Over the last year or two, we have seen record layoffs at major tech firms. Often, they have been attributed to AI investments. Digging a little deeper, not all AI-related reductions in force (RIF) are being driven by the same motivation. If we divide the world into three buckets: AI-Suppliers, Vendors, and Customers, we can begin to peel back the drivers. Of course, we have to recognize that in a supply chain, vendors are also someone’s customer, and customers are someone’s vendor, but for simplicity we can divide behaviors into these three camps.
The level of investment going into AI infrastructure is historic. AI-Suppliers are building massive data centers, and many more are planned. Other companies are investing billions to create AI platforms and models, and it feels like we are in an epic arms race to make ever ‘smarter’ and more capable platforms. Several of the traditional tech giants have been undergoing significant business shifts resulting in mass layoffs as they pivot away from investing in their traditional businesses and toward investing in new AI frontiers. Think Meta, Oracle, Microsoft, etc. These staff reductions make the news, and contribute to the perception that AI is crushing the job market.
Beyond the AI suppliers, however, it seems as though every vendor and customer alike is using AI in some manner to augment or operate their business or supplement the productivity of their personnel. The cumulative spend across all industries is incalculable.
Vendors are all under pressure to incorporate AI-based features into their tech products. As discussed in earlier posts, this is introducing new costs into their products and putting pressure on gross margins in the form of added cost of goods sold. With reduced gross margins, there is less money available to fund operations, leading to the need to drive efficiency in operating costs. For most software businesses, the largest cost line item is personnel, so this is a natural place to look for savings. The good news is that AI has the potential to help employees become more efficient. The bad news is that as efficiency increases, businesses need fewer employees. However, the efficiency gains are not free, so as companies embrace AI-based tools to help their staff become more efficient, they also take on the costs of the new tools. The balancing act is to manage total spend by netting the cost of new tools against the efficiency gains and the savings driven by reducing staff. From the vendor perspective, one area where AI is specifically driving efficiency is the engineering department. Companies that ‘partner’ with AI to write and test code are seeing significant efficiency gains in the pace of product delivery. A skilled engineer can be three or four times more efficient by partnering with AI tools, while the added AI cost is closer to the human cost of just one new engineer. Three or four fold productivity gain for les than two times the cost. Fewer engineering jobs, but greater productivity, and on a blended basis, the AI cost plus HR cost is lower.
On the customer side of the equation, AI is permeating every aspect of running a business. The new applications the vendors are delivering are making their customers’ team members more efficient. The efficiency comes at a cost, but so far the cost impact is not that great because the inertia of existing license pricing is limiting how fast vendors are able to pass along their new costs to their customers. As I argued in an earlier post, this equation is likely to change as vendors move toward consumption pricing and customers are forced to pay for their AI benefits.
Today, we see headcount reductions in the customer market primarily in entry-level or lower-paid roles. AI-driven platforms can efficiently replace humans performing elements of the sales development (SDR) role, marketing communications roles, and customer support roles. AI agents can efficiently do data gathering and analysis, and are becoming adept at producing reports and presentations that used to require human action. This is where the phrase “AI Ate My Job” is most apt. Unfortunately, this imbalance is creating a huge problem for new grads and those without experience entering the job market. With the elimination of entry level jobs, there is little opportunity to get on the job training and experience. Without experience, you cannot find a job to get experience.
Educational institutions are slowly adapting to this reality by integrating AI into the curriculum. We used to talk about generations that were ‘born digital,’ and comfortable learning how to operate technology. Now we are seeing a generation that is being ‘born AI savvy,’ and excel in the application of AI. These are the skills that traditional organizations need to hire in order to effectively embrace AI in their businesses, and this is where educational institutions need to adapt. We are also starting to see an ‘old dog, new tricks’ problem emerge as experienced employees who are used to doing things the ‘old’ way find it difficult to transition to the new way things are being done.
It may be true that AI ate some jobs, but it is also creating new opportunities. We are in a transitional period that will be very disruptive for many people. The pace of change is dizzying, but as has been the case with all technology transitions, things will eventually settle into a new normal. What feels different is the pace of change being introduced by the breathtaking advances in AI. The pace of technology advancement is accelerating, and the workforce will have to keep up or be left behind. AI may eat some jobs and close some doors, but in time it will also open new ones.