AI in Business and Beyond

Jul 16, 2024

AI in Business and Beyond

Introduction Announcements

  • Career intent survey: Please complete the survey to help tailor the program based on your past experiences and outcomes expected. No specific deadline, but earlier submissions are preferable.

Historical Overview of AI

  • Key Trends
  • AI's future path explored through different data formats (structured/unstructured text, images, videos).
  • Introduction to the relational data model and data engineering.
  • Transition to understanding Machine Learning (ML): supervised, unsupervised, self-supervised, reinforcement learning.

Applications and Use Cases of AI

  • Explanation of the productivity increase AI offers, disruption in knowledge work, customer service, R&D, and professional services.
  • Group assignment for exploring AI applications in businesses.

Framework for Applying AI in Organizations

  1. Creativity Domain: Personalization using AI-generated avatars (e.g., ads, Hollywood actress contracts, personalized video ad featuring Jennifer Lopez, etc.).
  2. Productivity Domain: Enhanced by AI in knowledge work (e.g., Visual design tools like Runway ML, Diagram for UI design, Craft for customer research).
  3. Trust Domain: Address issues of deep fake, social trust erosion, and potential misuse (deep fake campaigns of politicians, misleading fake news).

Major AI Impacts and Challenges

  1. Creativity & Personalization: Enhances customer engagement, customizes ads dynamically, supports creative industries in marketing using AI-generated visuals.
  2. Productivity: Increases across Professional Services, R&D, product development, HR. Examples include AI tools (GitHub Co-Pilot for code suggestions, AI in business intelligence).
  3. Trust: The ethical challenge and societal impacts. Issues relate to deep fakes, fake news propagation, societal polarization.

Regulation and Guardrails for AI

  • Suggests frameworks and digitized verifications to regulate AI-generated content.
  • Possible blockchain solutions for tracking and authenticity.

Practical Assignment Guidelines

  • Assignment 1: Complete the Business Model Canvas for your organization.
  • Assignment 2: Create a one-page proposal for AI initiatives in your organization.
  • Assignment 3: Group assignment for creating a startup pitch involving AI.
  • Groups formed based on domain/industry.
  • Emphasis on fair contribution and grading within group submissions.

Notes on Group Formation and Assignments

  • Detailed guidelines will be provided via the Upgrad platform.
  • Email support provided for any clarifications related to assignments or group formation.

Negative Aspects of AI & Mitigation

  • Deep fakes, data privacy, creation of false information being major concerns.
  • Regulatory frameworks and the use of blockchain for content verification discussed.
  • Industry surveys indicate both the significant potential and risks of AI adoption.

Closing Notes

  • The importance of understanding the big picture implications of AI in multiple domains.
  • Preparation for emergent challenges and opportunities within organizational strategies regarding AI.

Summary: The lecture covers the historical perspective of AI, its application across various domains, and the significant productivity and ethical challenges it presents. It introduces practical frameworks to help businesses incorporate AI and manage its impact while ensuring fair and robust contribution in group assignments.