Role Overview
AIM Research is the world's leading media and analyst firm dedicated to artificial intelligence. We are seeking a Business Head of Research to lead our AI and GCC research practice, own the P/L, and grow our product portfolio. This role will drive strategic direction for flagship offerings (such as PeMa Quadrant), launch new products and services, oversee vendor briefings, and manage a high-performing research team. The ideal candidate will combine deep domain expertise in AI and global capability centers with strong commercial acumen and leadership skills.
Key Responsibilities
1. Strategic Leadership & Team Management
- Hire, mentor, and retain a multidisciplinary research team (analysts, data scientists, and editors) focused on AI, GCC trends, and emerging technologies.
- Define annual research objectives, set clear KPIs, and foster a culture of high output and continuous learning.
- Establish and enforce rigorous research processes, quality standards, and peer-review protocols across all deliverables.
- Collaborate with HR on organizational design, performance reviews, and career development plans for research staff.
2. P/L Ownership & Business Growth
- Create and manage the annual budget, revenue forecasts, and expense plans for the research division.
- Monitor profitability for all productsreports, subscriptions, custom advisory, and data servicesensuring targets are met or exceeded.
- Identify growth opportunities within the AI and GCC domains; propose new revenue streams, partnerships, and sponsorships.
- Collaborate with Sales and Marketing to build go-to-market strategies for PeMa Quadrant updates, new reports, data products, and custom research mandates.
- Present to senior leadership on financial performance, market trends, and strategic investments.
3. Product Portfolio Management
- Own existing flagship offerings (e.g., PeMa Quadrant) and ensure timely updates: collecting vendor briefings, assessing vendor submissions, and validating vendor positioning.
- Research, conceptualize, and launch new products and offerings (e.g., AI startup rankings, GCC Explorer enhancements, custom data dashboards, subscription-based intelligence).
- Prioritize product roadmap based on market feedback, competitive analysis, and client demand in AI and GCC spaces.
- Coordinate with editorial and design teams to produce high-quality, data-driven reports, infographics, and presentations.
4. Vendor Briefings & Ecosystem Engagement
- Develop and execute a structured vendor-briefing calendar: vet AI vendors, GCC service providers, and emerging technology startups.
- Lead briefing sessions, manage RFP processes for inclusion in PeMa Quadrant, and ensure fair, transparent evaluation based on methodology criteria.
- Cultivate relationships with vendors, ensuring they understand AIM Research's methodology, timelines, and data requirements.
- Evaluate vendor maturity, technology differentiation, and market positioning to inform inclusion decisions and advisory guidance.
5. Thought Leadership & Market Insight
- Identify high-value research themes: Generative AI, AI infrastructure, AI adoption in GCCs, vendor landscapes, emerging use cases, etc.
- Oversee the development of signature reports, whitepapers, and syndicated research that reinforce AIM Research's authority in AI and GCC intelligence.
- Publish regular market updates, blog posts, and newsletters summarizing key findings; represent AIM Research at webinars, podcasts, and industry events.
- Collaborate with product marketing to ensure research insights are translated into compelling messaging for conferences (Cypher, MachineCon, Happy Llama), emailers, and LinkedIn posts.
6. Client & Stakeholder Engagement
- Build and maintain strong relationships with enterprise clients, sponsors, and ecosystem partners (CIOs, CDOs, GCC leaders).
- Serve as the primary point of contact for custom research inquiries, advisory mandates, and strategic projects.
- Present research findings, brief clients on market dynamics, and recommend actionable intelligence tailored to client objectives.
- Work closely with Partnerships to identify co-branding, sponsorship, and joint-research opportunities with technology vendors and consulting firms.
7. Methodology & Data Integrity
- Define and refine research methodologies for AI vendor evaluations (PeMa Quadrant), GCC assessments (GCC Explorer), and custom data products.
- Ensure data collectionfrom primary interviews to secondary sourcesis accurate, unbiased, and up-to-date.
- Oversee analytical models, data visualizations, and interactive dashboards; validate insights before publication.
- Stay current on industry best practices, emerging research tools (e.g., Python, R, Tableau), and advances in AI/ML analytics.
Required Qualifications
- Experience: 15+ years in research, analyst, or advisory roles at a market intelligence firm, management consultancy, or technology analyst house.
- Domain Expertise: Proven track record analyzing AI ecosystems, GCC trends, or related technology markets.
- Leadership: Demonstrated success managing P/L, meeting revenue targets, and leading cross-functional research teams.
- Product Launches: Experience conceptualizing, developing, and launching research products (e.g., vendor quadrants, subscription services, custom reports).
- Vendor Ecosystem: Familiarity with organizing and executing vendor briefings, RFP processes, or technology evaluations.
- Education: Bachelor's degree in business, engineering, data science, or a related field; Master's or MBA preferred.
Core Skills & Competencies
- Strategic Thinking: Ability to translate market trends into actionable research roadmaps and go-to-market plans.
- Commercial Acumen: Strong understanding of P/L management, pricing models, and revenue growth strategies.
- Client-Facing: Excellent verbal and written communication; comfortable presenting to C-level stakeholders.
- Analytical Rigor: Proficiency in research methodologies, data analysis, and visualization tools (Tableau, Power BI, Python/R).
- Collaborative Mindset: Proven ability to work across functionssales, marketing, editorial, eventsand drive cross-departmental initiatives.
- Adaptability: Thrive under tight deadlines, shifting priorities, and fast-evolving AI/GCC landscapes.
- Quality Orientation: Meticulous attention to detail, ensuring methodological integrity and data accuracy in all outputs.
Key Performance Indicators (KPIs)
- Revenue & Profitability: Year-over-year growth in research division revenue; meeting or exceeding P/L targets.
- Product Launch Success: Number of new products launched (e.g., updated PeMa Quadrant, new data dashboards) and adoption metrics (subscriptions, downloads, inquiries).
- Client Satisfaction: Renewal and upsell rates, Net Promoter Score (NPS), and feedback from custom research engagements.
- Vendor Coverage: Number of vendors briefed, evaluated, and included in flagship reports; turnaround time for vendor submissions.
- Team Health: Employee engagement scores, retention rate, and performance against individual KPIs.
- Thought Leadership Impact: Citations, media mentions, webinar attendance, and social media engagement for published research.
