Last week, the Wall Street Journal ran a headline that should make every professional pause: “Use AI or Get Fired.”
The article showed that companies are taking different approaches to AI adoption. Some are letting go of employees who struggle to use AI at work. Julie Sweet, CEO of Accenture, told investors that employees for whom “reskilling, based on our experience, is not a viable path” will be shown the door.
Other companies are building AI learning environments before evaluating employees’ skills or interests. For example, McKinsey now gives priority to employees trained in AI for client projects, but only after offering the training. PwC’s Margaret Burke also commented on their investment in AI training: “It will absolutely pay off.”
Accenture now evaluates its 779,000 employees on their use of AI, and Walmart’s push for company-wide AI literacy shows the direction retail is taking. AI literacy has become a basic requirement in many companies. While the fresh produce industry may not feel the same urgency as tech companies, AI skills are becoming necessary to stay relevant as the market changes.
The difference between companies that require AI use without support and those that invest in training raises an important question: who is responsible for AI readiness? The answer is that both sides play a role. Success needs business leaders to provide structure and resources, and professionals to take initiative and build their skills.
The Company’s Role: More Than Just Tools
Another point in the WSJ article was: “Some companies are training people in how to use the tools—but leaving it up to them to figure out what to use them for.” This is like giving someone a commercial kitchen and expecting them to become a chef without any recipes, guidance, or support.
Companies that get AI adoption right understand their role in creating the right environment, such as:
Strategic Direction: The best results come when companies do more than just provide tools and hope for the best. They look for real problems to solve, such as automating reports, improving customer communication, or making compliance easier. Clear examples help turn big ideas into practical first steps.
Structured Learning Pathways: AI training shouldn’t be a one-time workshop or an optional lunch session. It should be part of ongoing professional development, moving from basic to advanced skills, just like companies did with computer literacy or food safety training.
Time and Space for Experimentation: Innovation doesn’t happen in spare moments. Teams need real time to explore, make mistakes, and find new ways to use AI. This isn’t just about adding more work; it’s about changing how we work.
Clear Performance Integration: Adding AI collaboration to performance reviews sends a clear message that this is now part of our work. It is not just another skill to check off, but part of how we measure success in our roles.
The Individual Imperative: Curiosity Isn’t Optional
Even the best company programs cannot overcome individual resistance or apathy. Recent Microsoft and LinkedIn research shows that while 75% of knowledge workers now use AI tools, most use them only for basic tasks like summarizing information or drafting first drafts. The gap between access to AI and actually using it well shows why individual initiative is as important as organizational support.
Individual professionals must own their development through:
Practical Application: Learning theory isn’t enough. Whether you’re automating reports, improving customer communication, or analyzing trends, look for real ways to use AI in your daily work, not just to finish training sessions.
Proactive Exploration: If you wait for permission or clear instructions, you will fall behind. People who succeed are those who try AI in their daily work, such as drafting emails or analyzing data, and learn by doing instead of waiting for a mandate.
Critical Thinking: AI results aren’t always right. The technology works best when we use our own judgment, industry experience, and some skepticism. It’s a tool that needs a skilled user, not a replacement for your expertise.
Continuous Learning: AI changes quickly, so what you knew yesterday is only the starting point. Keep updating your skills, follow new industry uses, and stay curious about what comes next. Treat it as ongoing learning, not a one-time course.
Finding the Balance: Shared Accountability
If you work in the fresh produce industry, this topic might seem distant from your daily challenges, but AI literacy isn’t just for tech experts or consultants. It’s for anyone who wants to stay competitive. Whether you are planning irrigation schedules, predicting prices, or preparing a business review, AI will become part of your job.
AI adoption works best when company support and personal effort come together. Companies can’t just require AI use without offering training, time, and clear examples. But employees also can’t wait for perfect programs before starting to learn on their own.
As we go through this change, remember that AI adoption isn’t all-or-nothing for companies or individuals. It doesn’t happen overnight. It’s about understanding, using AI regularly, and learning to work with the technology while keeping the human judgment and experience that make our industry special.
The AI Insider 