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After extensive discussions, society has gradually formed a consensus on the issue of "job losses caused by artificial intelligence". Never in the past few hundred years have we seen a new technology cause job losses so rapidly on a macro level. Therefore, in the long run, AI is unlikely to lead to large-scale unemployment, especially as the proportion of working-age people in the total population is declining in most developed countries. However, because of how quickly companies are adopting ChatGPT and other generative AI, we may see a large number of jobs replaced by AI in the short term.

If we compare the development of AI technology with the rise of electricity in the early 20th century, we find that it took decades for factories to convert steam-driven central transmission shafts into electric motors for single machines. For business owners at that time, if they wanted to take advantage of the emerging power technology, they had to reorganize the industry. However, the restructuring process in the last century has been very slow, giving the economy enough time to adapt. At the beginning of the transition between the two new technologies of electricity and steam, only new factories would use electric engines, so there was no large loss of jobs. In addition, electricity created new jobs, and workers laid off from steam plants could be transferred to the electric power industry. Greater wealth creates entirely new industries to attract workers, which raises workers' expectations of life.

In the mid-20th century, with the popularity of computers, something similar happened. Although the technology is developing faster than electrification, it still gives the economy enough buffer time to avoid mass unemployment.

The difference with AI is that major companies are now applying AI technology so rapidly in their daily operations that they are experiencing a wave of unemployment before the benefits arrive. In the short term, white-collar workers may be most affected. In fact, critics believe that society will usher in an "AI gold rush" powered by advanced chip manufacturers such as Nvidia, not a bubble. Goldman Sachs recently predicted that European and American companies will use this technology to replace a quarter of the human labor in current business operations, especially those workers who previously believed that they could avoid unemployment due to their professional knowledge.

To mitigate this risk, we have two possible options. The first is for government to step in, either to slow down the commercial adoption of AI (which is highly unlikely) or to provide special welfare programs to support and retrain the unemployed.

However, there is another, often overlooked, possible option that does not have the unintended consequences of government intervention. Some companies are rapidly integrating generative AI technology into their existing systems, not simply to automate tasks, but to help employees become more productive. Through a complete reset of corporate processes, managers can unlock new value-creation potential. If many companies do this, as a society we will create enoughThere are enough new positions to avoid falling into the dilemma of short-term job losses.

But will they? Even the most "Buddhist" companies can often do a good job in control, but innovation is another matter. In the past, we didn’t need to worry about this problem because there was enough time for some proactive and innovative companies to gradually change the industry. As they innovate over time, society can create new jobs to compensate for the slow loss of jobs in some industries and keep unemployment low. But from a macroeconomic perspective, we do not have enough time to adapt to the structural changes in the industry brought about by artificial intelligence.

Therefore, if they do not want to rely on government intervention policies, most companies in the market now need to speed up innovation so that the loss of jobs in the entire economy matches the rate at which new jobs are created. Generative artificial intelligence is rapidly entering business and social systems, but it also creates opportunities for companies to accelerate innovation. If enough companies can innovate spontaneously and proactively, then we don’t have to worry about unemployment caused by AI.

Of course, companies will not and should not enter the field of AI to solve macroeconomic problems. But luckily, they have enough business motivation to use AI. If companies can seize the AI ​​wave and create new opportunities, they will have a better chance of achieving long-term development.

Use AI to proactively attack

Some companies are now actively taking on The banner of promoting AI innovation has been raised. Elon Musk, a pioneer of recyclable rockets and electric cars, has pledged to make Twitter an artificial intelligence leader like Microsoft and Google. But Musk has always been known for his erratic behavior, and Twitter has yet to make a final decision on this commitment. So, what does it mean for a company to deploy artificial intelligence?

To answer this question, we first need to look at the factors that allow companies to respond to changes with ease. Tabrizi, a member of our research team, convened a research group to study 26 large companies with good financial data between 2006 and 2022. Based on comparable data and case studies of each company, the team divided these companies into three groups: high, medium and low from the two dimensions of agility and innovation.

What factors separate agile, innovative companies from those that are mediocre and conservative? The team narrowed the goal down to eight driving factors that influence agile innovation, namely purpose of existence, dedication to customer needs, positive psychological implications for colleagues, maintaining an entrepreneurial mindset even as the company expands, having the courage to pioneer, and being highly collaborative. , the ability to control rhythm, and bimodal operation. Most leaders extol these qualities, but it turns out, it is very difficult for large companies to maintain these characteristics for a long time.

Tabrizi also wrote an article explaining how Microsoft has become an industry leader by overhauling the hierarchy and establishing partnerships with companies such as Open AI. However, affected by the above driving factors, other companies have also made similar improvements and adjustments in the field of AI. In this article, we focus on two main drivers – the can-do spirit and the entrepreneurial mindset. Companies will be further along in agile innovation if they take full advantage of these drivers, because they drive change throughout the organization.

Be brave to pioneer

Recently, any company investing in AI has Possibly profit from it. Since AI investment has a clear contribution to cost reduction, the company may feel that it is not bad from the perspective of financial report data. However, pure investment will only bring about a single increase in profits. Companies that only focus on cost changes may miss opportunities to create greater substantial value. Better use of AI technology will help companies establish more solid industry barriers. Prudent investment cannot protect a company from competition in the long term, and certainly cannot help it escape the macroeconomic challenges it is facing.

“Pushing new technologies carefully, but still doing so-so” may be a problem that all new technologies will encounter. Big companies are very risk-averse, which is why they can always control the cost of producing products within a certain range like a well-oiled machine. For this reason, large companies are more willing to "outsource" innovation work by acquiring startups, even if this method sometimes has little effect. All successful businesses, especially those of a certain size, tend to minimize risk and trial and error costs. However, as Brené Brown points out: “You can choose to move forward, or you can choose to stay in your comfort zone, but you can’t have both.”

For companies, "brave pioneering" has long become a cliché, and leaders protest against it too much. But in the field of artificial intelligence, managers need to truly "unify knowledge with action" and embrace technology rather than reduce risks.

Take Adobe as an example. The Photoshop developed by it has long occupied the largest share of the photography design market. When generative artificial intelligence appears, Adobe can adopt a steady and steady strategy, first apply it on a small scale, and then wait and see what happens. Just like Kodak did when digital photography came along, or Motorola did when smartphones came along. However, Adobe chose a strategy that ran counter to these predecessors in the technology world, and the company quickly integrated generative artificial intelligence deeply into the software Photoshop. In this way, even the most ordinary user can create a variety of previousUnable to make videos, Adobe could have viewed artificial intelligence as a threat or interference. And before AI technology was invented, the company continued to optimize Photoshop. However, in the face of new technologies, Adobe management still has the courage to actively invest in AI to further empower products.

On a technical level, chip manufacturer Nvidia was once a household name for providing the best artificial intelligence semiconductor chips. To outsiders, the company might just be lucky enough to have the right technology at the right time. But Nvidia's current achievements are no accident. In the past decade, the company has actively acquired innovative companies to develop professional capabilities in the field of AI. Through acquisitions and independent research and development, NVIDIA has expanded a large number of businesses including the development of customized chips and software. We expect Nvidia to continue its aggressive innovation strategy, which will not only provide the company with higher value products but also make better use of artificial intelligence rather than simply cutting costs.

Not every bold innovation will succeed. But in order to overcome corporate management's deep-seated aversion to risk, a can-do mentality is essential.

Entrepreneurial mentality

To succeed in the field of AI, maintaining an entrepreneurial mentality is as important as bold innovation. Regardless of the size of the company or the length of its operation, This is true. Startups are good at scouring the market for opportunities and responding quickly to customers' current needs. While large companies have the resources to spot these opportunities, they are often slow to respond to customer needs due to obstacles and a lack of courage, while start-ups can enter the market faster under the same circumstances. Open AI defeated Google with ChatGPT. It has two seemingly incompatible advantages. It has an entrepreneurial mentality and is not hampered by indecision like Google. At the same time, it has Microsoft and other investors to provide it with sufficient capital. resource.

The so-called entrepreneurial mentality not only refers to the courage and flexibility of a company, but also includes a strong desire to achieve great things. This is like a heroic journey to face huge challenges. The mission of a startup should be to create something extraordinary, not to mass-produce a predictable, high-quality product, even though that's perfectly possible. Therefore, startups will actively look for opportunities and adopt flexible cooperation methods. In order to achieve what they need to achieve, they abandon existing organizational structures and biases, no matter how long-established and respected these stereotypes may be.

Other Drivers

Companies cannot adopt all of the above drivers overnight, but what they can do is start moving in that direction Work hard and seriously explore new possibilities. For those looking to find career purpose and achieve something, most of the drivers above also apply on a personal level. They can try boldly and maintain an entrepreneurial mindset in the workplace toand other necessary conditions. Just like companies, employees can actively participate in the AI ​​industry by acquiring the necessary skills and experience, which not only protects their careers, but also empowers employees at a higher level.

Most of the energy in the business operation process is on how to produce reliable products at lower costs. In order to prevent large-scale unemployment, what we need now is for more companies to break this convention and accelerate the development of AI. The biggest danger now is that most companies will pursue stability and only make a single investment to meet short-term benefits.

Keywords: AI

Behnam Tabrizi Babak Pahlavan | Text Bei Hnam Tabrizi has taught "Leading Organizational Transformation" at Stanford University's Department of Management Science and Engineering for more than 25 years. As an expert in organizational and leadership transformation, he has helped thousands of CEOs and leaders plan, mobilize and implement new transformation initiatives. He has written ten books, most recently Offensive: The Leader’s Handbook of Sustainable Innovation (IdeaPress, August 2023). Babak Palawan has been working in artificial intelligence since 2008. He founded the artificial intelligence startup CleverSense, which was acquired by Google in 2011. He has since worked at Google for 11 years as senior director of product management. . Chang Minxiao | Editor