Data is at the center of the great transformations that digital technologies are causing in today's world. That is why in the last decade we have seen the rapid rise of companies that have focused their business model on the value of data. Artificial Intelligence is one of the fastest developing technologies in the world, in part thanks to the vast proliferation of data. It is transforming society and our quality of life.
Some studies predict that AI could add around €14 trillion to the global economy by 2030, and double economic growth rates by 2035. Today's leaders need the knowledge and confidence to ensure that their organizations are prepared to capitalize on the opportunities offered by Artificial Intelligence, through the direct and indirect impact on employees, customers and the business ecosystem, successfully incorporating it into their main strategic lines.
This program is designed for company executives who want to understand the fundamental concepts of Artificial Intelligence and be able to implement machine learning technology in their business processes. Candidates will be able to acquire the knowledge and analytical skills necessary to lead an organization powered by Artificial Intelligence. Through the most recent advances in computer science and management, we will explore successful use cases, transforming complex business problems into business value and relevant information for decision making.
Course program
Module 1. Discovering AI: Opportunities, Challenges and Design Strategies
What is AI and what can it do for you? Discover how artificial intelligence can empower people, products and business decision making. Learn what AI can (and can't) help you solve, and how AI helps you design the best solutions for your organization.
- Basic concepts of AI operation
- Top leading approaches that can be achieved
- Knowledge of the tools and techniques for the design of AI in your products and decision making
- Learning the artificial intelligence technologies that leading companies use today and in the future
- Ethics in artificial intelligence: risks and challenges
Module 2. Application of AI to real-life organizational problems
Discover how sophisticated data and artificial intelligence capabilities can be used in different areas (product, marketing, operations) to solve business and financial problems.
- How can you identify business problems and challenges that AI can solve?
- Knowledge of the capabilities, limitations and challenges of AI within the business
- How a leader can make AI operate in product development, people management, and financial decisions?
- Discovery of the main AI use cases that are transforming businesses, as an example (top 3 by sector)
Basic materials
- Predict commodity price patterns based on satellite data (or similar visuals)
- Predict agricultural yields from data sets including site images and IoT sensor scans
- Predict the risk of animal health problems by analyzing audio patterns
Financial Services
- Customer churn prediction
- CIdentification of fraudulent activities using unusual payment transaction patterns and other data
- CImprove life insurance by predicting lifestyle risks based on habits identified on social media
- CImprove administrative productivity with robotic process automation
- CConsumer goods and services sector
- COffer a "digital human" conversation interface with customers in physical locations
- CProposal of new store locations
- CIdentify the next best offer in the customer journey to drive desired behavior
- COptimize the variety of products in the store to maximize sales
Energy
- Predict energy demand trends based on data sources ranging from sensors to social media
- Predict problems and recommend proactive maintenance for mining, drilling and support equipment
Healthcare
- Predicting the risk of developing a disease at an early stage
- Improve the surgical skills of doctors with robotics
- Diagnosis of known diseases from scans, images, biopsies, audio, and other data
- Identify patterns of fraud, spending and abuse from clinical and operational data
Industry
- Improve the quality of the construction process by detecting errors
- Automate aircraft piloting
- Detect defects and quality problems during production using visual and other data
- Predict future demand trends and potential supply chain constraints
Telecommunications
- Optimize network resource allocation based on real-time and predictive load analysis
- Predict regional demand trends for telecommunications traffic
- Secure communications through the deployment of cryptographic technology
Transportation
- Automation of customer service interruption alerts
- Traffic/passenger flow optimization through visual data, including video and images
- Personalization of loyalty programs and promotional offers for individual customers
Public sector
- Predict the probability of traffic accidents or queues and optimize the traffic system to reduce risk
- Detect potentially fraudulent users
- Optimize the allocation of public resources for urban development to improve the quality of life
- Predict macroeconomic variables based on government, private and public data
Utilities
- Power plant energy management and scheduling optimization based on energy prices, weather, and other real-time data
- Optimization of energy prices and systems for recommending offers to customers
- Smart home devices that manage consumers' energy consumption
Module 3. AI in the company: transforming your business
¿Cómo puede preparar su negocio para una transformación exitosa de inteligencia artificial? La construcción de una organización data-driven requiere de una transformación cultural y tecnológica. How can you prepare your business for a successful AI transformation? Building a data-driven organization requires a cultural and technological transformation.
- Learning organizational designs that enable the development and implementation of successful AI initiatives, from data infrastructure or algorithmic fluency to driving a data-driven culture
- How does AI impact workers? How are roles defined? How is talent promoted?
- Discovery of best practices in project selection, team building and execution