Best Advice From The AI Moment Podcast
Through my AI podcast (AI Moment), we shared a huge amount of actionable pieces of advice to business leaders.
Over the last few weeks, I have collated the best pieces of actionable advice from the podcast, alongside the advice I have shared most frequently in conversations and follow-up AI chats.
Run An AI Transformation, Not Just Tool Roll Outs
Explainer: AI is a transformation project, not just another tool roll-out or a workshop one-and-done exercise.
Recommendation: Read this dedicated post on AI transformation rollout.
Treat AI as business transformation, not tools: Start by deeply mapping real workflows and “unknown knowns”, then redesign work and company context before choosing or automating with tools.
Use a 4-bucket opportunity audit: For each task/process decide if AI should Accelerate (faster), Optimise (remove bottlenecks), Cure/Fix (inconsistent quality), or Kill (pointless/manual work that should disappear or be fully automated).
Run governed, cross-functional sprints: Build capability with training, workshops, and hackathons, assign a SWAT-style owner team, apply risk/governance by decision criticality, and execute in 30/60/90/180‑day sprints to move from pilots to scaled AI transformation.
Map Workflows Before Automating
Explainer: Many businesses make the mistake of deploying AI tools and licenses without understanding their existing processes, resulting in disjointed "random acts of AI". Applying AI to a poorly understood or informal process simply accelerates existing inefficiencies and creates high-speed chaos rather than actual business value.
Recommendation: Document your exact workflows and clean up operational inconsistencies department by department before deploying AI. Map out your customer journeys and internal processes on a whiteboard to identify exactly what tasks can be accelerated, optimized, fixed, or entirely removed.
Link to podcast: Want AI Success? Map Your Workflows
Build a Company Context Document
Explainer: Users often fail with AI because they treat every prompt as a blank slate, expecting the AI to read their minds and return generic outputs. The specific AI model you choose is increasingly less important than the quality, depth, and specificity of the context you feed it.
Recommendation: Create a concise 2-to-3-page "Company Context Document" containing your ideal customer profiles, brand positioning, and tone of voice guidelines. Assign an owner to keep this document updated, and instruct all team members to upload it at the start of every AI session to ensure high-fidelity, on-brand responses.
Link to podcast: Make LLMs Work Better With A Company Context Document
Maintain "Human-in-the-Loop" Verification
Explainer: Blindly offloading cognitive tasks to AI leads to the erosion of essential critical thinking skills, muscle memory, and workplace trust. Furthermore, AI can generate confident but factually incorrect "hallucinations" or low-quality "slop" that damages a brand's reputation if it is published without oversight.
Recommendation: Adopt a strict "Human-in-the-Loop" mandate where no AI-generated data or content leaves your department without a designated human taking accountability for its accuracy. Use AI to augment human judgment and do the heavy lifting, but always apply the filters of "Time, Trust, Truth, Verify, and Validate" before execution.
Link to podcast: AI Verification: Why Human Oversight Is Still Essential
Invest in Paid AI Subscriptions
Explainer: Judging AI's potential based on free versions is a trap, as these are essentially limited demonstrations that provide average, throttled results. Free versions lack the depth, breadth, and seamlessness required to truly transform business workflows and solve complex problems.
Recommendation: Upgrade your team to the paid tiers (around £/$20 monthly) to unlock stronger models and deeper capabilities. This small investment acts as a massive productivity multiplier that easily pays for itself if it saves an employee just one or two hours a month.
Link to podcast: Why Paid AI Subscriptions Will Improve Your Output
Run Practical AI Hackathons for Training
Explainer: Traditional, one-off AI training webinars often fail to drive actual adoption or overcome team resistance because they lack practical application. The "light bulb moment" for AI adoption rarely happens in a sterile corporate training session; it happens when cross-functional teams collaborate to solve tangible, messy business pain points.
Recommendation: Stop relying on generic training and instead facilitate regular, 90-minute AI hackathons or guided workshops. Challenge your teams to bring tasks they find boring or time-consuming, and have them use AI to build rapid working prototypes that solve those specific individual pain points.
Link to podcast: AI hackathons To Drive Business Innovation & A Cultural Shift.
