Introduction: The Reality Behind AI Hype
Artificial Intelligence (AI) is often compared to revolutionary milestones like the steam engine or the internet. A recent McKinsey report underscores this transformative potential. However, while AI dominates headlines, its real-world implementation in the workplace remains uneven and fragmented.
The key question many companies face isn’t “Should we use AI?” but rather “How do we effectively use AI across diverse roles?”
Understanding the Gap: From Buzz to Practicality
Despite growing awareness, AI implementation is rarely linear. Different departments often operate at different speeds, and individual comfort with technology varies greatly. There’s frequently a disconnect between the promise of AI and its meaningful use in daily operations.
This is where companies like CarGurus are making deliberate strides. Through its initiative AI Forward, CarGurus is offering a blueprint for how cross-functional collaboration and structured experimentation can bridge this gap.
Meet AI Forward: A Collaborative AI Initiative
In October, CarGurus launched AI Forward, a dedicated working group consisting of 20 employees from departments such as product, legal, engineering, and sales. The group’s primary mission? To evaluate promising AI tools, create training opportunities, and foster a company-wide culture of AI exploration.
According to Sarah Rich, Senior Principal Data Scientist at CarGurus and lead coordinator of AI Forward:
“If everyone has to figure out AI on their own, we risk losing interest. We’re trying to offer cheat sheets and share what’s working.”
This reflects a core principle of successful AI integration: shared learning beats isolated discovery.
How AI Forward Supports Adoption Across Teams
Early Actions and Strategy
AI Forward began by hosting individual meetings with department heads to identify promising use cases. Some teams already had AI in mind, while others needed guidance. Rich’s team focused on:
Pinpointing relevant tools
Assessing tech readiness by department
Bridging the gap between need and capability
Departments such as engineering and legal were ideal starting points due to the availability of mature tools like Cursor, Windsurf, and large language models (LLMs) for reviewing contracts.
Departmental Support and Experimentation
Ongoing initiatives include:
Monthly group meetings and department-specific sessions
Office hours and jam sessions for real-time support
AI coding weeks to ensure hands-on practice
These touchpoints make it easier for employees to test and adopt tools without feeling overwhelmed.
“We make time for experimentation—it doesn’t just happen,” Rich emphasized. “But once people see results, AI often starts to sell itself.”
Addressing Resistance and Building Confidence
AI Forward recognizes that enthusiasm for AI varies. While some are eager to experiment, others prefer structure and assigned tasks. To accommodate this, the team developed tiered offerings:
Open-ended jam sessions for early adopters
Ticketed work challenges for those needing more structure
This inclusive approach ensures that even skeptics can find their comfort zone.
At Trenzest, we also emphasize phased adoption and customized onboarding paths when guiding clients in integrating AI tools into their operations. Tailored support is critical to engagement and long-term success.
Defining and Measuring Success with AI
Rather than focusing solely on time saved, CarGurus evaluates AI usage through several metrics:
Frequency of tool use
Types of tools adopted
Confidence in safe usage
Sentiment and perception
Interestingly, improved outcomes—not just faster work—are a key metric. For example, using AI to explore six creative solutions before choosing the best one is seen as valuable, even if it takes more time.
Three Phases of AI Adoption: What the Data Reveals
Rich’s team observed a predictable trajectory in employee sentiment:
Excitement: High hopes fueled by media buzz.
Disillusionment: Tools underdeliver or feel clunky.
Empowerment: Employees recognize AI as an augmenting force, not a replacement.
This final phase is where the real transformation happens—when employees integrate AI into their roles with clarity and confidence.
Advice for Building Your Own AI Working Group
Sarah Rich’s advice is straightforward but impactful:
“While there’s a tendency to get caught up in technology, the real challenge is the humans. Bring people together, make them feel safe, and give them a reason to pay attention.”
For startups and mid-sized businesses looking to replicate this success, Trenzest offers tailored AI adoption strategies, pilot programs, and team training modules to help ease the transition. Learn more about our AI consulting services for growing companies.
The Role of Platforms like Trenzest in Scaling AI Adoption
Platforms like Trenzest help businesses navigate the complexity of AI integration by offering:
Curated AI toolkits for different industries
Internal onboarding systems for teams
Workshops and mentorship models similar to AI Forward
Insights into scalable use cases for marketing, operations, and customer service
With the right structure, even small businesses can lead the way in AI innovation.
Final Thoughts: Human-Centric AI Integration
AI adoption isn’t just a tech initiative—it’s a people initiative. CarGurus’ success with AI Forward proves that when employees feel supported and empowered, adoption naturally follows. Creating the space for exploration, offering structured guidance, and respecting varying comfort levels are all crucial.
As you consider bringing AI into your organization, remember that success doesn’t come from tools alone—it comes from how people use them. And with partners like Trenzest, you can turn curiosity into capability.
