
It’s December 2025, and you're finalizing your 2026 board deck. Beyond the P&L scrutiny, you know the question that's coming: "What's our AI strategy?"
If you don't have a solid answer ready, let me give you one that's proven, practical, and profitable.
The #1 Use Case for AI in Your Company
Customer support. Full stop.
Before you think this sounds too simple, hear me out. I've built what I call the "AI Implementation Triangle" think Maslow's hierarchy, but actually useful for business leaders like us.
Three layers:
Layer 1: Tasks that are repetitive and nobody wants to do
Layer 2: Tasks people aren't naturally good at
Layer 3: Tasks requiring speed and urgency

Customer support lives squarely in Layer 1 and that's exactly why it's your best entry point.
Why Customer Support Is Burning Your Money
Let's talk reality. Go ask your CHRO what department has the highest churn. I guarantee they'll say customer support. You're probably seeing three out of five new hires leave, with average tenure barely over 12 months.
Why? Because 50%+ of support tickets are repetitive. Nobody dreams of earning barely above minimum wage answering the same questions hundreds of times a day, measured against brutal volume metrics and CSAT scores.
The scaling problem is even worse. If you're in e-commerce, you need to 3x your team for holidays then downsize. Training takes 1-3 months depending on product complexity. Release an update at noon, and your team won't be fully trained until next week.
What AI Changes Overnight
Here's where it gets interesting. At my company, we implemented Kayako's AI agent platform. The results:
70% of tickets now handled by AI (700 out of every 1,000)
50% reduction in support costs
Increased pay for remaining team members (2-3x in some cases)
24/7 coverage with zero holidays, sick days, or turnover
But here's what surprised me most: We didn't lay people off. We upskilled them into Level 2 and 3 agents. One former support rep is now building our AI renewals agent, automating contract red lines and quote management.
Train the AI once, and it's done,no 10,000 repetitions needed. Update your product at 12:01? The AI knows it by 12:02. Perfect brand voice, perfect recall, every single time. No bad days after angry customers.
Your 2026 Board Answer
When your board asks about AI strategy, here's what you tell them:
"We're implementing AI-first customer support that scales our capability without scaling headcount. We expect to see 70% automation rates while upskilling our team into higher-value roles. It's measurable, it's working in the real world, and it's our foundation for AI across the organization."
That's a confident, data-backed answer that demonstrates real AI leadership, not just AI hand waiving.
What This Means For You
You have options:
Reinvest savings into product or growth
Improve margins and keep the savings
Upskill your team into better-paying, more fulfilling roles
All of the above
This isn't just about cost savings. It's about proving to your entire organization that AI implementation works, building confidence for future AI initiatives across other departments.
Ready to Move?
My team can implement this at your pace, one week or one quarter, we work at your pace. We use Kayako: $79 per seat/per mo, $1 per AI-resolved ticket.
Visit Kayako.com to learn more, or reply to this email and I'll personally walk you through how we did it.
Your board is going to ask the AI question. Make sure you have the right answer.
Kathy
P.S. What do you have to lose besides your board's confidence that you can lead AI transformation? Let's make sure that doesn't happen.
P.P.S. What is in my board deck for 2026 AI Initiatives?
AI agents managing the customer success process so we can touch more customers more often. Less human admin work, more human-to-human meetings.
AI reviewing legal contracts to reduce our contract review bill. Paying $400/hour for something we've done hundreds of times is the definition of insanity. Those redlines will be managed by an AI agent.
AI rebuilding legacy software to breathe new life into products near end-of-life. All software eventually needs rebuilds to work with modern tech stacks or it dies. It's painful and nobody wants to spend a year doing a rebuild but AI can do it in a few weeks to months.
AI doing bug fixes as tickets come in through support. This will be an extension of Kayako. No more having 30-50% of your expensive engineering team working on bug fixes. That falls squarely in the "don't want to do and repetitive" bucket.