Avoid Unrealistic AI Expectations
The initial AI hype is wearing off, and a growing backlash is setting in. Now, your plans and investments need to reflect what’s actually happening.
As recently reported in Inc., a Boston Consulting Group (BCG) study found significant gaps between AI expectations and reality.
Leadership expectations for AI do not match the messy reality of rolling the technology out to frontline workers and managers. And while the study focused on larger enterprises, these challenges apply directly to small and midsize organizations.
The AI Gap
Gaps between expectations and reality manifest in three key areas:
1Expected ROI
Many businesses are investing heavily in AI but aren’t seeing the promised returns yet. The BCG study shows only 20% of leaders feel their adoption rate is correct. The other 80% feel they’re moving too slowly or inconsistently.
The study attributes this to the AI hype cycle and a limited understanding of AI among non-technical business leaders. Fear of missing out (FOMO) is driving urgency rather than clear strategic goals.
2Trust
Business leaders trust AI more than frontline workers and managers. While leadership sees pure potential, the employees using the tools are highly skeptical. Many worry that working with AI tools is just training their eventual replacements.
3Training
Executives and upper management want quick AI adoption, but their staff commonly struggle with when and how to use these new tools. The study notes that AI leadership is often unclear, leading to conflicting expectations and priorities. Your team needs hands-on training to integrate AI into their workflows, along with an easy way to provide feedback.
Steps You Should Take
Given the gaps and their potential to slow or halt AI efforts, we recommend you take the following five steps for your AI projects and efforts.
1)Create an AI
Appropriate Use Policy
A robust AI Appropriate Use Policy creates a foundation for why, when, and how your team uses AI. It also sets solid expectations for data security, privacy, and governance.
2)Define and Share your
AI Goals and Strategy
Communication builds trust. When you share your AI goals and strategies, your team will understand how AI supports their daily work. This sets healthy boundaries and removes the fear of the unknown.
3)Clearly Establish AI
Leadership and Governance
Consistent direction, priorities, and expectations reduce friction while creating predictable results. Top-down leadership provides a uniform approach that demonstrates your commitment to responsible AI usage.
4)Identify and Focus on
Specific Use Cases
AI for the sake of AI will fail. Look closely at your daily workflows, especially repetitive or data-intensive tasks, and define clear use cases. Pinpoint your desired outcomes so that you can easily review and refine the rollout.
5)Setup and Follow a
Change Management Process
Don’t just let AI happen. Instead, make it happen. Treat your transition to AI like any other mission-critical project. Regular updates, feedback loops, and clear timelines will help you stay ahead of issues. Your team will be able to spot and fix problems before they stall your progress.
Help is Here
We are here to help you succeed. If you want to learn more, check out our AI Landing Zone, send us a message, or book a meeting with our Cloud Advisors.
About the Author
Bill is a Senior Cloud Advisor responsible for helping small and midsize organizations with productive, security, and secure managed cloud services. Bill works with executives, leaders, and team members to understand workflows, identify strategic goals and tactical requirements, and design solutions and implementation phases. Having helped hundreds of organizations successfully adopt cloud solutions, his expertise and working style ensure a comfortable experience and effective change management.
