By Pragya Malhotra Gupta, Chief Technology and Product Officer, isolved
AI is advancing fast and for many workers, so is the fear of being replaced.
In fact, 37% of employees worry AI will take their jobs, a concern that’s especially acute in technical roles tied to repetitive tasks like entry-level coding, data analysis and IT support. These functions align closely with AI’s current strengths, making them feel particularly vulnerable as automation gains traction.
But replacement is only part of the story. As automation takes over routine tasks, many roles are evolving, not disappearing. Developers, for example, may spend less time writing code and more time refining AI-generated outputs. Analysts, on the other hand, may shift from producing reports to interpreting results and driving strategic decisions. In many cases, AI is less a job killer and more a job shaper, pushing roles toward higher-value, human-led work.
The challenge is how organizations respond to this shift. Many are calling for greater “AI fluency” across the workforce, but their actions don’t always match their ambitions. Too often, leaders look to external hiring instead of developing employees already inside the organization.
The result is a growing disconnect. Employees are expected to adapt overnight while organizations miss the chance to strengthen culture, retain knowledge and build trust by investing in internal growth. Closing this gap means giving employees opportunities to build AI skills in the flow of daily work and adopting the technology in ways that support long-term performance.
Four strategies for developing AI-ready teams
AI fluency develops through consistent practice, not one-time training. Employees build confidence when they can use AI regularly, connect it to their responsibilities and apply it in meaningful ways. Here are four ways to get started:
1. Make AI learning part of daily work
You don’t need a major initiative to help your team get comfortable with AI. Start small by weaving it into the tasks people already do.
Encourage experimentation with tools that can suggest code, automate repetitive testing or clean up datasets. These low-risk applications show employees how AI can save time and make their work easier.
You can also set the stage for peer-to-peer learning. Ask experienced team members to lead short workshops or demos that show practical use cases. Even brief “show and tell” sessions create momentum and encourage people to share what does and doesn’t work in real-world contexts.
2. Balance external hiring with reskilling
Hiring talent with AI expertise may be necessary in certain cases, but it shouldn’t come at the expense of developing your existing team.
Reskilling the people you already have in place allows you to retain institutional knowledge while preparing employees for evolving responsibilities. This helps ensure continuity, reduces onboarding time and demonstrates that you value employee growth.
Create rotational opportunities where team members spend time working on AI-focused projects outside their normal scope. Pairing junior staff with senior mentors on these projects accelerates skill development and builds stronger collaboration across levels.
3. Build trust through responsible adoption
Employees will only embrace AI if they believe it’s being implemented with care. Set clear expectations for how the technology will be used, what data it will access and where human oversight is required. To create trust, you need to establish strong privacy practices and review AI outputs for fairness and accuracy.
Communication is equally important. When you’re open about what tools are approved, how they’re monitored and what safeguards are in place, your team feels more confident about putting AI into practice.
4. Position technical teams as leaders in adoption
Your team has both the technical expertise and the organizational insight to guide how AI is used. Involve them in pilot projects, decision-making and governance to ensure that adoption is grounded in real workflows instead of top-down mandates.
This approach also elevates the role of technical teams across the business. Instead of being seen only as troubleshooters, they become strategic partners who identify opportunities, drive efficiencies and shape how AI delivers value. When employees see themselves in that role, they’re more motivated to keep building their skills.
Successful AI adoption starts with people
AI adoption will only succeed if employees are given the tools and opportunities to grow with it.
By encouraging continuous learning, valuing internal development alongside external hiring and introducing AI with transparency and care, you create an environment where employees thrive alongside the technology.
Your investment in employees strengthens trust, supports culture and lays the groundwork for lasting innovation. By putting people at the center of AI adoption, you can ensure your organization is ready for the opportunities ahead.