Sadly, Intel is facing more layoffs as it tries to improve its ability to invest in its future. It is interesting to note that this stems from problems created prior to Pat Gelsinger’s return to Intel during which BK fought Microsoft’s efforts to create an NPU and underinvested in processor and process technology. Once you fall behind, it’s really expensive to catch up, and companies of Intel’s size just can’t move that quickly. Both AMD and Qualcomm have benefited significantly from this Intel problem as the market pivots to AI.
Two downsides to layoffs are that they disrupt teams, and they can turn otherwise loyal employees into disgruntled employees who will act out. While we don’t know the cause of Intel’s recent quality problems, one of the potential causes is the prior layoffs. So avoiding them or doing them as well as possible should be a high priority.
This is potentially one of the areas where AI could make a huge difference, helping to avoid layoffs by surfacing alternatives or highlighting the ignored risks or turning layoffs into less of a dual-edged sword where the damage done by the layoff tends to make any problem the company is facing worse.
AI could make layoffs work far better for both employees and the company by forensically focusing on the interplay between employees and the firm and not only optimizing that relationship, but highlighting people who would be better off gone, both for the company and themselves, as initial targets of an action like this.
Layoffs
One of my degrees is in Manpower Management, which is a skill set that seeks to optimize the employee/employer relationship. Sadly, it was hampered both by a lack of diversity in well-trained candidates and an inability to deeply understand the relationships between the company and its employees.
While I was trained on strikes and layoffs, I got to experience the first ever IBM layoff that nearly broke the company. People critical to IBM’s operations were terminated which damaged IBM’s ability to not only recover financially from what was a near-death experience, but that shut down manufacturing lines for successful products because the company no longer had the skills to run them. In short, IBM’s layoff, which was supposed to save the company, almost killed it because the value of the employees being terminated wasn’t considered.
AI could fix this both by better identifying employees that are poor matches to the company or their job, suggesting changes that would better benefit both, as well as identifying those rare individuals who operate beyond their job requirements and keep the company running.
For instance, in old IBM, it was the secretaries and administrators that kept the company running. While these were low paying positions, the people in them often had a direct and significant impact on morale, customer and employee retention, and often worked as the critical lubricant that assured people got to where they needed to be, and things actually got done.
But they were also classes that were seen, since non-engineers held them, as non-critical even though they were incredibly critical.
This isn’t just a problem with layoffs. I’ve also seen company acquisitions destroyed because critical people weren’t locked down with retention packages or were arbitrarily let go as a result of the merger because their value wasn’t identified.
Properly trained AI could rank the value of the employees to the business and help craft a layoff or an acquisition employee retention policy so that there was far less harm to the employees and the company as a result of the layoff. If it was allowed to share information across companies, AI could also help find better positions for the terminated employees in other companies based on what the AI learned avoiding the disgruntled ex-employee problem (ex-employees can end up as buyers and be biased against the company they were kicked out of).
Wrapping Up:
While the Intel layoffs are unfortunate, they do provide an opportunity for the company and industry to develop better employee management tools that are AI-driven that could not only improve company operations and make layoffs less likely but improve both the layoff and acquisition process to minimize the damage and potentially provide a better benefit for both the firm and the employees at risk.
Intel is building an AI competency which will have both hardware and software elements, one of the focus areas should be operational so that Intel can use the technology to not only improve their operations, and particularly either avoid or do layoffs better, and then they can use this success as a foundation for their growth outside of Intel into AI solutions.
When it comes to layoffs, we tend to look at the negatives, but there is a way to learn from these events by using technology that could make overall employee management far more efficient and bad layoffs a thing of the past. Since Intel is in the AI business, there could be a silver lining to this dark layoff cloud.
