While the cadre of AI leaders squabble on many issues, they speak in unison of a potential job replacement crisis from the technology they are unleashing. So why are the three entities – corporations, employees, and government – not doing much to prevent the crisis. Rather than running a series of disconnected sprints, why not create a relay race. Here are some of the rules of a ‘relay race’.
Long-term Project Forecasting. Corporations think of their project in a longer trajectory like 3 to 10 years in advance, this allows for a better prediction in allocating resources – particularly workforce (jobs) and technology adoption.
There are significant risks and uncertainty in such long-term planning, with unpredictable inputs like market competition, user preferences, product acceptance, etc., but measure this with a chance / risk rate across a length of time before the project begins.
Use Case
With our Job Futures powered with Skills Label, we built a Project Label to accomplish all of this in a concise dashboard. The project label collects all these inputs, along with thresholds and time constraints. (See our list of Task Labels that are stacked into a Project Label.)
The Job Future is a “future job”, one contract, Job Label, and timeline – with a chance a job will be posted / listed in six months to two years. See the Job Futures website to get an idea of the concept
Limited Work Week. Corporations begin shortening work weeks back to the standard 40-hour work week. The staple 60-to-80-hour work weeks in some professions like AI, software development, investment banking, etc. is a foolish, unsustainable practice. Particularly with huge efficiency gains from AI and with a fundamental change in how corporations train and build their workforce (some consultants say it starts now, in 2026).
Use Case
Bolt, a San Francisco company with 550 full-time employees, decided to make their four-day workweek permanent for all employees, with the same pay and benefits. More than 90 percent of workers and managers approved for the program to continue.
This is good because it takes efficiency gains from AI and gives it back to the employees. (In my opinion) making it permanent –infuses work-life balance into the corporate culture canceling the “watch your back mentality, I can use AI to outpace and outperform my team”.
Employ Larger Workforce. Related to shortening the work week and the following point, Share Domain Knowledge and Skills, look to employ larger teams for longer contracts. A corporation faces a stack of projects (or work), rather than ask smaller teams to work more to complete the work, employ larger teams to do the same.
“20 years ago, IBM was America’s most valuable company with a payroll of nearly 400,000. Today, Nvidia is nearly 20 times as valuable and five times as profitable as IBM was back then but employs roughly a 10th as many people.” (WSJ)
While corporations like Microsoft and Meta employ more people 125,000 and 85,000 respectively, not nearly the same as IBM in the 80s, both aggressively lowered their headcount the last two years and the “writing is on the wall” for more. Both CEOs acknowledge roughly 30 percent of new software is created with AI.
Share Domain Knowledge and Skills. Corporations need to create a loyalty relationship with their employees (longer term employment contracts) to encourage employees to show a willingness to hand the baton, share their skills and domain knowledge among your team.
In sprints, the ones running the race are the top 5 percent of the workforce, many are commanding huge salaries. But the reality is the same work could be accomplished if the knowledge and skills were more freely spread across a larger team. If someone knows their employment at a company is stable for 5+ years and NDAs and IP theft are more strongly enforced, larger workforces might actually be encouraged.
In an article I wrote three years ago, Skills and AI Preparing The Future Workforce, I state some of my thoughts on skills and preparing for AI. The main graphic shows the idea of building a Collective Intelligence by connecting intelligent systems (AI), the skills of a person, with a network and team. The last one is critical. There are studies that the person with the highest IQ on a team, does not perform better than a team that works consistently, and cohesively together. A Collective Intelligence is predictable and is more strongly correlated with “the average social sensitivity of group members, the equality in distribution of conversational turn-taking” than “individual intelligence”.