Back
EP 004
25 Min
Most vendors sell AI as a way to make a leader look smart and save money. Tamara Wall, who has led support through a 55-point swing in team engagement, says it does the opposite: it magnifies whatever your culture already is.
Tamara Wall does not see AI as software you buy. She sees it as an employee you hire, one that needs onboarding, coaching, and accountability. As Head of Support at Common Room, with prior leadership at Culture Amp and Datto, she has a sharp warning for leaders rushing to flip the switch. On this episode of the Fini Podcast, she explained why AI exposes bad leadership, how to bring a team along instead of scaring them, and which metrics actually tell you the truth.
Meet Tamara Wall
Tamara is Head of Support at Common Room and has led operations at Culture Amp and Datto. She has guided teams through dramatic change, including a period where engagement swung by 55 points, and she is known for building high-engagement teams. Her core belief: support is a critical, strategic function, not a cost center, and AI should make that more true, not less.
AI is a mirror
People talk about AI as a magic fix for broken cultures or weak leadership. Tamara's view is blunt: AI is a mirror. Whatever you already have, good or bad, it magnifies. If you are unclear, inconsistent, or operating without a vision, AI will expose it faster. But if your culture values accountability, transparency, and curiosity, AI becomes a multiplier instead of a replacement. The technology does not set the outcome. Your operation does.
Treat AI like an employee you hire
The most useful reframe in the conversation: introduce AI the way you would onboard a new hire. It needs training data, coaching, performance metrics, and accountability. You would not give a new agent one day of training and expect perfection, so do not expect it from AI either. And when the bot makes a mistake, Tamara does not call it the AI's fault. She treats it as an operational process that failed and needs adjusting. That shift, from blaming the tool to fixing the process, is what separates teams that improve from teams that give up.
The human role evolves, it does not shrink
A common fear is that if AI takes 60 to 70% of tickets, humans are left with nothing but angry, complex cases all day. Tamara reframes it: the human role evolves rather than disappears. When AI absorbs high-volume, low-complexity work, people are freed to solve harder problems, partner with product and engineering, protect revenue, and build real customer relationships. Support becomes a craft you teach deliberately through simulation, shadowing, and new AI-adjacent roles like prompt design and knowledge base management, not something people merely survive.
Her red lines, and the seduction of speed
Tamara is clear about what she will not automate: churn-risk escalations, emotionally charged situations, sensitive identity or safety issues, and contractual or legal commitments. Those require emotional intelligence, and automating them to save time replaces exactly the thing the moment needs. Her warning is that speed is seductive. When volume explodes, leaders panic and chase deflection, and inaccurate AI erodes trust fast. Her system is to pause, look at the actual quality, and pull AI back when the focus should be rebuilding trust rather than moving fast. Move fast, but with guardrails.
What support leaders should take from this
Fix the process, not the blame. When the bot fails, treat it as a broken operational step to adjust, the same way you would coach a person.
Onboard AI like a hire. Training, coaching, quality checks, and accountability apply to a bot just as much as to an agent.
Sell safety, not speed, to your team. People fear losing control and relevance. Show the roadmap, include them in the build, and make them co-owners of the future state.
Set red lines before you launch. Keep humans on churn risk, emotional, legal, and safety-sensitive cases. Those need a human heart and brain.
Drop CSAT for effort and health. Track customer effort, customer health, and product-quality signals. Ticket volume without context is just noise.
Start small and adapt in public. Pilot safely, measure relentlessly, and let your team see you adjust. Waiting for the risk to vanish is how you get left behind.
Listen to the full episode
Tamara goes deeper on leading teams through change, designing escalations, and why CSAT belongs to a different era, in the full episode of the Fini Podcast. You can follow her work on LinkedIn.
AI you can coach, measure, and hold accountable like a real team member is what Fini is built for. Book a demo to see it in action.
What does it mean to treat AI like an employee you hire?
Tamara Wall introduces AI the way she would onboard a new team member: it needs training data, coaching, performance metrics, and accountability. You would not expect perfection after one day of training a person, and the same applies to AI. When it makes a mistake, she treats it as an operational process to fix rather than the AI's fault.
Why does Tamara Wall say AI exposes bad leadership?
Because AI is a mirror. It magnifies whatever a culture already has. If a team is unclear, inconsistent, or lacks vision, AI makes that worse and faster. If the culture values accountability and transparency, AI becomes a multiplier rather than a replacement.
Which support metrics matter more than CSAT?
Tamara prioritizes customer effort, customer health, and product-quality signals over CSAT, which she considers antiquated because it captures a single moment rather than the whole journey. She also treats ticket volume without context as noise.
Which support tasks should stay with humans?
Churn-risk escalations, emotionally charged situations, sensitive identity or safety issues, and contractual or legal commitments. These require emotional intelligence, and automating them to save time removes what the moment actually needs.
