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\n\t\tOpinions expressed by Entrepreneur contributors are their own.\t<\/p>\n
Most executives believe they\u2019ve done their part on artificial intelligence<\/a>. They\u2019ve approved the tools, announced the initiative and moved on. But the adoption numbers tell a different story.<\/p>\n According to Slingshot<\/a>\u2018s Digital Work Trends Report<\/a>, 86% of C-suite executives believe AI usage is required in their company operations. Yet fewer than half (49%) of middle managers are reinforcing that expectation with their teams. This gap between what leaders announce and what employees actually do isn\u2019t a technology problem. It\u2019s a leadership one.<\/p>\n I\u2019ve spent more than 35 years leading Infragistics<\/a>, and one lesson which has remained true through every major technology shift is that the success of any new initiative depends less on the technology itself and more\u00a0 on how leaders introduce it. The organizations that see lasting change are the ones whose leaders create an environment where people can adopt new tools with confidence.<\/p>\n AI is no different. If leaders want employees to embrace it, they need to do more than roll out a platform or issue a mandate. They need to create a safe space where people feel comfortable learning, experimenting and building new habits. Here are three ways leaders can do so.\u00a0<\/p>\n Real AI adoption<\/a> requires employees to experiment with the tools. But people won\u2019t take those risks unless they feel safe doing so.<\/p>\n That\u2019s where coaching becomes far more effective than command-and-control leadership. Rather than simply telling employees to use AI, coaching-oriented leaders<\/a> work alongside their teams and ask what\u2019s working, what isn\u2019t and where people are getting stuck.\u00a0<\/p>\n Anyone who has spent time with an AI tool knows that getting genuinely useful results takes practice. The first prompt rarely gives you what you need. Over time, though, you learn to ask more specific questions, provide the right context and test different approaches until the output actually fits your workflow.\u00a0<\/p>\n That kind of learning is personal and iterative, and it looks different for every role. A marketer figuring out how to use AI to track KPIs is going to take a completely different path than a salesperson using it for outreach. Employees need room to go through that process, and that only happens when leaders create an environment where figuring it out is part of that job and not a sign that someone isn\u2019t ready.<\/p>\n One of the fastest ways to encourage AI adoption is for leaders to use it themselves.\u00a0<\/p>\n Employees pay far more attention to what leaders do<\/em><\/a> than what they say<\/em>. So, when leaders openly incorporate AI into meetings, planning sessions, decision-making or content creation \u2014 and are honest about both the successes and limitations \u2014 they normalize learning. And that transparency gives employees permission to experiment without feeling like they need to be experts from day one.<\/p>\n One simple habit leaders can implement is to open team check-ins by sharing how they used AI that week, what they tried, what worked and what didn\u2019t, then inviting employees to do the same. Conversations like those are an opportunity to exchange ideas, uncover successful use cases, encourage collaboration and help employees learn from one another instead of experimenting in isolation.<\/p>\n How leaders talk about AI matters just as much as how they implement it<\/a>. When AI is framed as another mandatory technology rollout, employees often see it as another box to check or, worse, as a threat to their jobs.\u00a0<\/p>\n Slingshot\u2019s Digital Work Trends report found that nearly 1 in 5 Gen Z employees (19%) and 17% of millennials worry AI could eventually replace them. A company mandate<\/a> does nothing to address that fear. But when leaders position AI as a way to remove repetitive work, improve decision-making and give employees more time for higher-value thinking, that conversation starts to look very different.<\/p>\n Employees don\u2019t want to hear that AI will replace what makes them valuable. They want to understand how it helps them become even better at the work they already do well. That means being clear about where AI adds value and where human judgment remains essential. AI can analyze data, summarize information and automate repetitive processes, but people still provide strategy, creativity, relationship-building and accountability. When those roles are clearly defined, AI becomes less intimidating and much more useful.<\/p>\n Ultimately, the organizations making the most progress with AI are the ones whose leaders make it safe to learn, model the behaviors they expect from others and consistently reinforce that AI is an investment in their people, not a replacement for them.<\/p>\n<\/p><\/div>\n Most executives believe they\u2019ve done their part on artificial intelligence<\/a>. They\u2019ve approved the tools, announced the initiative and moved on. But the adoption numbers tell a different story.<\/p>\n According to Slingshot<\/a>\u2018s Digital Work Trends Report<\/a>, 86% of C-suite executives believe AI usage is required in their company operations. Yet fewer than half (49%) of middle managers are reinforcing that expectation with their teams. This gap between what leaders announce and what employees actually do isn\u2019t a technology problem. It\u2019s a leadership one.<\/p>\n I\u2019ve spent more than 35 years leading Infragistics<\/a>, and one lesson which has remained true through every major technology shift is that the success of any new initiative depends less on the technology itself and more\u00a0 on how leaders introduce it. The organizations that see lasting change are the ones whose leaders create an environment where people can adopt new tools with confidence.<\/p>\n<\/p><\/div>\n1. Coaching creates the confidence to experiment<\/h2>\n
2. Model the behavior you want to see<\/h2>\n
3. Position AI as growth, not compliance<\/h2>\n
Key Takeaways<\/h2>\n
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