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Target Audience

Innovation Managers, Chief Information/Digital Officers, Computer Scientists Developers with business interest, Management/Business Administration Experts, Talent program participants aspiring for C level.

Learning Target

Participants should have an understanding of the current state of AI applicability in business with a special focus on machine learning and deep learning technologies. On one hand they will get an overview of the AI provider landscape specifically connected to each organisational function, on the other hand they will understand the general principles of how AI technologies work today, and where they are going in the near future.

  • Broad understanding of different artificial intelligence technologies and applications in the enterprise environment
  • Learning about the landscape of AI driven technology providers in specific business areas
  • Understanding how AI is transforming the future of business on an organisational level with special emphasis on the sales and marketing, customer service, manufacturing, supply chain management and the supporting functions (HR, finance, backoffice)

Contents

  • How does AI help and how does it work
    • 10 use-cases with specific business impacts
    • What is AI? - hype versus reality
    • Trends in AI - investments, development areas, the overview of the AI development market
    • How does AI work? - understanding the conceptual layers of different AI applications
    • How does it learn? - data and procedural requirements for AI systems to learn, understood through personal experiences

  • Applications in in Sales and Marketing
    • Technology merges the Sales&Marketing channel into a unified customer journey
    • Addressing new customers: customer profiling and mass message customisation to lookalike audiences
    • Converting customers: from recommender engines to sales team management solutions
    • Contracting with customer: CRM based recommendation (B2B), and e-commerce closing boost (shopping assistants and search engines in B2C)
    • Delighting the customer: monitoring and reacting to market feedback, predicting churn

  • Applications in Manufacturing and Supply Chain management
    • Data driven supply chain that drives horizontal integration with buyers and suppliers
    • Reducing inventory and transportation costs with big data analysis: from demand forecasting to route and inventory optimisation
    • AI in Industry 4.0

  • AI applications in Customer service HR
    • Boosting zero level support: chatbots and intelligent search engines
    • Managing the customer service team: from transcripts to voice sentiment analysis and predictions
    • The recruitment revolution: from targeting passive talents to CV processing and video interviews
    • Onboarding assistance with robotic process automation and chatbots
    • Talent management, knowledge management and employee churn management with network analysis and natural language processing

  • Applications in Legal, Finance and Backoffice
    • Processing contracts for sensitive clauses with NLP
    • Identifying sensitive information for GDPR compliance with pattern recognition
    • Improving audit with processing invoices at scale
    • The SSC automation opportunity: robotic and cognitive process automation


Methodology

Interactive lecture, group work, practical practice activities, reflection

Duration

5 days

Dates and Locations

Functional Questions

Organisational Questions