Now that we’ve entered the age of Artificial Intelligence, leaders across organizations are grappling with challenges the world hasn’t seen since the introduction of the personal computer and the Digital Revolution, and inevitably, there will be mistakes leaders make with AI.
For some leaders, the reluctance to embrace AI tools could put their companies behind the competition. Chatbots and AI marketing tools can enhance the customer experience in ways that many companies would struggle to provide through solely human workers.
On the other hand, organizations that rushed into AI adoption without considering how best to use it may find themselves bogging down productivity or preventing teams from streamlining old processes.
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4 Mistakes Leaders Make with AI
As with all technology, AI is a tool, not a panacea or a replacement. Used wisely, it can boost and enhance productivity; used poorly, and it may cause more harm than good.
Here are four mistakes leaders can make in the age of AI—and some ways to avoid them.
1. Pushing Adoption Without Training
For some organizations, adoption of Generative AI has resulted in what some call “workslop”—poorly produced materials generated almost entirely from artificial intelligence tools. This workslop requires team members, colleagues, and even bosses to spend hours each day deciphering, reworking, or entirely redoing the work.
Often, employees are simply doing as they were asked to do—use Gen AI to improve productivity by asking it to perform time-consuming or repetitive tasks. While the impulse is appropriate, without good training on the best ways to integrate AI tools or what tasks the tools can perform, workers are left guessing and experimenting. Such floundering can result in the workslop that others must clean up, thereby undoing any productivity gains.
Leaders who want to add AI to workflows and processes should spend time defining the details of that integration and giving employees clear instruction on how to best incorporate the tools. Leave room for experimentation and mistakes as well; adopting new technologies is never a straightforward path, and it will likely require some adjustments along the way.
2. Tacking on AI instead of Integrating it
In some places, organizations excited at the possibilities offered by Generative AI tools rapidly embraced these tools by tacking them onto existing processes rather than reworking the processes to include AI. The resulting work often fails to live up to the productivity promises of AI.
Historically, most technology requires some reworking of existing processes to use it to its best advantage. Consider, for a moment, the replacement of a horse and wagon for deliveries with an automobile. A horse and wagon driver has a process that involves caring for the horse, harnessing the horse to the wagon, and so on.
If the wagon driver simply harnessed the automobile to the back of the wagon, no productivity would be gained. In fact, productivity—and the horse—would suffer!
To best use the new AI tools, leaders should look carefully at which processes can be improved by it—and which ones can’t (at least, not yet). For areas where AI could improve the process or workflow, consider how to deconstruct or rework it before adding AI. What steps could be performed by AI? How would integrating AI at those steps affect the overall process?
3. Assuming AI Tools can Replace Employees
To paraphrase Aragorn at the Black Gates of Mordor, there may come a day when AI tools can replace human employees—but it is not this day.
This is not to say that there are no real productivity gains to be had from AI tools—there are! And it’s likely that AI tools will one day become as indispensable to the average worker as ballpoint pens, telephones, and computers are today.
Instead of looking at AI tools as replacements for employees, consider them as augmentation tools. Team members who can use AI tools well can boost their team’s productivity and create “superteams”—groups that employ both human and AI team members in their best capacities to produce the best work.
4. Ignoring Employee and Customer Perceptions
Finally, leaders and AI apologists still face an uphill battle when it comes to employee perceptions of AI. A Pew Research study showed that, while Americans do have some cautious optimism about certain applications of AI tools, they are “more concerned than excited” about the increased daily use of AI. Job questions aside, people worry that AI will further erode relationships, creative thinking, and problem-solving and decision-making abilities.
Leaders and AI champions who simply brush aside these perceptions or rush to adopt tools without listening to employee feedback will run into change resistance almost immediately. Change initiatives are doomed to fail when leaders forget that all organizational change—large or small—is ultimately personal.
When leaders and early adopters of AI step back, integrate AI tools with intentionality, and address concerns and perceptions with an open mind, they will be much more likely to realize gains from these powerful tools.
Leading through disruption isn’t easy, and mistakes are inevitable in the process. But leaders who approach AI integration with intentionality and humility are more likely to see successful AI transformation than leaders who either push adoption for the sake of adoption or ignore the technology altogether.
Want to learn more about leading successful change in your organization? Contact us to find out how the experts at Stewart Leadership can help you meet the moment and deliver business results and people results.
Self-check:
- What is one way I could better listen to employee or customer concerns about AI tools?
- What is one process that might benefit from integrating AI? Which piece of that process should we target for AI augmentation?
- Is there “AI workslop” in our organization right now? Why? How can we pare it back or eliminate it?
