
I call this methodology SMAAI — Strategic Marketing Adaptation to AI. It provides a structure for assessing how marketing adopts AI and planning the changes. Assessment combines questionnaire responses, documentary evidence and available operational measures. It supports decisions about adaptation; commercial effects are evaluated separately in the context of each project.
A maturity assessment depends on the quality of the evidence and the agreed scoring procedure. A change in the index describes a change in the assessed practices; it does not on its own establish the effect of AI on revenue or profit. A project’s baseline, business measures and evaluation design are agreed separately.
Related publications
These works address skills, adoption and purchase-stage applications of AI. They provide research context for the approach.
The two-sided AI skills underinvestment trap: a formal model
2026Advanced Applications of LLMs in Marketing During the Purchase Stage
2026Motivational mechanisms of early AI adoption in marketing: behavioral and organizational determinants
Start with your situation
Describe the marketing task, existing AI tools, team and expected change. We will identify useful evidence and agree the assessment scope.