Market validation and commercialization of dynamic AI governance - ON-1257

Genre de projet: Innovation
Discipline(s) souhaitée(s): Affaires, Sciences sociales et humaines, Science économique
Entreprise: FairFuture AI Inc.
Durée du projet: 4 à 6 mois
Date souhaitée de début: 01/04/2027
Langue exigée: Anglais
Emplacement(s): Toronto, ON, Canada
Nombre de postes: 1
Niveau de scolarité désiré: MaîtriseNouvelle diplômée/nouveau diplômé
Ouvert aux candidatures de personnes inscrites à un établissement à l’extérieur du Canada: No

Au sujet de l’entreprise: 

FairFuture AI is a Canadian company focused on Responsible AI research and development and building an enterprise AI governance platform. The platform is designed to help organizations maintain an AI inventory, assess risk, manage controls and evidence, and adapt oversight as models, data, policies and AI agent behaviour change. Fiara is the intelligence layer intended to simplify this governance experience.

Our ambition is to develop a global Responsible AI platform and a Canadian research hub through sustained academic and industry collaboration. These three projects address immediate commercialization and technical research priorities within that longer-term program. We aim to create commercially useful intellectual property in Canada, develop skilled Canadian talent, support future employment and build export opportunities. Research outputs are intended for incorporation into FairFuture's platform, subject to agreed academic IP, licensing and publication arrangements.

Veuillez décrire le projet.: 

FairFuture needs to validate customer demand and translate its Responsible AI R&D into a viable enterprise offering. This Business Strategy Internship will develop and test a commercialization model for dynamic AI governance and Fiara, the platform's intelligence layer. The innovation challenge is identifying which governance problems buyers will pay to solve, how continuous and runtime oversight should be packaged, and how a Canadian company can enter these markets.

The intern will define competing hypotheses about priority customers, buying triggers, decision makers and adoption barriers. Using desk research, competitor and substitute analysis, and approximately 15–20 structured interviews with governance, technology, security and procurement stakeholders, the intern will test the need and our proposed approach. Interview recruitment and a fallback outreach plan will be agreed with FairFuture; customer access is not assumed.

The intern will test alternative packages and pricing metrics using concept comparisons, willingness-to-pay interviews and cost-to-serve scenarios. Analysis will distinguish stated interest from purchasing evidence and examine procurement, deployment and data-residency constraints. Canadian beachhead options and a staged US/export pathway will be compared.

Month 1: hypotheses, segmentation and interview protocol. Month 2: discovery interviews and evidence-based product priorities. Month 3: package, pricing and unit-economics scenarios. Month 4: recommended business model, pilot offer, partner/channel strategy and a 12-month commercialization roadmap with milestones and decision gates.

Outputs will include an anonymized validation dataset, buyer and adoption analysis, pricing model, prioritized platform requirements and measurable pilot success criteria. Weekly meetings with FairFuture's founder and the academic supervisor will support analysis, mentoring and a final presentation. This is a business innovation project rather than routine sales execution; it supports commercialization of Canadian IP and future skilled employment.

Expertise ou compétences exigées: 

Required: customer discovery and structured interviewing; qualitative analysis; market segmentation and competitive analysis; enterprise software business models; pricing and willingness-to-pay assessment; financial modelling in Excel or equivalent; clear recommendations supported by evidence. Ability to separate assumptions, interview findings and validated purchasing signals is essential.

Preferred: an MBA or related master's student with experience in enterprise SaaS, innovation management or technology commercialization. Assets include familiarity with AI governance, Responsible AI, Canadian regulated sectors, procurement and international market entry. Technical coding is not required. The intern should be able to translate findings into product priorities and pilot criteria while protecting interviewee confidentiality. A suitable academic supervisor would bring expertise in entrepreneurship, strategy, marketing or commercialization.