Do you need an AI policy? Clear guidelines on acceptable use, data handling, and transparency.

Default to transparency: “Unless there’s a reason not to, let’s openly share when AI helped create this.”

Draft a one-page AI use policy for your team with AI’s help - covering dos, don’ts, and disclosure.

Bias & Fairness: Reduce unintentional bias in AI outputs that could affect hiring, customer service, or decision-making.

Reframe AI as a co-pilot, not a threat. Position it as an assistant that drafts, checks, or supports—while humans still make the final calls.

Test AI outputs with two team members from different backgrounds to spot and correct bias before publishing.

Data Privacy & Security: Ensure sensitive data isn’t uploaded to public AI tools and protect client/employee information.

Anchor on time saved, not tech used. Focus on the hours reclaimed for strategic work, not the novelty of AI.

Train your team to anonymise data before inputting it into AI tools, using placeholders or dummy text.

Intellectual Property: Who owns AI-generated content, and how should teams credit or handle it?

Change the question: Instead of “Should we use AI?” ask “What’s the smartest way to use AI for this task?”

Use AI for first drafts, then apply human editing to align with brand voice and protect originality.

Job Roles & Redefinition: Which tasks should AI support vs. which remain human-led?

Highlight loss aversion: “Competitors are already saving costs with AI—are we comfortable falling behind?”

List 3 repetitive tasks your team does weekly and choose one to trial automating with AI.

Human Oversight: Keep a “human in the loop” for quality control and ethical checks.

Default to human + AI review. No AI output is considered final until signed off by a person.

Rotate an ‘AI reviewer of the week’ role across the team to ensure accountability.

Transparency with Clients: Decide when and how to disclose AI use in deliverables.

Social proof through team wins. Share small success stories of AI adoption internally to normalise its use.

Add an ‘AI-assisted’ tag to early drafts so it’s clear when tools have supported the work.

Productivity vs. Creativity: Balance efficiency gains with preserving originality and human insight.

Reward curiosity, not perfection. Encourage playful experimentation with AI tools.

Host a 15-minute “AI brainstorm sprint” where AI and humans compete to generate campaign ideas.

Costs & ROI: Avoid tool overload by choosing wisely and measuring benefits.

Use pre-commitment nudges. Set a 30-day AI challenge to lock in learning and usage.

Track hours saved vs. subscription costs for one AI tool over a month to measure ROI.

Accessibility & Inclusivity: Ensure AI enhances collaboration for diverse learning and working styles.

Gamify adoption. Try fun challenges like “AI vs. Human: who can draft the best version?”

Use AI to adapt one document into visual, audio, and text-friendly versions for different learners.

Employee Training: staff so AI becomes an enabler, not a stressor.

Make training the default. Offer AI upskilling as opt-out rather than opt-in.

Add a 10-minute “AI tip of the week” to team meetings for ongoing, bite-sized training.

Change Resistance: Manage fear, skepticism, or over-reliance on AI among staff.

Make it easy: start small. Focus on automating one simple, repetitive task first.

Trial AI meeting summaries for just one recurring weekly meeting before rolling it out wider.

Legal & Compliance Risks: Stay ahead of evolving regulations around AI use in business.

Set visible AI goals. Example: “Our aim is to save 10 hours/month with AI.”

Use AI to generate a compliance checklist for evaluating new tools before adoption.

Security of AI Tools: Evaluate the safety of platforms (data storage, open vs. closed systems).

Leverage status quo bias. Introduce AI within familiar workflows (email, Slack) so it feels natural.

Trial AI auto-summaries of Slack channels or email threads to reduce overload.

Future-proofing: How today’s AI choices impact scalability and resilience tomorrow.

Future-self framing. Ask: “In 2 years, will our team thank us for experimenting early?”

Ask AI to scan industry reports and summarise 3 upcoming trends in your sector.