When your organization finally decides to implement AI, the real work has only just begun. Having led AI implementations at a mid-sized distribution company, I’ve seen firsthand how the gap between commitment and successful execution can make or break your investment.  

I had a recent discussion with Justin Johnson at GoMotivate and it reminded me of the importance of what happens after the Yes. 

The First 30 Days: Setting the Foundation 

The initial excitement of signing that AI contract quickly gives way to the reality of implementation. I thought the hard part was choosing the vendor. Turns out, that was just the beginning. 

Your immediate priority should be: 

Create Your Cross-Functional Implementation Team 

Don’t make the mistake of delegating AI implementation solely to IT. In successful implementations, the team composition typically includes: 

• IT leadership to manage technical integration 
• Operations managers who understand current workflows 
• Training specialists to develop new protocols 
• Service team representatives who understand customer touch points 
• Power users from different departments 

As I discovered when implementing an AI-powered reorder recommendation system back in 2019, involving the people who will use the system daily in its design phase pays enormous dividends later. We worked directly alongside the vendor on the customer service floor to understand how AI would impact team members and how they could use it successfully. This collaborative approach helped us build a solution that delivered measurable results.​​​​​​​​​​​​​​​ 

Leadership in the Trenches 

The most successful implementations share one common characteristic: leaders who deeply understand the AI they’ve deployed. 

Executive engagement is non-negotiable. 

I believe strongly in a leader getting down in the trenches and understanding the AI and how it operates, and how people interact with it. You cannot continue to coach leaders if you’re not confident in what’s expected of AI in the benefits that it will deliver your organization.  

This means participating in demonstrations and training, personally using the AI tools, understanding limitations and capabilities, and being able to clearly articulate how AI supports your company’s strategy.​​​​​​​​​​​​​​​​ Without this engagement, employees quickly sense that AI is just another corporate initiative that will pass with time. 

The Cultural Transition: Managing the Human Element 

The human component requires just as much attention as the technology itself. 

Design Your AI Interaction Playbook 

The most successful implementations have an AI Interaction Playbook” with four critical elements that transform AI capabilities into actionable business processes.

Content: What People Need to Say and Do

Specify exactly what information your team must communicate when using AI. This includes specific language for presenting recommendations, key questions to ask customers and essential information they need to be successful. Well-defined content helps even hesitant team members engage confidently with AI tools.

Sequence: The Step-by-Step Process

Outline the precise order of actions from start to finish. Create a consistent workflow that includes decision points, verification steps and alternative paths based on different scenarios. A clear sequence ensures everyone follows the same process, making results more predictable and training more effective.

Timing: When to Take Each Action

Define precisely when interactions should occur – immediately after specific events, within established timeframes, or at different moments in the customer journey. Proper timing can dramatically impact acceptance rates and customer satisfaction.

Expected Outcome: The Definition of Success

Establish clear metrics that define successful execution. When team members understand what good looks like, they can self-assess and continuously improve.

Without this framework, your team will struggle to consistently leverage AI’s capabilities. This is particularly important for customer service representatives transitioning from order-taking to more consultative roles.

Prepare for Resistance: Addressing Team Skepticism in 2025 

Even in 2025, you’ll face skepticism from your team. Common concerns include: 

Fear of job displacement: This challenge intensifies when implementing multiple AI solutions. I experienced this firsthand with just an order and product recommendation engine. Employees naturally worry about their future roles. 

Reluctance to change familiar workflows: This resistance is fundamentally about fear, not process. In my experience, the pushback came from employees saying, “I’ve done it this way for years, why change now?” The issue was confidence, not capability. Once we addressed their concerns, even our most resistant employees embraced the new approach. 

Questions about accuracy and reliability: Many distributors underestimate implementation complexity. As one electrical distributor discovered, order matching presents significant challenges.  

Mistrust of AI recommendations: Despite clear performance improvements in our implementation, we conducted blind tests to prove the AI’s effectiveness to skeptics. This resistance doesn’t just come from frontline staff. Mid-level managers often show the strongest resistance, particularly those who’ve built their careers on intuition-based decision making.​​​​​​​​​​​​​​​​ 

From Cost Savings to Revenue Generation 

The initial ROI calculations for AI typically focus on cost reduction – particularly in labor hours saved. However, the true value emerges when you redirect those savings toward revenue generation. 

Redeploying Your Team 

Distributors are finding their AI ROI by redeploying staff to higher-value activities including proactive customer outreach, enhanced product expertise development, more sophisticated cross-selling and upselling, and account management for previously underserved customers.​​​​​​​​​​​​​​​​ 

Transitioning from Order-Takers to Business Developers 

One of the most significant shifts is repositioning your customer service representatives. It’s not an order-entry job anymore. It can’t be. This transformation requires developing comprehensive new scripts and guidance. When a customer service representative shifts from simply processing orders to identifying growth opportunities, they need clear direction and support tools. You can’t just give this to CSRs and say: “Make these phone calls, and do these tasks.”  

It won’t work. 

The most successful distributors create multi-tiered guidance systems: 

• Quick-reference cards for common scenarios 
• Detailed playbooks for complex situations 
• Regular role-playing sessions with feedback 
• Recording and reviewing successful interactions as learning tools 

Remember that your CSRs didn’t sign up to be salespeople. They need confidence-building support to successfully make this transition. When properly equipped, however, they often become your most effective revenue generator because they combine product knowledge with regular customer contact.​​​​​​​​​​​​​​​​ 

The 90-Day Roadmap to Success 

Based on my experience, here’s a pragmatic 90-day implementation framework: 

Days 1-30: Foundation Building 

• Assemble your cross-functional team 
• Complete initial data assessment 
• Begin infrastructure preparation 
• Establish baseline metrics for future comparison 

Days 31-60: Initial Integration 

• Start technical implementation with limited scope 
• Develop your AI interaction playbook 
• Begin training program development 
• Identify early adopters and champions 

Days 61-90: Expansion and Refinement 

• Expand implementation to additional departments 
• Collect and analyze early results 
• Refine training and playbooks based on feedback 
• Celebrate and publicize early wins 

The Long View: Competitive Sustainability 

The distributors seeing the greatest AI success are those who view it not as a project but as a fundamental business transformation. Their approach includes continuous improvement cycles with regular reviews of AI performance and refinement. They develop evolving training programs that provide ongoing skill development for both new and experienced users.  

These companies establish clear accountability with defined ownership for AI outcomes at every level of the organization.​​​​​​​​​​​​​​​​ At Distribution Strategy Group, our research indicates that early adopters in distribution can expect efficiency gains of 30% to 40% by 2030. 

The Path Forward 

Implementing AI in your distribution business isn’t just about installing new software. It’s about reimagining how work gets done. The organizations that thrive will be those that master not just the technology but the human elements of this transformation. 

Remember that technology alone doesn’t create competitive advantage. It’s how you integrate it into your business processes and culture that makes the difference. By following the framework outlined above, you can navigate the complex post-commitment phase of AI implementation and position your organization for sustainable success. 

Want to learn more about effective AI implementation in distribution? Join us at the Applied AI for Distributors conference in Chicago, June 24-26, 2025.