Artificial Intelligence in Sales & Marketing
Corporate Training Courses Company

Artificial Intelligence in Sales & Marketing

Course schedule

Classroom Training:
DateVenueDurationPrice
6 - 10 Jul 2026London5 days£4,995
21 - 25 Sep 2026London5 days£4,995
15 - 19 Jun 2026Dubai5 days£4,995
13 - 17 Jul 2026Cape Town5 days£4,995
10 - 14 Aug 2026Istanbul5 days£4,995
14 - 18 Sep 2026Riyadh5 days£4,995
12 - 16 Oct 2026Dubai5 days£4,995

Please note: prices shown above are exclusive of VAT (20%).

If you don’t see your preferred course date, please contact us.
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Course Overview

Delegates discover how AI enhances project planning, scheduling, and delivery. The course covers predictive analytics, resource optimisation, and automated reporting. Participants learn to use AI tools for improved decision-making. The programme equips project professionals to lead data-driven, adaptive, and efficient projects.

Who Should Attend

Marketing and commercial professionals using AI tools for customer engagement and campaign analytics. Past delegates have included:

  • Marketing Managers
  • Sales Executives
  • CRM Analysts
  • Brand Strategists
  • Digital Marketing Specialists

Course Outcomes

  • Apply AI to segment markets, predict customer behaviour, and personalise outreach.
  • Use automation to optimise lead scoring and campaign performance.
  • Analyse sentiment and consumer insights through AI-based analytics.
  • Measure ROI using machine learning-driven attribution models.
  • Design AI-integrated digital marketing strategies for sustainable growth.

Course Topics

Introduction to Artificial Intelligence

  • Understand AI principles and types across industries.
  • Identify opportunities and challenges in AI adoption.
  • Evaluate emerging AI technologies and their impact.
  • Discuss the ethical, legal, and social implications of AI.

AI in Decision-Making

  • Apply AI insights for operational and strategic decisions.
  • Integrate predictive analytics to improve decision outcomes.
  • Use AI for scenario modelling and data interpretation.
  • Manage biases and transparency issues in algorithmic decisions.

Ethical AI and Governance

  • Implement frameworks for responsible and transparent AI use.
  • Identify ethical risks associated with automated decision systems.
  • Design governance models ensuring fairness and accountability.
  • Promote stakeholder confidence in ethical AI implementation.

AI for Marketing Optimisation

  • Use AI algorithms to identify target audiences and optimise ad spend.
  • Leverage predictive analytics to forecast campaign success rates.
  • Analyse customer engagement using AI-driven behavioural insights.
  • Apply automation to personalise and scale marketing communications.

AI in Sales Strategy

  • Apply AI forecasting for sales pipeline and revenue projections.
  • Design intelligent CRMs that automate sales recommendations.
  • Use analytics to monitor sales team performance in real time.
  • Incorporate AI tools to increase conversion and client retention rates.

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