AI in business
Designing a course on AI for business owners requires a comprehensive outline that covers various aspects of artificial intelligence and its practical applications in business. Below is a sample course outline for an AI for Business Owners course:
Module 1: Introduction to AI in Business
- 1.1 Overview of Artificial Intelligence
- Definition and key concepts
- Historical development of AI
- Types of AI: Narrow AI vs. General AI
- 1.2 Importance of AI for Business Owners
- Enhancing efficiency and productivity
- Gaining a competitive edge
- Identifying business opportunities with AI
- 1.3 Common AI Terminology
- Machine learning, deep learning, natural language processing, etc.
- AI applications: Robotics, computer vision, recommendation systems, etc.
Module 2: AI Technologies and Tools Overview
- 2.1 Machine Learning Basics
- Supervised learning, unsupervised learning, reinforcement learning
- Training and testing data
- 2.2 Deep Learning
- Neural networks
- Deep neural networks and their applications
- 2.3 Natural Language Processing (NLP)
- Understanding and processing human language
- NLP applications in business
- 2.4 Tools and Platforms
- Overview of popular AI frameworks (TensorFlow, PyTorch)
- Cloud-based AI services (AWS, Azure, Google Cloud)
Module 3: AI Implementation in Business
- 3.1 Identifying Business Problems Suitable for AI
- Case studies of successful AI implementations
- Assessing feasibility and ROI
- 3.2 Data Collection and Preprocessing
- Importance of quality data
- Data cleaning and preparation
- 3.3 Building AI Models for Business
- Selecting the right algorithm
- Training and fine-tuning models
Module 4: Ethical Considerations in AI
- 4.1 Ethical Issues in AI
- Bias and fairness
- Transparency and accountability
- Privacy concerns
- 4.2 Implementing Ethical AI Practices in Business
- AI ethics policies
- Responsible AI development and deployment
Module 5: Integration of AI into Business Operations
- 5.1 AI in Marketing and Sales
- Customer segmentation
- Personalization and recommendation engines
- 5.2 AI in Operations and Supply Chain Management
- Inventory optimization
- Predictive maintenance
- 5.3 AI in Finance and Decision-making
- Fraud detection
- Risk assessment
Module 6: Overcoming Challenges in AI Adoption
- 6.1 Addressing Resistance and Cultural Shift
- Change management strategies
- Employee training and upskilling
- 6.2 Managing Security Risks in AI Systems
- Cybersecurity considerations
- Protecting sensitive data
Module 7: Future Trends in AI and Business
- 7.1 Emerging Technologies
- Quantum computing
- Edge computing
- 7.2 Continuous Learning and Adaptation
- Staying updated on AI advancements
- Future-proofing AI implementations
Module 8: Capstone Project and Case Studies
- 8.1 Applying AI Concepts to Real-world Business Challenges
- Group projects
- Analysis of successful AI implementations in various industries
Conclusion and Graduation
- Closing Remarks
- Recap of key learnings
- Opportunities for further exploration in AI for business
Benefits of this course
Ability to assess the implications and applications of AI in your industry and build a business case for its implementation
Robust framework to critically examine the social implications and ethics of AI
Accounting for AI — a Comparison of Methods
Open Access Resources for AI in Schools
On AI-Generated Works, Artists, and Intellectual Property
Can ‘we the people’ keep AI in check?
ChatGPT And Beyond: What’s Behind The AI Boom?
Expert warns of AI tools’ potential threat to democracy
ChatGPT could be a useful AI tool. So how are we regulating it?
Meet The Three Artists Behind A Landmark Lawsuit Against AI Art Generators
BKC Policy Practice: Artificial Intelligence
The Ethics and Governance of Artificial Intelligence Initiative
Ethics and Governance of AI Reading List
Ethics and Governance of AI Supporters, Collaborators, and Friends
Ethics and AI: 3 Conversations Companies Need to Have
Great promise but potential for peril
The state of AI ethics: The principles, the tools, the regulations
An Overview of Artificial Intelligence Ethics and Regulations
Conceptual understanding of machine learning algorithms, deep learning and neural networks
Guidance from leading industry experts
Topics
Artificial Intelligence ecosystem.
Explore the history and potential of AI within the context of the digital ecosystem.
AI and machine Learning: Understanding the black box.
Delve into the mechanics of the three main types of machine learning: supervised, reinforcement, and unsupervised learning.
Understanding deep learning and neural networks.
Understand what deep learning is and how it is powering the modern approach to AI.
Working with intelligent machines.
Explore the concept of intelligence in machines and the impact of AI in the labour market.
The ethics of artificial intelligence.
Explore the hierarchy of ethical and legal considerations around AI.
How to drive AI in your business.
Identify the potential business opportunity of AI in a specific context.
Who Invented A.I.? - The Pioneers of Our Future
The 10 Best Examples Of Artificial Intelligence (AI) And Machine Learning In Practice
Who Invented A.I.? - The Pioneers of Our Future
Top 10 Applications Of Artificial Intelligence in 2021 | Artificial Intelligence Training | Edureka
How Artificial Intelligence Will Transform Businesses
How to Insert AI into business processes and what are the critical factors to consider?
Artificial Intelligence might sound like something from the future, but it’s already helping thousands of organisations grow their revenue and work more efficiently. Use our check-up tool to see how it could benefit your business.
Using AI in Business: Examples of Artificial Intelligence Application in Business
MIT Bootcamps: How to identify business opportunities with AI
AI For Business Specialization
Artificial intelligence in business Examples of artificial intelligence use in business
7 Applications of Artificial Intelligence in Business
9 top applications of artificial intelligence in business
EMERGING AI AND DATA DRIVEN BUSINESS MODELS IN EUROPE
Top 10 Executive Courses in AI and Machine Learning
Massachusetts Institute of Technology (MIT) - Sloan School of Management - Executive Education
AN INTRODUCTION TO ARTIFICIAL INTELLIGENCE
This introductory module guides you through the evolution of key AI technologies and how they have developed to transform industry and business practice. The relationship between AI and collective intelligence, as well as the implications of this partnership for business strategy and society are also introduced. As part of an ongoing project, you’ll begin to consider your own organization in terms of the application of AI technologies.
MACHINE LEARNING IN BUSINESS
In this module, you’ll explore the core concepts of machine learning – an AI technology which aims to design, understand, and use computer programs to learn from experience. Discover how machine learning can be successfully integrated into business functions through rich case studies and faculty-led videos that examine the opportunities that this subfeld of AI affords. For your ongoing project, you’ll propose ideas for the application of machine learning in a business context of your choice.
NATURAL LANGUAGE PROCESSING IN BUSINESS
This module is devoted to natural language processing (NLP), an AI technology developed to intelligently process human language. Through rich case studies and faculty-led videos, which explore functions such as machine translation, summarization, and sentiment analysis, you’ll learn how NLP can be skillfully deployed in a series of business contexts. For the next part of your project, the focus will shift to NLP and its strategic implementation in a business context of your choice.
ROBOTICS IN BUSINESS
Rise of the Robots: Nvidia and Adobe announce A.I. partnership
This module delves into the key elements of robotics as a transformative AI technology, with a focus on automating processes and tasks. Through rich case studies and faculty- led videos that survey robots and autonomous vehicles, you’ll learn how robotics can beneft an organization. You’ll have the opportunity, once more, to submit ideas regarding the potential for robotics to be deployed in a business context of your choice
Watch: Hyundai revealed a one-armed robot that charges your electric car for you
ARTIFICIAL INTELLIGENCE IN BUSINESS AND SOCIETY
Artificial Intelligence’s Impact on Business
In this module, you’ll see examples of other kinds of AI as well as return to collective intelligence and the human-machine relationship. Here you’ll also consider the impact of AI on jobs, and the ethical and social implications of AI integration. You’ll be tasked with anticipating and planning for the risks and considerations that may apply to integrating AI in a business context of your choice.
What Are The Negative Impacts Of Artificial Intelligence (AI)?
THE FUTURE OF ARTIFICIAL INTELLIGENCE
Beyond ChatGPT: what chatbots mean for the future
This module will allow you to imagine the future of AI and its potential use in your organization. Using what you have learned from the previous modules, you’ll create a business roadmap for the strategic implementation of AI and collective intelligence into an organization of your choice.
Artificial Intelligence: Implications for Business Strategy
ARTIFICIAL INTELLIGENCE: IMPLICATIONS FOR BUSINESS STRATEGY
AI Business Models
10 Business Models That Reimagine The Value Creation Of AI And ML
Comparing 5 AI Business Models – Part 1 – Transformation or Near-Term Value?
Near-Term AI Trends – A Guide for Mid-Size Business Leaders
The AI Career Gap – AI Knowledge as a Career Accelerator
The Ultimate Guide to Understanding and Using AI Models (2023)
AI Creates New Business Models
Choosing The Right AI Business Model
Personal Impact Mission (13 October 2021)
Yukiko Kobayashi
Big Data & Data Management (18 October 2021, 15:00-17:00)
Prof. Dr. Thomas Hofmann, ETH Zurich & Dr. Jürgen Galler, CEO 1plusX
AI & Machine Learning (27 October 2021)
Prof. Dr. Damian Borth, University of St.Gallen
The Platform Economy (03 November 2021)
Dr. Holger Schmidt
Nicole Büttner, Co-founder & CEO Merantix Labs
AI, Ethics and Regulations (17 November 2021)
Prof. Dr. Valentin Jeutner, University of Lund & Nanda Bergstein, Director Corporate Responsibility - Tchibo
AI-based Leadership (23 November 2021)
Prof. Dr. Miriam Meckel, University of St.Gallen & Léa Steinacker, Co-Founder and Chief Operations Officer of ada
Learning objectives
Learn existing functions within banks to uncover potential inefficiencies
Compare and contrast how standard versus digital banks perform given functions in your country
Determine the best tactics to attract new customers for loans and identify the holes in the way customers are currently found
Consider which functions would be better utilised with machine learning or artificial intelligence
Understand the limitations of ML and AI and how to use them to analyse results and determine risk factors
Artificial Intelligence, Machine Learning and Genomics
AI vs. Machine Learning vs. Deep Learning vs. Neural Networks: What’s the Difference?
The Limitations of Machine Learning
Limitations Of Machine Learning: Facts You Should Know
The Limitations of Machine Learning
Apply the concepts and applications of ML and AI to real-world scenarios
Determine situations that should utilise cryptocurrency versus digital fiat currency
Sort risks according to whether they apply to fintech or regular financial institutions
Predict which functionalities will remain in banks or switch to an outside entity
Develop a plan for integration of fintech within a financial organisation
What you will learn
Module 1: Digital Transformation and Financial Services
Module 2: Personal Banking
Module 3: Lending Markets
Module 4: Applications of Machine Learning in Fintech; Risk Management and Credit Scoring
Module 5: Digital Distributed Ledger: Blockchain and Cryptocurrencies
Module 6: Regulations
Module 7: Fintech Capstone Project
EXPLAINED a guide to AI for executives
The single biggest technology revolution the world has ever seen
Is AI anything more than the latest technology buzzword?
So what is AI anyway?
AI as we know it isn’t really a technology in its own right at all.
Wait, haven’t we been there before?
AI is far from a new idea, with a term coined as long ago as 1956, how far have we come?
Ok, I’m sold. But what do I actually need to do now?
In such a fast-moving field, it can be hard to see the wood for the trees.
Hold on, we haven’t talked about the risks involved
It pays to begin an AI journey with a clear sighted vide of the risks involved.
And what about the bigger picture?
The actions we take when it comes to AI can reverberate way beyond the boundaries of a single organisation.
It’s time to get smart and get started
As it gains critical mass, AI will change how we work and live, forever.
Unlocking the power of artificial intelligence in the digital age
Artificial intelligence (AI) is empowering significant and rapid change for businesses across almost all sectors and industries. In particular, machine learning – a computer’s capacity to improve its performance without human instruction – is driving the development of new applications that can accelerate productivity and competitive edge for companies.
From the automation of different aspects of business to forecasting patterns in data, AI can accomplish tasks with far greater accuracy and speed than human beings – transforming not only what businesses and managers can do, but how they do it. Healthcare, finance, retail and travel organisations are delivering completely new customer experience thanks to chatbots, intelligent voice assistants and conversational AI. Meanwhile, an array of new machine learning applications are giving businesses access to deep analysis of key internal data (such as employee engagement, networks and departures) for organisation redesign.
Transforming Your Business with AI gives you a deep understanding of how AI is deployed in business, so that you can see what it can (and cannot) do for you and your organisation. The programme equips you with practical frameworks and templates to work with data scientists and programmers, showing you how to commission analysis and analyse the results you receive.
How you benefit
Gain solid, jargon-free understanding of AI, Machine Learning and the opportunities for your organisation.
Understanding AI And Machine Learning Concepts To Build Your AI Leadership Brain Trust.
Explore how different applications work across functional areas.
9 top applications of artificial intelligence in business
Master the skills and vocabulary to work effectively with data scientists.
3 in-demand AI skills that boost data scientists' development
10 Essential Skill Sets For Data Scientists
11 data science skills for machine learning and AI
Data Scientist Skills: Definitions and Examples
10 skill sets every data scientist should have
Bias in Data
There’s More to AI Bias Than Biased Data, NIST Report Highlights
Towards a Standard for Identifying and Managing Bias in Artificial Intelligence
Understand the risks and limits of relying blindly on algorithms.
5 Rules to Manage AI’s Unintended Consequences
Learn how to build AI capabilities for your organisation.
15 Ways To Leverage AI In Customer Service
Building the AI-Powered Organization
Work on individual or group Action Learning Projects, with feedbacks from Learning Coaches, to solve real business problems within the context of your actual job and organisation.
Participant profile
Transforming Your Business with AI is designed for:
How Artificial Intelligence Will Transform Businesses
Senior executives who want to understand how they can make their organisations AI-ready
Leaders and senior executives seeking the comprehensive perspective they need to lead in a digital world, with a focus on the strategic, organisational and innovation implications of AI and data technologies
Senior managers seeking to build their own capabilities in strategy, leadership and innovation, while developing personalised, actionable plans
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Learning objectives
Learn about digital technologies used in digital transformation projects
The 4 Pillars of Successful Digital Transformations
What is digital transformation?
Explore the sources of value of digital transformations for businesses
Consider challenges of privacy and security in digital transformations
Digital transformation: Key technology, cybersecurity and privacy risks
Assess digital tools, technologies, processes and their uses
Evaluate the use of digital solutions for business problems
Suggest new business solutions that are enabled by advances in digital technologies
Apply principles of digital transformation to real-world business problems
4 Principles to Guide Your Digital Transformation
Develop a framework for digital transformation within your organisation
Propose digital innovations that build on existing business infrastructure
Recommend appropriate approaches to infrastructure, data governance and change management to support digital transformations
Technologies Driving Digital Transformation
The Cloud and Mobile
The Internet of Things
Big Data Analytics
Automation and Artificial Intelligence
FinTech and Blockchain
Implementing a Digital Transformation
Sources of Value in a Digital World
A Framework for Implementing a Digital Transformation
Considerations of Privacy and Security
AN INTRODUCTION TO ARTIFICIAL INTELLIGENCE
This introductory module guides you through the evolution of key AI technologies and how they have developed to transform industry and business practice. The relationship between AI and collective intelligence, as well as the implications of this partnership for business strategy and society are also introduced. As part of an ongoing project, you’ll begin to consider your own organization in terms of the application of AI technologies.
MACHINE LEARNING IN BUSINESS
In this module, you’ll explore the core concepts of machine learning – an AI technology which aims to design, understand, and use computer programs to learn from experience. Discover how machine learning can be successfully integrated into business functions through rich case studies and faculty-led videos that examine the opportunities that this subfeld of AI affords. For your ongoing project, you’ll propose ideas for the application of machine learning in a business context of your choice.
NATURAL LANGUAGE PROCESSING IN BUSINESS
This module is devoted to natural language processing (NLP), an AI technology developed to intelligently process human language. Through rich case studies and faculty-led videos, which explore functions such as machine translation, summarization, and sentiment analysis, you’ll learn how NLP can be skillfully deployed in a series of business contexts. For the next part of your project, the focus will shift to NLP and its strategic implementation in a business context of your choice.
What is artificial intelligence (AI)? What does it mean for business? And how can your company take advantage of it?
Through an engaging mix of introductions to key technologies, business insights, case examples, and your own business-focused project, your learning journey will bring into sharp focus the reality of central AI technologies today and how they can be harnessed to support your business needs.
Focusing on key AI technologies, such as machine learning, natural language processing, and robotics, the course will help you understand the implications of these new technologies for business strategy, as well as the economic and societal issues they raise. Examine how artificial intelligence will complement and strengthen our workforce rather than just eliminate jobs. Additionally, the program will emphasize how the collective intelligence of people and computers together can solve business problems that not long ago were considered impossible.