AI-based strategies in business development

Fundamentals and strategic classification

• The role of AI in business development: introduction to deep learning, machine learning and their applications.
• Data analysis made easy: algorithms for market analysis and customer profiling.
• Interactive exercise: Building a data pipeline (understanding and applying ETL processes).
• Practical use of tools such as TensorFlow, Power BI, Tableau and OpenAI.

Consolidation and practical application

• Case studies: Analysis of successful business development processes in companies that use predictive analytics and machine learning for lead generation (e.g. Salesforce Einstein, HubSpot AI tools).
• Hands-on session: Implementation of AI tools - practical introduction to the use of chatbots for customer interaction (e.g. Dialogflow, GPT APIs).
• Prototype of an AI-based business development module - creation of an MVP (Minimum Viable Product) for a specific company.
• Systematically identifying and developing new business areas with the help of AI.

My Case

• Development of an individual new business strategy with AI.
• Creation of a convincing business plan with financial planning.
• Targeting and winning over stakeholders.

Implementation and future outlook

• Risks and ethical considerations in the use of AI - discussion on topics such as bias in machine learning, data privacy (GDPR) and transparency in algorithms.
• Practical use of Natural Language Processing (NLP) and RPA (Robotic Process Automation) for automation projects.
• Strategy rollout plan - development of a detailed plan for implementing the technologies learned into the existing business strategy.