
10 ways AI can support learning and skills resilience (or not)
AI can do plenty in terms of learning and skills development – but educators and talent leaders also need to understand what AI tools should not be used for. ...

by Michael G. Jacobides, M. Dalbert Ma, Konstantinos Trantopoulos , Vasilis Vassalos Published January 15, 2025 in Brain Circuits • 3 min read
Despite being the most widely used performance metric, focusing on engagement as an end in itself tends to be counterproductive. Focusing narrowly on engagement without a clear sense of how the game will add strategic value often brings difficulties.
Different goals (customer acquisition, expansion, refining market positioning) call for different design elements. Once you know your objectives, give designers and engineers a clear brief and choose the right KPIs to gauge success.
For instance, if the desired strategic outcome is user lock-in, one route to success is to design a game featuring social comparison based on desirable user identities while excluding tangible rewards. But if the goal is to shape users’ values and beliefs, the game needs to hold their attention over the long term (for example, through engagement in virtual worlds and social comparison).
Choosing the right KPIs will prevent the project from being led astray by ‘nice-to-have’ wins that are irrelevant to your strategic goal. (For example, if you want to gain market share by selling more to existing users, focus on the number of new users the game attracts.)
One of the mantras in the digital arena is that success often requires experimentation and numerous iterations to achieve optimal results. While there’s some truth in this, our analysis suggests that ‘trying it all’ is counter-productive and associated with failure.
There are three critical design features of games (virtualization, social comparisons, and tangible rewards). Neglecting to incorporate any of these features in the project is a sure pathway to failure.
Incorporating undesirable social identities and attempting to promote them will cause gamification to fail, regardless of which other features are incorporated: users will not buy into social identities or comparisons they do not like or cannot relate to.
Strategic clarity and understanding which paths work – and which don’t – are key in gamification, so keep these priorities in mind when designing projects and beware focusing on metrics that relate purely to engagement as the end goal.
The business value of gamification: three pathways to new customer acquisition
The business value of gamification: Pathways to customer retention
The Business Value of Gamification
Play to win: Enhancing customer engagement with gamification
Beyond subscription models: recurring revenue-generating patterns

Michael G. Jacobides is the Sir Donald Gordon Professor of Entrepreneurship & Innovation and Professor of Strategy at London Business School. He studies industry evolution, value migration, firm boundaries and organization design. He is the Chief Expert Advisor on the Digital Economy at the Hellenic Competition Commission and a co-author of the WEF’s white paper on digital platforms and ecosystems. He served on the Global Agenda Council of the World Economic Forum and has presented at the Davos Annual Meetings.

Dalbert is a PhD candidate in the Strategy and Entrepreneurship department at London Business School. He has a Masters in Management from IESE Business School, a Master of Laws with a specialization in competition law from Erasmus University Rotterdam, and a Bachelor’s in Philosophy, Politics and Economics from the University of York. Before academia, Dalbert was involved in financial technology research at China’s central bank and in infrastructure project financing at Deloitte Financial Advisory.

Advisor and Research Fellow at IMD
Konstantinos Trantopoulos is an Advisor and Fellow at IMD, working with senior executives, boards, and investors globally on growth, value creation, and profitability. His work focuses on how organizations shape strategy and translate it into measurable value through people, leadership, processes, and emerging technologies including AI. His insights have appeared in Harvard Business Review, MIT Sloan Management Review, California Management Review, MIS Quarterly, Το Βήμα, and Forbes. He is also the co-author of Twin Transformation, available on Amazon.

Vasilis Vassalos is leading the Information Processing Lab and is the Director of the MSc in Data Science at the Athens University of Economics and Business. He has received numerous awards and has been Principal Investigator for over 15 funded research and advanced development projects since his arrival at AUEB. He is the author of over 70 technical publications and two US patents. He received a Diploma in Electrical and Computer Engineering from the National Technical University of Athens, and his MS and PhD in Computer Science from Stanford University.

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