Even before the pandemic, businesses were increasingly investing in AI and data science to improve efficiency, decision making and automate more processes. Like with so much else, COVID-19 and its social and economic repercussions are forcing change and potentially accelerating AI in business.
Notably, the economic crisis triggered by COVID-19 puts a premium on business efficiency and service improvements which when properly developed AI can deliver. Additionally, automation can potentially help fulfill social distancing within the workplace, deploying more robots to work alongside human workers.
With so much buzz around how AI could help businesses remodel and recover, businesses are looking to educational programs to help equip their leaders with the skills needed to understand the challenging and often confusing world of AI. Yet, how does this increased thirst for knowledge and AI itself affect working professional programs and the business schools that teach them?
Ahead of the pandemic, we published commissioned qualitative research with more than 20 business schools internationally on how they are responding to AI and developing their working professional programmes.
There are three striking trends we can see:
1. Cross-disciplinary integration
First, cross-disciplinary integration is a developing theme as business schools realize their students need to answer more than just technology questions about AI. Indeed, how this technology can have profound social effects in affecting jobs and making major decisions autonomously without human intervention.
There is growing evidence of more cross-campus and cross-disciplinary collaboration. One business school dean told us how their school is addressing how the ethical dimensions of AI is driving integration across university departments like computer science, philosophy and sociology. As a result, the University of California Berkeley created a new division, the Division of Data Science and Information, to address such needs.
2. Skills needed to run a workplace where humans and AI co-work
Second and unsurprisingly, business schools are beginning to train the skills needed to run a workplace where humans and AI co-work. As smart machines take over lower-level work, graduates will need to start contributing to their organization at a higher level than previously expected of recent graduates.
In part, this means how students get a stronger conceptual education on AI’s capabilities and potential for use when they must lead businesses reshaped by AI. Understanding how human fits in, there is also an emphasis on how to develop talent around emotional intelligence, logic, problem-solving and creativity.
Yet, many of the business schools fed back the importance of actual hands-on experience with AI itself. This also reflects a need for students to understand the hype around AI and give them the opportunities to see how humans and AI can work together, plus actually work with the tools themselves. The latter is valuable for working professionals who need to grasp the issues of AI ethics and bias, as well as understand the human in the machine angle of training and retraining AI.
Some good examples of how AI is becoming part of the business school curriculum are from Kellogg School of Management and Imperial College Business School.
At Kellogg, the school has added a “human-machine learning program” where students explore the intersection of cutting-edge tech and strategic human decision making. Other institutions have added classes like “digital transformation”, “AI strategy”, “digital immersion”, “how you manage in a technology environment”, “accounting analytics”, “supply chain analytics”, and many others.
Imperial College Business School offers an immersive, three-day program, “AI and Machine Learning in Financial Services,” that teaches the fundamentals of how AI and machine learning and can be applied to financial functions such as fraud detection, lending processes, asset management, risk assessment, regulatory compliance and beyond. In this program, participants explore the role of emerging algorithmic techniques on financial decisions, which they can then bring back to their workplace.
3. AI as part of the learning experience
And finally, of course, AI can become part of the working professional student learning experience itself. There is a wide variety of AI initiatives underway and most are aimed at augmenting how a business school connects and supports students. There’s also an expectation that AI can automate some of the routine administration and allow professors to concentrate on teaching rather than paperwork.
The biggest successes so far appear to be how quite simple AI like chatbots, and personal assistants can make the lives of students more productive and happier. A great example of this is the Deakin Genie at Deakin University in Australia’s which is a smartphone-based app that serves as a “hyper-personal assistant” for students – reminding them of upcoming assignments and deadlines and helping the students with research for an assignment, or book a classroom for group study. One European business school is using AI to promote human interaction among its students. Following research that highlighted student loneliness, a chatbot was launched that asks students if they want to be in a group and 19% of the school’s students opted in. The same system also welcomes all students online and asks if they need help.
Like the rest of society, AI is beginning to change working professional education and potentially business schools. While there is a need to resist the hype, the effects of AI will become more considerable over time, and therefore, it seems reasonable to assume business leaders may want access to programs which will help them adapt to better address a fast-evolving business landscape. This is even more true as old certainties are shaken up by the impact of COVID-19, and perhaps now is the time for all of us to experiment more boldly than ever before.
Michael Desiderio, executive director at the Executive MBA Council