The world is increasingly driven by systems making decisions that were previously made by humans.
As these decisions become more high stakes and their logic more complex, let's consider the characteristics of the people and companies who will thrive in a world dominated by AI.
Most companies will benefit from the emergence of AI embedded in operational technologies.
Your supply chain may be improved if your suppliers optimise their own processes and leverage that improvement to better serve you.
And while your competitors may similarly benefit, the AI winners will be those companies that work out how to derive competitive advantage from their own unique AI initiatives.
One key advantage would be a unique data source which can be used to continually refine products, services and customer experiences to improve customer loyalty.
Google continues to improve its search algorithm, which drives further interactions which are used to deliver further improvements – a virtuous data-driven cycle of improvement acting as a "data moat" protecting market share.
Sadly, the number of companies that manage to scale up their analytics initiatives in production (around eight per cent according to McKinsey) remains stubbornly low.
Scaling up, however, is where the value lies.
AI experiments may deliver results that are interesting or potentially useful, but given the cost in time and resources, the real ROI is derived from creating autonomous business processes driven by embedded intelligence.
Vladimir Putin said whoever dominates the development of AI will rule the world.
If he's right, the risk is that countries with lax concern for AI ethics, protocols and standards will gain an advantage.
To succeed in an AI-driven world, Australia and New Zealand must ask what incentives and resources we can offer our researchers.
Australia and New Zealand are unlikely to create the next global cloud computing platform hosting AI systems or to monetise a brand-new form of algorithm.
We are, however, in a position to support a well-educated and creative workforce to promote innovation.
We can also assist local stakeholders in developing their data moats to ensure global competitiveness.
We mustn't allow offshore competitors to beat us to a data-driven understanding of local customer needs and behaviours.
If we do, it will be very difficult for us to sustain their loyalty.
At an individual level, the characteristics of winners are the same ones that have always enabled employees to thrive in disruptive times.
Individuals who are innovative and adept at learning new skills will secure the best opportunities.
Much as computers made typing pools redundant, typists who developed IT skills became more valuable.
AI will similarly transform the way humans work.
Employees who learn to use new tools to improve their personal performance will outpace their peers.
And although the debate about AI's ultimate contribution to job losses continues, it is likely that many more workers will have their jobs substantially augmented by AI than will be replaced by it.
Of course, companies that proactively help their employees evolve their skills and adapt to change will also benefit.
There is a false economy waiting for companies focusing exclusively on automation to the detriment of their workforce.
If the wellbeing of employees is ignored in a relentless pursuit of efficiency through AI-driven automation, the consequences for both employees and their employers could be dire.
So who will lose out?
AI thrives with large, diverse, high-frequency volumes of data.
Companies that have failed to master big data to serve their BI or Advanced Analytics goals may simply not manage to adopt AI successfully.
Similarly, if your data moat is not kept well protected in terms of governance, maintenance and controlled evolution, then the foundations of your AI programs will easily crack.
Given that last year, only one-third of IT executives stated that a top priority for 2019 was the curation of high-quality datasets for analytic purposes, how many organisations are truly setting themselves up for AI success?
Organisations that don't ensure their AI systems are trustworthy – meaning fair, accountable, transparent, ethical and robust – will struggle to succeed.
Many high-profile lessons have been learnt in recent years by big tech companies where AI systems fell short on some of these criteria.
As a result, they required significant rework to address stakeholder requirements for things such as gender neutrality or transparency.
Large companies with momentum in AI adoption may withstand such setbacks but those just embarking on their AI journey who hit similar hurdles may set their AI programs back years while their competitors move ahead.
And who will win?
In short, some key winning attributes will be…
- People: Those with a talent for quickly adopting new tools.
- Companies: Which promote the evolution of their data assets and their employees' abilities, and transfer successful innovations into production
- Countries: Which provide an environment that rewards innovation and research.
Obviously, there are many other facets to this discussion, though these are the ones that most caught my eye.