Everyone is talking about AI investments. Organizations are buying licenses, rolling out copilots, and experimenting with new tools. But many leaders are asking the same question:
Why aren’t we seeing better results?
The answer often has less to do with the technology than the people using it. AI can change how work gets done, but technology alone won’t make that happen.
Technology Is the Easy Part
Most organizations know how to evaluate software. They compare features, review pricing, run pilot programs, and negotiate contracts. But turning that investment into measurable business results requires employees, managers, and leaders to rethink how work gets done.
Ask yourself these questions:
- Are employees using AI to create more value?
AI can draft documents, summarize meetings, and organize information in seconds. Pretty much everyone is doing that with their AI tools by now. In my work with both employees and business leaders, I’ve seen the biggest gains come from teams that use AI to rethink how they work, solve bigger business problems, and create new value for the business.
- Have managers evolved the way they lead?
AI changes a manager’s job just as much as an employee’s. As routine work takes less time, managers are presented with new opportunities to coach their teams, strengthen critical thinking, and raise the quality of their work.
- Do your roles still reflect the work being done?
As repetitive tasks become less time-consuming, employees have more capacity for higher-value work. Job descriptions, responsibilities, and performance expectations should evolve alongside those changes.
- Are you hiring for tomorrow’s needs?
AI literacy is becoming a baseline skill in many roles. Qualities such as curiosity, business judgment, communication, and adaptability are becoming stronger differentiators because they determine how effectively employees apply AI to solve business problems.
How Do You Turn AI Into a Workforce Advantage?
The organizations making the most progress with AI have one thing in common: they treat it as an ongoing business conversation rather than a one-time technology rollout.
Here are a few best practices I’ve seen make the biggest difference:
- Define where AI should create business value: Identify the business problems you’re trying to solve, whether that’s reducing turnaround times, improving customer service, increasing capacity, or refining decision-making. Well-defined business goals make it much easier to measure the success of your AI investment.
- Make workforce planning part of every AI discussion: Before expanding your technology investment, ask whether employees have the skills, managers have the support, and roles have evolved enough to maximize the AI tools you already have while supporting where you want the business to go with AI.
- Reward thoughtful experimentation: Give employees time to test ideas, compare approaches, and share what they’ve learned. Some experiments will uncover better ways of working, while others may reveal what isn’t worth pursuing. Both help your organization build practical knowledge that can be shared across the business.
- Review roles regularly: As AI changes how work gets done, responsibilities naturally evolve. Revisit job expectations, performance goals, and development plans so they continue to reflect where employees create the greatest value.
The more I talk with business leaders about AI, the less the conversation centers on the technology itself. It almost always comes back to people.
If these are conversations you’re having within your organization, we’d love to compare notes. At J2, we’re working with employers every day to think through how AI is changing hiring, leadership, and workforce development.