CEO: You read the Shopify and Fiverr leaks. Now what?
(Do you even have an AI memo to leak?)
The leaked internal AI memos from Shopify and Fiverr weren’t just noise. They revealed two very different leadership responses to the same pressure: how to integrate AI across a business.
Shopify treats AI as a co-worker and expects employees to use it that way. Fiverr’s memo was a warning shot about restructuring, accountability, and the pace of change. The language was clinical. The intent was clear.
If you’re in a leadership role and haven’t reacted yet, it’s time. This isn’t about theory anymore. This is about what CEOs and exec teams need to do next.
Things have moved on since I shared my 25-step AI adoption strategy in February (although it’s still very relevant!). If you’re a CEO, here are 20 specific, practical moves you need to consider making in response to the AI shift - based on what I’m seeing in the leaked memos, expert networks, and boardroom conversations in 2025.
CEO, shift your mindset
Start learning again
If you’re not staying up to date on AI, you are already a liability. You don’t need to be technical, but you do need to understand the fundamentals: what tools can do, how they’re evolving, and what risks they carry. Block out time each week to read, test, and talk to people who know more than you. This is a core leadership skill now.
Put emotional intelligence at the centre
As AI handles execution, your edge comes from emotional intelligence. That means being able to lead with clarity, handle complexity, and navigate fear. Equip your managers with training that goes beyond performance reviews - focus on coaching, listening, and managing through uncertainty.
Adaptability is now a requirement
Planning cycles are collapsing. The idea that you can define a five-year workforce strategy is outdated. Instead, focus on building a culture that can shift quickly. That means rapid testing, iterative learning, and removing the stigma around change.
Redesign roles around purpose, not process
Most job descriptions are about tasks. Those tasks are now being automated. Redesign roles so they’re built around outcomes and purpose - what people are trying to achieve, not just what they do day-to-day. This creates room for creativity, judgment, and value that AI can’t replicate.
Don’t wait for inequality to become a crisis
AI will reward people who already have access to tools, time, and networks. If you’re serious about equity, start allocating budget and headcount to skills development for the people who are most at risk of being left behind. This isn’t charity - it’s risk management.
Rethink your organisation
Champion strategic upskilling
Don’t waste money on general AI training. Identify where in your business AI will have the most immediate impact, and upskill there first. Build custom programs, bring in experts, and track whether people are actually applying what they’ve learned.
Create internal talent marketplaces
People are going to want to shift roles. Some jobs will shrink, others will evolve. Make it easier for people to move internally than to leave. Build an internal platform - or even just a shared doc - where people can see emerging roles and projects and put themselves forward.
Build trust through transparency
People don’t expect you to have all the answers, but they do expect honesty (or radical candour). Share what you know. Be clear about what’s changing, what’s not, and where decisions are still being made. Secrecy breeds resistance. Transparency builds alignment.
Empower employees to shape adoption
Fiverr's memo was a list of decisions made at the top. Shopify asked employees how they wanted to use AI. The latter gets you more ideas, more buy-in, and fewer surprises. Ask people what’s slowing them down - and then apply AI there first.
Set accountability rules now
AI will make mistakes. You need to decide now who is responsible when that happens. Is it the tool owner? The team lead? The user? Set clear lines of accountability so no one’s guessing later. Make it someone’s job to check AI output before it hits clients, regulators, or the public.
Upgrade how you integrate tech
Foster human:AI collaboration
This isn’t about replacing people - it’s about redesigning teams. Where can AI take the first pass, freeing your team up to add judgment? Where do you still need a human in the loop? Build these decisions into your workflows now.
Audit your workflows
If you haven’t already audited your internal processes, start today. You’re likely wasting hundreds of hours a month on tasks that AI could handle. Find those. Document them. Replace them. Don’t build a strategy around gut feel.
Build guardrails early
Too many companies delay conversations about ethics, privacy, and bias. That’s a mistake. You need clear guidelines on how tools should be used, what data can be fed into them, and what’s off-limits. Don’t outsource this to legal. Make it a leadership issue.
Focus on small, successful pilots
Big transformation plans sound great on paper. They rarely work. Find one department, one process, and one clear metric. Run a pilot. Prove it works. Then roll it out wider. This is how real adoption happens.
Measure adoption and impact
It’s not enough to say “we’re using AI.” You need to know who’s using it, how often, and what results they’re seeing. Set benchmarks. Track change. Make this visible across the organisation so teams can learn from each other.
Lead like it’s 2025
Tell your AI story internally
If your team doesn’t understand your AI strategy, they’ll assume the worst. Communicate early and often. Explain the why, the how, and the expected outcomes. This isn’t a tech story - it’s a business story.
Train managers to lead hybrid teams
Managing people alongside AI workflows is new territory. Managers need help. Provide playbooks and training on everything from reviewing AI-generated output to coaching employees on how to work with automated systems.
Encourage cross-functional squads
Some of your best AI ideas won’t come from IT. They’ll come from someone in ops who’s been repeating the same process for three years. Build squads that mix functions and levels. Give them permission to solve real problems with new tools.
Reward experimentation (and failure), not just success
If you only reward what works, people will play it safe. Reward effort, learning, and smart risk-taking. Build a culture where trying something new - even if it fails - is seen as a contribution.
Update your hiring and performance metrics
AI changes what good looks like. You need people who can adapt, learn fast, and collaborate with tools. Rewrite job descriptions. Change how you assess candidates. Update performance criteria to reflect the reality of hybrid human-AI work.
And if it all sounds too much: suck it up and do it anyway. Clear you schedule. Make space. Read books. DON’T NEGLECT THIS.