The massive snowfall in Davos this year certainly made getting around a little more challenging compared to years past, but that did nothing to dampen the conversation. We were fortunate to be at this year’s World Economic Forum, and after dozens of conversations with executives from around the world, we wanted to share a number of things that struck us about what we heard.
AI is growing up: Augmenting humans and social good
AI is top of mind for many executives, but the application of AI—and, more broadly, advanced analytics—is generating more thoughtful and nuanced conversations. While there are serious concerns about the social implications of AI, the reality is that it’s hard to see how machines can really be effective on their own, just as it’s hard to see how humans can work as well without machines. The most thoughtful organizations are looking to understand how AI can most effectively augment humans.
That idea of augmentation is playing through in other areas too. If you have good AI, you need processes to ensure the insights it generates are used. This is harder than it sounds. You can’t simply have a machine spitting out advice because people just won’t read it. By the same token, it doesn’t help to automate poor decisions. It’s all about finding ways to get the various technologies focused on what they do best, and then working together with humans to drive better results.
It was inspiring also to see how much focus there is on harnessing AI for social good. There is a significant opportunity for AI to help with big problems, from predicting the absence of rain in a region to managing mass immigration flows. While businesses are moving ahead quickly with AI, NGOs and regulators are far behind when it comes to the talent and capabilities needed. That may be changing, however. Increasingly there are courses on AI and social good being offered at cutting-edge technical universities, where there is strong interest from top students.
Gaining traction: Distributed ledgers (e.g., blockchain) and ecosystems
There is also a massive debate emerging around distributed ledger technology (more commonly referred to as blockchain, though that’s actually just one example of distributed ledger technology) specifically around its applications to businesses. There’s still lots of hype—often shaped by lack of true understanding of what the technology is—but also some real substance beyond its use for the cryptocurrencies that have been in the headlines. The promise of distributed ledgers lies in their ability to reliably, securely, and transparently access and share targeted sets of data.
Let’s take the example of sepsis, a dangerous but very preventable disease. Technology can help prevent sepsis by linking signals the body generates to historical health data. The analysis of this combined data could then signal danger signs before other symptoms arise and drive timely medical interventions. Distributed ledger technology could enable that kind of merging of data and analytics in a way that’s very hard to do today. Another example is banks that want to lend in emerging markets, where there is often no credit risk data, but widespread mobile phone usage. Through distributed ledgers, banks could access telco data to see potential customers’ phone bill payment records as a quick and reliable measure for loan suitability.
Distributed ledgers are also important for unlocking the cumulative power of ecoystems, which are increasingly a focus for businesses. It’s becoming clear to even the largest and most successful companies that they can’t do everything on their own. They are now concentrating much more on engaging in ecosystems of businesses, platforms, vendors, agencies, and the like through formal and informal partnerships, synergistic agreements, alliances, and other arrangements. However, ecosystems don’t happen at scale yet because of the difficulties getting different data systems to speak to each other with current technology. Distributed ledgers are the key ingredient to enable that level of communication and analysis.
Businesses are starting to put pilot teams together to understand how distributed ledgers work, and what the implications are for their businesses. We’re on the verge of some very interesting business models emerging from this.
Who’s got talent?
Almost everyone we spoke with mentioned how important the talent question has become. Of course, talent is always an issue but it’s now a CEO topic. There were three flavors of the talent challenge which we noticed:
- “I need to get my hands on some quality data scientists.” There is a limited number of these kinds of people, so the competition is intense (and expensive).
- “I need to train my senior people and managers to understand how to work with and lead these data scientists.”
- “I need to do something about the percolating social implications.” Many leaders are concerned about the implications that displacement of jobs by automation will have on society. Added to that is the fact that much of the employment growth in Western countries is in the gig economy. Leaders are looking at re-skilling as a cheaper and more effective approach than paying to hire and train new people. But that then requires the development of the capacity to develop, administer, and adapt a constant training function, because the reality is that many employees will need to be constantly learning and adapting. That includes thinking through the skills needed in three to five years, and beginning to develop that now before it’s too late.
Bold moves and what they mean for the organization
Many business leaders are thinking much more boldly about the changes they should make. One executive at an oil services business realized that they needed excellent advanced analytics capability to help manage their pipelines (such as for maintenance). His approach was to hire the best entrepreneur he could find and set up a self-standing business to specifically build out this capability. Not only did this executive believe it was the best way to build up an important capability quickly, it was also a talent play.
These bold moves are inextricably tied to organizational issues. Building out new businesses or figuring out how (or whether) to move to full-scale agile ways of working through the business raises all sorts of thorny questions: what does the governance look like? How do you make investment decisions? These are exactly the kinds of questions that reflect a deeper commitment to transformations at the core of the business.
The tough talk: Cybersecurity and looming “Techlash”
Overall, the feeling was very positive that the business outlook was good and the economy is flying. But below the surface there were very real and potentially damaging concerns. Cybersecurity is foremost among them, with companies locked in an arms race to stay ahead of (or even catch up to) highly sophisticated cyber criminals. It’s a big issue with CEOs and boards, and some of the business world’s best minds are trying to understand how to get the upper hand.
One other undercurrent of concern was around the idea of a “techlash,” or backlash against tech companies driven by fears that they are becoming too large and monopolistic. At one level is the basic concern that tech companies are just outcompeting incumbents, but beyond that there’s a sense that large tech companies are dictating terms to the marketplace, not taking privacy concerns seriously enough, and unfocused on the social implications of technology. Yes, to some degree this is driven by jealousy at the success these new tech businesses have enjoyed and the natural discomfort that comes with disruption. But there is also real concern as well with what’s happening to our society with these changes, and a sense that not all of it is good.
Despite the complexity of some of these issues and concerns, we were encouraged to see the discussion about them. Dialog is an indication of innovation to come.