Define the problem
Turn ambiguous workflows into clear product opportunities
London Business School / Data Science & AI Initiative
Build AI products for LBS
A hands-on lab where participants turn LBS workflows into useful AI products through discovery, building and evaluation
Current batch · Fall 2026
Nine selected teams are developing projects across academic work, student services, campus life and investment research
Current batch
Fall 2026 projects
Meet the nine selected teams and the problems they are working on.
In development
1MBA
MBA course preparation in one place.
View team In developmentLBSOne
One interface for everyday LBS services.
View team In developmentOff-Campus Compass
LBS guidance for students moving to London.
View team In developmentRA1
Club expenses from submission to reimbursement.
View team In developmentVishmay
Find flatmates and connect with lease handovers.
View team In developmentBreadcrumb
Discover London events and people to go with.
View team In developmentThe Key for Sussex
Keep applications, deadlines and coffee chats together.
View team In developmentRoboTrade
Company research with sources attached.
View team In developmentSimply AI
Find rooms, facilities and step free campus routes.
View teamWhat participants learn in the Lab
Participants develop the product, technical, and leadership skills needed to build AI products from problem discovery to launch
Understand the user
Run interviews, map needs, and identify where AI can create value
Manage stakeholders
Work with participants, alumni, clubs, staff, and partners to navigate constraints and adoption
Build with AI
Use AI-assisted tools to prototype and ship quickly
Evaluate and iterate
Test quality, learn from feedback, and improve the product
Think toward product-market fit
Move from a promising demo to something people understand, adopt, and return to
Spring 2026 Batch
Explore the Spring 2026 batch
Nine teams joined the first LBS AI Lab batch to build AI products for LBS workflows
Prototype
RecruitSmart LBS
An AI-powered job search co-pilot built for LBS students.
View team PrototypeLondon Eats Pal
A discovery platform for top-rated cafes and restaurants near campus.
View team PrototypeEMS++
A coherent curriculum planner for MBA elective selection and timetable management.
View team PrototypeLBS Compass
A knowledge-base chatbot for incoming students navigating LBS.
View team PrototypeFundEd
A funding discovery and matching platform for prospective LBS students.
View team PrototypeBriefd
One master calendar for LBS events, jobs, and opportunities.
View team PrototypeWayfinder
A mobile guide to rooms and facilities across LBS campuses.
View team PrototypeEventOS
AI-assisted club event planning, venue sizing, and form generation.
View team PrototypeZentra
AI-generated client WIP updates and fee tracking for legal billing.
View teamFall 2026 mentors
Guidance from product and technical mentors
Teams are supported by product and technical mentors through build sessions, product reviews, implementation guidance, and feedback cycles
Academic lead
Academic lead
Kostis Christodoulou
Clinical Professor of Management Science and Operations; Academic Director (MBA, MAM, EMBAG)
Kostis supports the academic direction of the Lab, connecting participant teams with rigorous AI, analytics, decision-making, and product learning
Product Mentor
Zahra Mogadasi
Product discovery, user feedback loops, and clearer positioning.
Profile
Product Mentor
Tiffanie Terry
Tiffanie is a product leader with nearly 20 years in consulting and product strategy. She has built and launched digital products for brands like PayPal and Harley-Davidson, and has led and scaled high-growth product teams. She'll help pressure test your idea to clearly define the problem, users, and strategy to build an MLP (Minimum Lovable Product).
Profile
Technical Mentor
Akshay Nagpal
Akshay leads product at a Series A startup in London, building AI-native consumer products. An Oxford MBA graduate, his background spans product management, data engineering and machine learning, with experience at ING Bank and Nokia. He’ll help teams sharpen their product ideas, design agentic AI workflows and turn early concepts into working products people love.
Profile
Technical Mentor
Alessandro Condorelli
Alessandro is an AI Developer at London Business School, where he builds agentic AI systems and works on applying emerging technologies to real business problems. His background spans AI, analytics, finance, and entrepreneurship, with experience building solutions for organizations including LBS and Harrods. He can help teams turn early ideas into practical solutions, particularly around AI, data, and product development.
Profile
Technical Mentor
Ivan Ante
Former investment manager who led a US$2bn+ multi-asset team and founded two education companies, Flosendo and Eden. Ivan helps teams decide what to build, choose AI tools and test their product.
Profile
Product Mentor
Shreyas Parbat
LBS MBA candidate with around five years in AI products, from data science at Grab to AI automation at an early-stage London startup. Shreyas helps teams develop their AI product, run simple experiments and learn from users.
ProfileNext batch
Join the next batch
Register your interest and find other LBS builders.