Evidence of friction abounded in conversations on stage and off at the World Economic Forum’s “Summer Davos” held in Dalian, China this week. Whether it was friction around the U.S.-China trade sanctions standoff, or concerns about the ethical boundaries of artificial intelligence, it was clear that business uncertainty may be our new normal, at least for a while.
And that’s okay. Frictions around a growing economy like China’s should be expected. They’re growing pains. In fact, it’s these very signs of friction that demand a lubricant for business in China and for those who do business with China. And that lubricant is trust.
Where there is uncertainty in any marketplace, believable information, transparent knowledge sets and collaborative models shine through. Shared knowledge will always be more powerful than walled gardens.
As China moves to a more consumer-led economy in terms of its GDP mix, we expect more opportunities to unlock new spending habits and new consumer aspirations. Despite the noise of geo-politics, consumers in China will continue to spend at pace, but we expect the mix of spending to change. More brands, more premium options, more channels through which to purchase, all mean we have expanding opportunities to engage consumer wallets.
But to tap into these changing habits, blind spots on changing consumer demand will need to be removed. Our collective jobs is to uncover those blind spots to help fuel this consumer-led cycle of growth.
Chinese Premier Li Keqiang told us this week that the government will push to create an equal playing field in the country for all companies. And that is welcome news. Open business models will fuel growth that consumers are demanding of us.
We’d be wise to listen to those consumers. We live in a world where consumers are more disloyal to their favorite brands than ever in history. Attributes like price, taste, brand halos and the like will continue to be important, but a growing pile of evidence points to trust as a key attribute to which consumers gravitate.
Trust extends to things like ethical supply chains, sustainable business practices and clean ingredients. But, as we heard at the World Economic Forum event this week, it also extends to how data sets are managed in a world where artificial intelligence (AI) and machine learning have increasingly bigger roles to play.
We saw concerning examples of AI that delivered discriminating outputs; we saw survey results that demonstrated clear concerns around so-called “bad” AI. But we also saw some great examples of good AI, such as providing development paths for hospitals of the future and addressing modern slavery.
And there’s the rub. Not all AI is created equal. Good AI requires the highest quality “training data” to provide foundational quality levels that build to believable outputs. The key to unlocking consumer growth in China and, perhaps more importantly, in partnership with China, will be built on a foundation of trustworthy knowledge. Poor quality inputs, or worse, manipulated inputs that tie to agendas, will undermine trust. Independent data sets, where truth is the only agenda, will be the lubrication we need.