Last week, I facilitated a cross-functional workshop with The World Economic Forum, and several tech startups (Noodle A.I., Rage Framework, Enterra) to investigate the impact of Artificial Intelligence (AI) on global production and value chain.
The cross-functional discussion explored many topicsfrom the underlying technology progress to the trigger points for impact and adoption across individuals, firms and governments, and the broader societal consequences of AI adoption.
Some key emerging themes from the session:
1) The very definition of A.I. itself is vague – we had many different definitions of AI, machine learning, etc. across participants in the room. Coming out of the session, we arrived at a consensus definition of AI as any algorithm software system that can generate foresight and insight through learning. See below for a break-down of sub-set of A.I. algorithms and techniques:
2) The current breakthrough in AI performance, enabled by innovations in underlying processing hardware, learning software, and proliferation of big data (tagged and structured data) will continue to advance to unlock faster, smarter, and more intuitive applications
3) Progress will be limited in near term to narrow types of AI (software that can learn specific problems for targeted domains) rather than general AI (software that can generalize and learn with limited and noisy data)
4) AI use cases are already pervasive – spanning from applications that impact individuals, factory floor, business value chains and eco-systems
5) Adoption however will be non-uniform, as use cases across functions and sectors will be largely dictated by private sector ROIs. In the short term, AI will likely eliminate more net jobs than it creates and further accelerate the well studied “winner take all” dynamics
6) AI will accelerate a broader trend that new products will increasingly compete and generate value through their digital functionalities rather than traditional physical features – with significant implications on business models and supply chains
Policies and social attitude that drives lifelong learning and entrepreneurship are key to manage society’s transition to the AI “cognitive” revolution.
Read the full findings here: “Will You Embrace AI Fast Enough” | “WEF – Technology and Innovation for the Future of Production”