Preparing for the AI revolution in Global Mobility

The past year has seen significant shifts in AI capability. ChatGPT is among the vanguard. While businesses, educators and governments assess the impact and risks of such technologies, where we are now as we prepare for the next Industrial Revolution? and how does this impact Global Mobility?

AI and AI-enabled technology is not new and is all around us. From iPhone’s Siri, to our home Alexa systems, android apps and chatbots, this next-generation technology is learning from us, predicting and preparing us for our next moves in all aspects of our home and working lives. What is new are the big questions for leadership around how to balance the economic and wellbeing benefits with the significant risks of this new age. Economic modelling from McKinsey published in June suggested new generative AI could add trillions of dollars to the global economy. The sectors set to gain most are banking, life sciences and technology.

Yet everyone can gain, not least with the ability to align customers and service providers closer than ever before, in what has been claimed as generative AI’s “breakout year”. To draw down the benefits, however, there are major questions around reskilling, business and personal leadership, including in education, and legislative frameworks on both a national and geographic regional level.


More mindful mobility?

This is not new to those of us in global mobility who have supported the moves of tech professionals at every level internationally for the past decade and more. What is new is how the global mobility supply chain can dovetail with clients and adopt AI in a way that both optimises cost and employee experience through forecasting and feedback; and that proactively addresses and identifies immediate and broader risks, including access to mobility opportunities.

“AI, including chatbots and machine learning, will continue a recent trend of significant transformations for Global Mobility functions,” confirms Tom Richardson, VP of solutions consulting at Equus. “We have been using AI for some time in areas like virtual assistants and recommendation algorithms. But the recent rise in popularity of large-language models has increased awareness and the adoption of new ideas across a range of functions and expertise.”

In relation to the risks associated with AI and machine learning, which include ensuring all-important compliance and diversity, equity and inclusion considerations that reflect an organization’s culture and mission, Tom Richardson says, “It is vital for teams to understand their responsibility in addressing challenges associated with AI and machine learning roll-outs, especially concerning algorithmic bias – which may lead to exclusion and discrimination. Primarily, this means ensuring that you have robust company governance frameworks with clear policies, ethical guidelines, and regular audits to current agreed standards.

”This vital focus on critical thinking and discernment is a reminder that AI and other technology are tools; not the answer on their own. “Transparency and ‘explainability’ in AI decision-making foster trust and accountability,” says Tom Richardson. These leadership qualities have been on the agenda for a while, reflecting the widening ESG focus. This is also something very much on the radar in international and higher education.

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