How Artificial Intelligence Optimizes Prospect-Focused 1:1 ABM: An Exploratory Study of AI Integration into Marketing workflows
Author
Andersen, Zanine Valentina Varela Tourinho Custódio
Term
4. Semester
Publication year
2026
Submitted on
2026-06-01
Abstract
This thesis explores how Artificial Intelligence (AI) can optimize prospect-focused 1:1 Account-Based Marketing (ABM) in B2B settings where complex buying processes and resource-intensive tasks make targeted efforts essential. Using a qualitative, exploratory design based on semi-structured interviews with practitioners in marketing, sales and go-to-market roles and applying thematic analysis, the study examines real-world AI use and integration within ABM workflows. Findings show that AI is being applied across all core ABM activities: in account identification, AI supports data enrichment, lead scoring, qualification and prioritization by analyzing firmographic, technographic, intent and behavioral data; in account intelligence, AI accelerates the gathering, enrichment and synthesis of internal and external information to improve customer research and stakeholder analysis; and in personalized engagement, AI enables content creation, campaign optimization, segmentation and scaled personalization. A strong data foundation anchored in CRM systems and marketing automation is critical for successful integration. Two integration paths emerge: AI-enabled martech platforms connected to CRM and more advanced, agentic AI systems capable of autonomously executing interconnected marketing tasks. At the same time, concerns around trust, governance, data privacy and output reliability necessitate continued human oversight. The thesis provides empirical insights into current AI integration in prospect-focused 1:1 ABM and concludes that AI primarily augments rather than replaces human decision-making, with organizations possessing robust data and governance capabilities best positioned to gain competitive advantage.
Denne afhandling undersøger, hvordan kunstig intelligens (AI) kan optimere prospektfokuseret 1:1 Account-Based Marketing (ABM) i B2B-kontekster, hvor komplekse købsprocesser og ressourcekrævende aktiviteter gør målrettet arbejde afgørende. Med udgangspunkt i en kvalitativ, eksplorativ tilgang baseret på semistrukturerede interviews med praktikere inden for marketing, salg og go-to-market-funktioner samt tematisk analyse, belyser studiet både anvendelser og implementering af AI i ABM-arbejdsgange. Resultaterne viser, at AI i stigende grad anvendes på tværs af de centrale ABM-aktiviteter: I identifikation af nøglekonti understøtter AI data-berigelse, lead scoring, kvalificering og prioritering ved at analysere firmagrafiske, teknografiske, hensigts- og adfærdsdata; i account intelligence effektiviserer AI indsamling, berigelse og syntese af information fra interne og eksterne kilder til bedre kunde- og interessentindsigt; og i personliggjort engagement hjælper AI med indholdsproduktion, kampagneoptimering, segmentering og skalering af personlige budskaber. En robust datafoundation, forankret i CRM-systemer og markedsføringsautomatisering, er central for succesfuld integration. To integrationsveje træder frem: brug af AI-aktiverede martech-platforme forbundet til CRM samt mere avancerede, agentbaserede AI-systemer, der autonomt kan udføre sammenhængende marketingopgaver. Samtidig kræver spørgsmål om tillid, styring, dataprivatliv og outputpålidelighed fortsat betydeligt menneskeligt tilsyn. Afhandlingen bidrager med empirisk indsigt i, hvordan organisationer aktuelt integrerer AI i prospektfokuseret 1:1 ABM, og peger på, at AI primært forstærker menneskelig beslutningstagning, mens organisationer med stærke data- og governance-rammer står bedst rustet til at opnå en konkurrencemæssig fordel.
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