COVID-19 has had profound effects on the global economy. While some industries took a hard hit, others found new opportunities — such as machine learning.
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The challenge of COVID-19 has accelerated a number of existing technology and business trends creating significant opportunities for companies that offer or deploy artificial intelligence. But it has also presented new, never-before-experienced problems for them.
Over the past six months, society has undergone a 101 course in statistics. People for whom datasets used to be a foreign language now look with interest at the latest statistical results to see whether the curve is indeed being flattened. They are following the variables and attempts to identify the key parameters and extrapolating from the information available to make predictions about prospects for the future. In short, large sections of society have become familiar with graphs, charts, databases, and even the basic principles of machine learning (ML).
Many who were previously suspicious of the advance of technology are increasingly regarding it as an ally not a foe, less as part of the problem and more as part of the solution. The population in general, and jobholders in particular, are a lot more accustomed to the idea of deploying AI to bring about change. The question is no longer whether to use AI, but how best to use it.
Innovation: From nice to have, to need it now
On the one hand, we have startups that have traditionally found their niches by looking for emerging cracks in the market. For them, COVID-19 has been a shattering earthquake, opening new rifts and chasms. On the other hand, we have legacy businesses that used to regard innovation as something of a luxury that might add something to their bottom line. Today, they recognize innovation as a critical necessity vital for their survival.
For everyone involved, it’s not only the scale of the change, but the pace of change too. Online shopping in the US, for example, accounted for 13% of total sales in January 2020. Five months later, in May, this had risen to 80%. Not only has the hourglass been flipped but the sand is running out as never before.
In this unexpected environment of 2020, ML has proven to be invaluable in more ways than what we could have imagined. Here are three takeaways from its continuing rise.
1. Traditional and legacy businesses are turning to startups for agile, real-time, machine learning-powered solutions. Many companies urgently want to transition and adapt to ecommerce, deploy solutions that deliver cloud optimization, and map and retrain workforce skills to adjust to the new work-from-home economy.
2. While AI startups help traditional businesses adapt to the new landscape, they themselves are not immune from the impact of COVID-19. One the casualties of the current disruptions is the value of data itself. Most predictive analysis relies on existing datasets, but these reflect pre-COVID behaviors and habits and are far less relevant and reliable in a black swan period like the current one. A critical challenge is to rebuild data models at high speed, based on fewer data points. Legacy and traditional companies must work with only those startups that come up with solutions to do precisely this.
3. The very speed at which decisions need to be made in the current environment itself creates new vulnerabilities. A natural tendency in large corporations is to centralize data to facilitate decision making. At the same time, the search of capital efficiencies is encouraging businesses to cooperate more closely, with increased openness. These are wise and necessary steps, but they require caution. They can increase the potential impact of any breach and the effects of bias in the process of analysis. Large corporations can seek startups that address such issues.
In a time of such upheaval, I’m witnessing large corporations look for the right startups, more than the other way around. In their urgent need to onboard agility and adaptions, corporations are the ones making the effort to reach out. This shift can bring about many critical and fruitful partnerships, but all parties need to look out for emerging risks and pitfalls in the new and changing landscape. In this new environment the hibernators won’t survive. Adapters will.
Judah Taub is co-founder and managing partner at Hetz Ventures. Previously, Judah acted as a senior consultant on data and technology for Lansdowne Partners ($20B London-based Hedge Fund), as well as an advisor to multiple young startups. He has lectured widely, including at Wharton Business School. He was elected as one of Forbes 30 Under 30 for 2020. He holds a B.A. degree in business and economics from the Interdisciplinary College in Herzliya, Israel.
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