On the road to developing a strategy, executives and other business leaders are often stalled by questions about how and where to begin implementing AI across their companies; the cultural changes that AI requires companies to make; and how to build and use AI in ways that are responsible, protect privacy and security, and comply with government rules and regulations.
A team at Microsoft have launched AI Business School to help business leaders navigate these questions. The free, online course is a master class series that aims to empower business leaders to lead with confidence in the age of AI.
AI Business School course materials include brief written case studies and guides, plus videos of lectures, perspectives and talks that busy executives can access in small doses when they have time. A series of short introductory videos provide an overview of the AI technologies driving change across industries, but the bulk of the content focuses on managing the impact of AI on company strategy, culture and responsibility.
The business school complements other AI learning initiatives across Microsoft, including the developer-focused AI School and the Microsoft Professional Program for Artificial Intelligence, which provides job-ready skills and real-world experience to engineers and others looking to improve their skills in AI and data science.
Unlike these other initiatives, AI Business School is non-technical and designed to get executives ready to lead their organizations on a journey of AI transformation.
Nick McQuire, an analyst who covers artificial intelligence for CCS Insight, said more than 50 percent of the companies his firm has surveyed are already either researching, trialing or implementing specific projects with AI and machine learning, but very few are using AI across their organization and identifying business opportunities and problems that AI can address.
INSEAD, a graduate business school with campuses in Europe, Asia and the Middle East, partnered with Microsoft to build the AI Business School’s strategy module, which includes case studies about companies across many industries that have successfully transformed their businesses with AI.
For example, a case study on Jabil describes how one of the world’s largest manufacturing solutions providers was able to reduce overhead costs and increase production line quality by using AI to check electronic parts as they are manufactured, freeing up employees to focus on value added activities that machines are unable to do.
“There is still a lot of work that has got to have the human capital piece in it, especially if it is not something that lends itself to standardized processes,” explained Gary Cantrell, senior vice president and chief information officer for Jabil.
A key to implementing AI, Cantrell added, was the leadership team’s focus on clearly communicating to employees the company’s strategy around AI – to eliminate routine, repetitive activities in order to free them up to focus on activities that cannot be automated.
“If they are guessing or they are speculating, it is undoubtedly going to become counterproductive at some point,” he said. “So, the better job you do at keeping the team glued together with where you are going, the better the adoption will be and the faster it will be.”
Prepping an AI-ready culture
The culture and responsibility modules of AI Business School also place a core focus on data. After all, companies that successfully embrace AI need to openly share data across departments and business functions, explained Azizirad, and make sure all employees can participate in the development and implementation of data-driven AI applications.
“You need to start out with an open approach to how the data of an organization is going to be used, which is the foundation of AI, to get the results that you are banking on,” she said, adding that successful leaders foster an inclusive approach to AI that brings different roles together and breaks down data silos.
To illustrate the point, the Microsoft AI Business School surfaces a case study from Microsoft’s marketing team, which wanted to use AI to better score leads for the sales team to pursue. To build the solution, marketing employees partnered with data scientists to create machine learning models that weigh thousands of variables to score leads. The collaboration brought together marketing employees’ knowledge on lead quality with the machine learning expertise of data scientists.
“In the case of AI and in the case of culture, the people closest to the business problem you are trying to solve really need to be involved,” said Azizirad, adding that the sales team is embracing the lead-scoring model because they trust it will produce high-quality leads.
AI and responsibility
Building trust also comes from developing and deploying AI systems in a responsible manner, an area that Microsoft’s market research has found resonates with business leaders. Among high-growth companies, the research found, the more leaders know about AI, the more they recognize that they need to make sure the AI is deployed responsibly.
The AI Business School module on the implications of responsible AI showcases Microsoft’s own work in this area. Course materials include real-world examples in which leaders at Microsoft learned lessons such as the need to safeguard AI systems against malicious attacks and the need for systems to detect bias in datasets used to train models.
“Over time, as companies become operationally dependent on these machine learning algorithms and models that they built, there’s going to be much more focus on governance,” said McQuire, the CCS Insight analyst.
