AI mania continues to ramp up at an exhilarating pace, and the pressure on executives to adopt it is only intensifying. But in the rush to deploy, don't overlook an important step: preparing your workforce.
IT issues can certainly plague corporate tech overhauls, but many actually fail because of an emotional response: internal resistance to change. Leaders often underestimate the level of employee pushback to new applications or workflows. That's especially true if the proposed change adds additional steps for the end user. Or if in the excitement, they move too fast without clear direction.
That’s the case with AI more than any other major IT shifts we’ve experienced in the past 20 years. Given all the fear-mongering, employees are justifiably nervous about whether they’ll see themselves replaced by a faceless, nameless robot. This is a very typical response to change. And how successful your AI initiatives are depends on how well you can address those concerns.
Naturally, installing a new data platform or building the right integration pipelines is important to the overall AI implementation. But companies must start to reflect the AI shift in every facet of their operations. They must refresh performance metrics, compensation plans, cultural tenets, leadership styles, and more.
Below are a few steps to turn even skeptical employees into internal AI champions.
Be Realistic
CEOs and other leaders can’t be silent about AI.
The ChatGPT phenomenon made AI a household topic and the buzz has only grown since then. Even if a company doesn’t take the time to set up formal policies, employees are inevitably going to use tools like ChatGPT. Truth be told - they probably already are. There’s simply no way to avoid the eventual creep of AI into operations. Instead of fighting it, businesses should figure out how to embrace it.
Proper data privacy and governance controls are a starting point. But after establishing the right guardrails, companies should let employees experiment. These real-world interactions with the AI will help showcase the tech’s potential and highlight its shortcomings. Soon, employees will realize how vital they still are to operations.
Throughout the experimentation phase, CEOs and other leaders should be in constant communication so employees are clear on how these tools align with broader organizational goals.
That being said, top-down mandates only go so far. Executives must also communicate why the investments are being made. Outlining the long-term strategy around AI shows it's about more than thoughtful experimentation. Instead, it sends a strong message that leaders expect employees to use and benefit from the tech.
But that message shouldn’t be one-size-fits-all. Managers should spend time tailoring the message to their teams. This will help individual contributors know exactly what's expected of them.
To drive home expectations, businesses should start to reflect the new focus on AI in performance objectives. For example, that could be a goal to automate 25% of an employee’s existing workflows. By linking annual performance targets to AI usage, workers can craft their own adoption journey.
Know Your Readiness
Eventually, employees will learn how to work alongside these new AI systems. Once the adoption phase is near completion, it’s time for the business to think about more sophisticated use cases. This is a critical step – and one that many organizations are still stuck on.
You hear it all the time: AI requires the right data to be successful. But it also requires a deep understanding of how the business operates and even deeper insight into the pain points that will lead to seamless workflows that have a real impact on productivity. Then, leaders can start to think about the data streams required to make that possible.
This is where employee feedback becomes critical. Not every business is ready to jump headfirst into AI deep end right away. In fact, broader access to basic analytic tools might be enough to satisfy most employees. A bottoms-up feedback loop helps identify whether there’s a need for a more complex system. It can also assist in pinpointing the areas where AI can make the most impact.
For example, executives might be unaware of the large number of hours employees spend on document analysis. And often, they are desperate for automation to help. They want to spend less time on manual data entry and more time in front of their customers. In this case, Intelligent Document Processing (IDP) is the answer. It gives employees instant access to critical knowledge that improves their productivity and enhances their decision-making.
The bottom line? Businesses can start to reap the benefits of AI while end users experience firsthand how it can make their lives easier.
Choosing projects that address common pain points will reduce the potential for pushback and get workers energized about AI's potential. But companies should also encourage employees to explore AI for themselves. Introducing a space for learning and exploring underscores just how important the tech is.
Think Big, Start Small, and Scale Strategically.
There’s no one formula for success in AI. The “secret” is simple: just get started. Instead of perfection, aim for gradual improvement. Don’t try to transform overnight. AI is a journey, not a destination. It should be broken down into manageable, incremental steps.
Those steps must include preparing the workforce for what’s ahead. Leaders should be encouraging teams to approach pilot projects with a fault-tolerant mindset. They should emphasize the importance of learning quickly, iterating based on feedback, and embracing failures as opportunities for growth.
When team members feel empowered to take calculated risks, that’s when real innovation happens. And when those breakthroughs occur, celebrate them! Recognize the achievements and learnings from pilot projects, no matter how small. Highlight how AI is positively impacting the team’s work, as well as the organization as a whole.
Companies that use AI success to identify and empower champions will become AI leaders in their industry.
