Artificial Intelligence for Business

The course will provide an introductory overview of the various existing AI techniques, putting them into an historical context
which is essential to understand how we arrived to the recent sensational exploit of AI applications and what can we expect from the near future. We will discuss industrial applications with their opportunities and challenges, touching also on some social, economic and ethic implications which will be deepened in other courses. A specific focus will be on the interaction between AI and robotics, given the relevance of artificial intelligence applications for manufacturing and industrial automation.

Getting value from data requires the design of a composite chain that begins from a strategic vision to the implementation, exploitation and continuous operation management. This course offers a preliminary and systemic vision to the use of the latest methodologies and techniques for extracting useful knowledge that will be explored in other courses of the Master.

Computer Vision is at the heart of the AI revolution. Machines nowadays can not only see better than ever but also generate realistic visual content spanning images, videos and 3D assets. We will walk through ideas and applications, shedding light on how computer vision may be deployed in controlled environments, e.g. in manufacturing,  “in the wild”, e.g. in assisted/autonomous driving,  as well as to generate cool stuff for applications largely yet to come.

The first part of this course provides the basic knowledge of the main concepts and principles of cybersecurity (e.g., risk, risk assessment and evaluation, attacks and their typical structure, resources, human component). Some specific aspects regarding the methodology, the technology and the behavior (i.e., operational security) will be considered mainly through a case-study approach. The most relevant outcome of this part of the course will be a better awareness of the main cybersecurity problems of current systems (and future AI applications), all the while acquiring a proper cybersecurity-aware mindset.

The second part of the course introduces the main components of the ICT infrastructure, both considering the computational infrastructures (e.g., CPU, GPU, TPU, FGPA, ASICS) and the networking components. The cloud computing and edge computing architectures such as quantum computing will be sketched and their challenges will be discussed.

Technical features will be considered while also taking in account the cost-related aspects.

The course will introduce participants to the value of using immersive paradigms in data analytics. It will walk through the principles underlying the design of immersive analytics systems, exhibiting how such type of systems may facilitate collaboration and change the process of data analysis.

In the contemporary fast-paced and ever-evolving landscape of modern business, innovation is no longer a mere optional, but rather a categorical imperative for survival. No company, whether large incumbent businesses or early-stage startups, can afford not to master the discipline of innovation in a structured and rigorous way. Within this context, AI has emerged as a transformative force, reshaping not only how companies operate but also the fundamental dimensions of what they offer and how they organize themselves.

This course aims to provide participants with the skills and the knowledge necessary to manage AI from a business innovation perspective in a disciplined way, to understand, embrace, and harness the potential of AI to reshape the future of business.

Participants will learn how to assess the value of AI for business and recognize the different ways AI can revolutionize different aspects of business innovation, such as products, services, processes, organizational structures, and business models. The goal is to develop a clear understanding of the levels, stages and business contexts in which AI systems can generate innovation advantages. To this end, students will have the opportunity to analyze complex case studies to understand the risks and opportunities related to AI adoption, identify the main barriers to its diffusion and develop formalized strategies to overcome them.

In addition and building on the idea that AI should be focused on providing value to end-users, participants will learn how to assess whether AI solutions address the crucial needs of customers and other end users by helping them accomplish significant tasks or “get an important job done.” This user-centric perspective ensures that AI is not just a technological novelty but a meaningful asset that improves people’s lives and solves real-world problems.

Furthermore, the course offers participants to acquire the skills to prioritize AI opportunities effectively. They will follow a structured process that revolves around assessing organizational goals and winning aspirations, aligning AI initiatives with the overarching vision of the business.

By the end of this course, participants will be well-prepared to navigate the AI landscape and lead their organizations into a future where AI is an integral and value-driven component of their business strategy. “Reinventing Business with AI” is the gateway to understanding, embracing, and harnessing the potential of AI to reshape the future of business.

Value creation is the relevant key success factor of long term business competitive advantage and managers are increasingly exploiting and exploring new business value creation opportunities. Management challenges are dealing with multiple critical levers that span from successful market and product decisions, pricing and process efficiency, to effective cost management and business model innovation. In this context performance understanding and performance management systems can play a relevant role into the unveiling, implementation and monitoring of value creation initiatives.

The course aims to provide the relevant knowledge for understanding organizations’ business financial performance and how business analytics can be applied to support the decision-making process of different business areas. Specifically, it focuses on the measuring and understanding of financial and value creation ratio, and on cost analysis and business analytics applications for supporting the decision-making process.

The landscape of business decision-making has undergone a profound transformation, courtesy of artificial intelligence. This evolution has the potential to bring forth pivotal advantages—enhanced accuracy, heightened efficiency, and a remarkable ability to unravel intricate patterns. Integration of AI into the decision-making processes not only holds the potential to refine precision but also positions organizations to secure a competitive edge through well-informed, data-driven, and strategically sound decisions.

In the first part of the course, we address the critical trade-offs involved in adopting Machine Learning methods for decision-making in business contexts. The course equips participants with both conceptual and practical skills needed to assess the costs—both social and economic—against the tangible benefits that these systems bring to the realm of corporate innovation.

In the second part of the course, we address how Artificial Intelligence can be used for (combinatorial) optimisation, in alternative to, or in combination with, Machine Learning. We introduce the main features of the Constraint Programming paradigm and the MiniZinc language, to show how this approach can be used to build Intelligent Decision Support Systems.

This is not an abstract exercise. Through in-depth case studies, students dissect the real-world complexities associated with AI adoption, gaining insights into the nuanced landscapes of risks and opportunities. The curriculum demands an interdisciplinary mindset, where technical expertise aligns seamlessly with the practicalities of business strategy, fostering a robust understanding of how AI amplifies decision-making capabilities.

Ethics and Politics

The module focuses on the family of AI narratives that shape public perceptions of the relationship between ethics, politics, law and technology.

These include AI ethics, anthropomorphism, value alignment, the principle of technological inevitability, the myth of technological exceptionalism, the principle of innovation, and the myth of the legal void. Indeed, falling prey to such narratives leads to poor business decisions.

Law for AI

The course will provide an overview of the main legal issues related to the creation and use of AI systems in many fields, with a focus on how such issues should lead companies to reconsider crucial aspects of their business strategies.

Specific attention will be paid to the duties imposed on businesses developing AI systems, especially focusing on the developments of laws and standards at EU level (e.g., the proposal for an Artificial Intelligence Act), as well as on companies employing AI in their business activities. The course will also deal with many of the aspects related to liability for damages caused by AI, from product liability to general civil and criminal liability rules. A specific focus will concern the legal implications of the use of AI-based automated decision-making systems by boards of directors or company managers (so-called “CorpTech”), as well as of the use of generative AI

Implementation of AI projects is a challenge that passes through people, this needs conscious leaders, able to facilitate the work of heterogeneous teams and get the most out of people both in terms of problem finding and change making. We will use the discipline of emotional intelligence to embed the neuroscience of change and build on this scientific approach to arrive to an action model.

The course aims to provide the right tools and competences needed to become a change maker in organizations in particular how to increase the awareness of the impact of leadership, support the management of the ordinary resistance to create new patterns of action, communicate and collaborate in teams to obtain extra-ordinary results.

This course is designed to provide participants with an understanding of how artificial intelligence (AI) and machine learning (ML) can be used to create value in various business contexts. In this course, participants will learn how to identify opportunities to apply AI and ML in different business areas, such as marketing, finance, operations, and customer service.

This course is designed to empower participants with a profound grasp of digital transformation strategies and their relevance across diverse business domains. Over the span of three dynamic sessions, you’ll delve into fundamental principles of digital transformation, explore advanced strategies, examine varied data representations, and master essential tools for business analytics. Real-world case studies will be integrated, ensuring you can apply your knowledge effectively in practical scenarios.

This course aims to provide participants with a comprehensive understanding of machine learning methodologies and their applicability in various business sectors. Consisting of three intensive lectures, the course covers fundamental machine learning principles, advanced learning paradigms, different data representations, and essential business analytics tools. The course also includes real-world case studies to ensure practical applicability.

With this course, the candidates will understand Large Language Models, delving into the fundamentals of large language models, with reference to prominent language models such as GPT-3, BERT, and more. Will be offered an overview about LLM-based applications and their industry relevance, exploring diverse real-world applications of large language models across industries such as insurance, life science, finance, customer service, content generation, and more. They will navigate the Technological Landscape, through the assessment the current state-of-the-art and ongoing advancements in the field of large language models, learning about the available models, platforms, and providers to make informed decisions about integration and implementation. Will gain insights into the challenges and best practices associated with adopting large language models in business processes, identify potential roadblocks and develop effective strategies for successful integration. And finally will explore emerging trends and future developments in the realm of language models and artificial intelligence.

This course is designed to review the changes in the world of work, focusing on how digitalization, big data and the spread of Artificial intelligence are leading to a profound transformation of organizational, human resources and competencies systems and processes.

Basic knowledge will be provided to conduct the analysis and definition of process and organizational model design and successful implementation in alignment  with business strategy. Costs and benefits will be assessed, return on investment analyzed, as well as the impact of introducing AI solutions for human resource management in terms of organizational innovation, corporate culture and compliance

Bologna is located in the center of Emilia Romagna, third region in Italy by GDP, first by export value. Many companies in this area, which are industry leaders in the Automotive, Fashion, Packaging, Automatic Machinery, Food, Pharmaceutical, Ceramics and ICT & Software sectors, are part of the BBS business network.

During this 4-day residential at the BBS Campus in Bologna, you will meet managers and inspirational leaders who have designed and implemented successful AI-based projects for services, products, processes and business models innovation in different industries, you will participate in Challenge-Based Learning events during company visits, play Business Games with other participants.

The project work is developed in groups and on real cases (Companies from the BBS Business Network or companies proposed by participants). It is a comprehensive endeavor involving two distinct phases. In the first part, we focus on analyzing a specific business challenge and identifying AI-based solutions. The second part is dedicated to the practical development and implementation of an AI prototype to address the identified challenge. Throughout the project, we aim to provide valuable insights, actionable strategies, and a functioning AI solution to enhance business operations.