Business and user understanding
DevelopedMapping of business needs, customer journey and user needs as a basis for AI prioritisation.
Case and implementation
Strategic AI implementation: From case to executable plan
From AI opportunity to structured and executable implementation plan.
This project is a master's assignment from Generative AI for Business at BI Norwegian Business School. The work shows how an organisation can move from general AI interest to a concrete and executable implementation plan — linking business needs, user needs, technology, risk, privacy and organisational execution. Skøyenåsen Dental Clinic is used as the case basis to test the method, but the detail page focus is implementation logic, methodology and transferable learning — not the concrete patient solution.
The solution is developed as a concept prototype and portfolio demonstration — not presented as a production-ready system.
The challenge the project addresses
Many organisations are curious about AI but lack structure for moving from idea to execution. The challenge is often knowing where AI actually creates value, which use areas should be prioritised, and how risk, trust, privacy and responsibility should be managed — without the work becoming a technology project detached from operations and user needs.
Model, approach and project logic
The implementation model moves from identifying relevant AI opportunities to a concrete execution plan in six connected phases:
Opportunity and needs clarification
Mapping of business needs, customer journey, user needs and where AI can create value without weakening quality or human control.
Use case prioritisation
Assessment of which AI use areas should be prioritised based on value, feasibility, risk and organisational maturity.
Solution design and architecture
Description of technology, data flow, integrations and boundaries — including human-in-the-loop and escalation to people.
Governance, privacy and risk
Framework for responsible use, privacy, security and clear boundaries against high-risk automation.
Roadmap and execution
Realistic plan for phases, roles, dependencies and organisational anchoring — from pilot to further scaling.
Case basis
Skøyenåsen Dental Clinic is used as a concrete business context to test the method. The operational patient solution is documented as a separate project.
The methodology is academically grounded through Generative AI for Business at BI and combines commercial understanding, user journey, governance and practical AI implementation.
What has been built or developed
The project delivers a comprehensive implementation plan — not a production-deployed platform. As part of the work, digital concepts were developed to test the solution logic:
- Needs analysis and business anchoring
- Solution design with technology and architecture
- Roadmap and phased execution plan
- Governance framework, privacy and risk assessment
- Human-in-the-loop and responsible implementation
- Digital concepts for front-end, chatbot, text and voice input, multilingual support, needs clarification and booking logic
Core deliverables and functional areas
The master's project structures the implementation work in clear delivery areas:
Needs analysis and prioritisation
DevelopedStructured assessment of AI opportunities, value and risk before choosing solution direction.
Solution design and technology
DevelopedDescription of technology, architecture and integration needs with clear boundaries.
Governance and privacy
DevelopedFramework for responsible use, privacy, security and human control.
Roadmap and organisation
DevelopedPhase plan, roles and execution logic for the organisation.
How the project or solution works
The implementation model is used in practice as follows — regardless of industry:
Identify opportunities
Map where AI can create value in the organisation's core processes and user journeys.
Prioritise and scope
Choose use areas with clear value, manageable risk and realistic feasibility.
Design solution and governance
Describe technology, data flow, privacy and human-in-the-loop before development.
Plan execution
Create a roadmap with phases, roles and control points for responsible implementation.
Why the project is relevant
For leaders and organisations
Provides a practical framework for moving from AI interest to executable plan — with focus on value, risk and responsible use.
For employers and recruiters
Documents the combination of commercial understanding, user journey, governance and practical AI implementation — with academic grounding from BI.
Transferable learning
The methodology can be used as a starting point for workshops, implementation maps and leadership dialogue in other organisations — without requiring an identical industry context.
Status, maturity and limitations
Completed master's project and practical implementation case with developed solution and execution logic. Digital concepts in the assignment were developed to test the method — not presented as production-deployed solutions. The project is not a medical, clinical or journal-adjacent patient solution.
Further development and scalable application
Further development of the solution
- Workshop format for leadership and team dialogue
- Implementation maps and phase plans
- AI use case prioritisation
- Governance frameworks adapted to maturity level
- Concrete execution plans for transformation projects
Adaptation to functions and industries
- Other organisations and maturity levels
- Service businesses with manual inquiries
- SMBs that want to structure AI work before larger investments
Marius Ottesen
Commercial leader and AI strategist
Develops business-oriented concepts, workflows and digital solutions at the intersection of commercial leadership, people, technology and practical AI.
Explore the project further
Get in touch if you would like to discuss how a concrete AI case can be developed from idea to practical and responsible implementation plan.