PAC Leadership Session
AI Adoption in the
Retail Industry
The right focus. The right approach. The right results.
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Validate Success

Activate Portofolio

Leverage Brand

Utilize Sales
Enhancing retail performance through AI-driven intelligence
European retail is accelerating its adoption of deep learning (DL) and machine learning (ML) to enhance customer engagement, optimize operations, and drive data-informed decision-making. As expectations rise for hyper-personalization, dynamic pricing, and predictive inventory management, traditional processes are under increasing pressure to evolve.
This session equips IT solutions and services leaders with insights into leveraging AI technologies to deliver seamless omnichannel experiences, improve demand forecasting, and strengthen supply chain resilience. It highlights strategic use cases where ML and DL can generate measurable commercial and operational impact.
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1.5-hour webinar

2-hour workshop

1-hour in-person presentation at an event
| Price €9,950 |
Designed for Your Business Goals
Market Intelligence Team
Analyst Relations Team
CEO/COO
CIO/CTO
Strategy Team
Sales Team
Marketing Team
Partnership Management Team
Chief Digital Officer
Product Management Team
Your Challenges
- Identifying high-value retail clients and understanding their DL/ML adoption priorities.
- Navigating complex client data, legacy systems, and fragmented decision-making processes.
- Minimizing lost opportunities caused by slow or generic technology recommendations.
- Delivering measurable business outcomes and ROI from DL/ML solutions to clients.
Your Benefits
- Provide targeted insights on DL/ML opportunities to align with client needs and reduce engagement friction.
- Access modular, expert-driven research tailored to specific retail technology challenges.
- Gain actionable recommendations for faster, higher-impact client engagements.
- Reduce uncertainty and resource waste by relying on validated market data and analyst guidance.
- Enhance credibility with clients through evidence-based strategies and use cases.
Session Agenda
- Analyze client demand for AI-enabled personalization, predictive analytics, and operational efficiency.
- Examine how the adoption of DL/ML influences retail market trends and competitive pressures.
- Translate customer expectations into actionable strategies for IT solutions providers.
- Provide practical recommendations to enhance engagement, differentiate services, and accelerate solution adoption.
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Meet Your Lead Analyst

Spencer Izard
Principal Analyst
Spencer Izard is a Principal Analyst at PAC, based in London, UK. He is the PAC research cluster lead for AI & Analytics, as well as Digital Customer Engagement (DCE). His primary research focuses on all forms of existing and emerging AI from a global perspective, aiming to support enterprise leaders in strategic decision-making and help software and services firms enhance client engagement and support their clients.
He is also a member of PAC’s cloud and security research clusters, where he focuses on the role of AI within these domains. From an industry perspective, he leads research and client engagements in the retail and banking sectors, drawing from his extensive experience in both.
Due to his 25+ years of career experience as a senior leader in enterprises, strategic advisor in software firms, and senior analyst, Spencer leads consulting engagements and creates research content that is focused on how enterprise leaders need to navigate technology change cycles to assist business outcomes and adoption patterns to aid in strategy creation and purchasing decisions. This perspective provides invaluable insight for software and services companies, helping them create effective strategies and engage with customers. It also assists senior leaders in enterprises in developing their digital strategy and preparing for RFI/RFP purchasing decisions.
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