INTRODUCTION
In the first article of a multi-part series on AI adoption in the workplace, we explained the steps businesses need to take to assess and plan their AI needs. In the second article, we explained how to plan and execute AI pilot programs.
Now that you’ve completed your pilot programs, you are ready to integrate AI into your existing processes and workflows.
MAKE YOUR PILOT PROGRAMS PERMANENT
In your pilot programs, you chose the processes and AI tools to test together. For the programs that successfully met their metrics, it’s time to scale the implementation across your organization.
Treat this AI implementation as a strategic transformation rather than just a tech deployment so that it is embraced throughout the organization. Start by solidifying a strong governance structure and ensuring key stakeholders are aligned. It’s also important to address any change management issues early by engaging teams, clarifying how AI will support (not replace) their work.
Next, prioritize departments or functions where AI can deliver the most immediate value, using an incremental rollout strategy. Each phase will include feedback loops, performance monitoring and opportunities to adjust based on real-world results. Collaborate among IT, operations, leadership and your cross-functional team to maintain momentum and consistency.
Finally, be prepared for the unexpected by creating fallback procedures for system outages or AI tool failures.
UPDATE YOUR PROCEDURES TO REFLECT NEW AI WORKFLOWS
As AI tools shift how tasks are performed, your documentation should evolve to match. Begin by revising your existing SOPs to include AI-enabled steps, automation triggers or decision points introduced by new tools.
Visual aids can significantly improve comprehension, so consider including screenshots, video walkthroughs and side-by-side comparisons that show “before” and “after” workflows. Document any configuration settings, API keys or customizations made during the AI implementation, and maintain a clear change log to track what was modified, when and why.
Finally, treat documentation as a living resource—encourage user feedback and make regular updates to reflect real-world usage and insights from your team.
CREATE AI TRAINING PROGRAMS FOR STAFF
You will need to provide your employees with training programs to equip them with the skills needed to work alongside AI technologies. Start by developing role-specific training materials that address how AI tools impact day-to-day responsibilities. This targeted approach helps employees see the relevance of the technology and builds confidence in using it effectively.
People learn in different ways, so offer a variety of learning formats—including video tutorials, written documentation, and hands-on workshops—to accommodate diverse learning styles. Foster a culture of collaboration by creating user communities where staff can ask questions, share best practices, and exchange insights.
In addition, identify and train “super-users”—individuals who excel at adopting new tools and can serve as in-house champions. These peer leaders become valuable resources for ongoing support, helping others troubleshoot issues and deepen their understanding of AI in real-world applications.
ESTABLISH A FEEDBACK MECHANISM
You need to set up a way to gather feedback on your newly implemented AI processes to make sure they remain effective and aligned with user needs. Start by setting up formal channels where employees can report issues, suggest improvements or ask questions. These channels can include a dedicated email address, a feedback form on your intranet site or an internal ticketing system.
You also should schedule regular check-ins with key stakeholders to proactively gather insights on what’s working and what needs adjustment. Use periodic surveys to measure user satisfaction, track adoption rates, and uncover hidden pain points.
To build trust and encourage continued engagement, establish a transparent process for evaluating and prioritizing suggested improvements. When users see that their feedback leads to meaningful changes, they’re more likely to stay engaged and invested in the success of your AI initiatives.