What actually matters now in AI for marketers—beyond the hype. Paul and Martin unpack the week’s launches from Anthropic and Google, new Microsoft–Claude tie-ins, and the UK government’s civil-service AI literacy push. They also tackle the practical question: should you chase “AI SEO” today, or double-down on timeless content and distribution?

Top takeaways

• AI visibility ≠ old SEO. Generative search is highly personalised; “rank tracking” for LLM answers is shaky. Invest in high-quality, well-structured content and robust distribution over gimmicky “get featured in ChatGPT” checklists.

• Anthropic’s direction: Haiku 4.5 offers fast, low-cost coding and general tasks; Claude Skills hint at SOP-driven, tool-aware assistants and a future marketplace.

• Enterprise shift: Claude is deepening its Microsoft 365 integration (SharePoint, Outlook, OneDrive, Teams), making business context more accessible to assistants.

• Video creation reality: Google’s Veo 3.1 and Flow expand control (reference frames, storyboard timelines). Quality still depends on human editing judgement—AI is an ingredient, not the whole recipe.

• AI Studio cleanup: Google has unified its playground and simplified keys/settings, making it easier for newcomers to explore models and tune temperature/controls.

• Public sector skills: The UK’s “One Big Thing: AI for All” aims to boost civil-service confidence via short modules and department case studies—baseline literacy first, then role-specific adoption.

• Training that sticks: Start with common foundations (what LLMs are/aren’t), then move to function-level workflows. Create “champion” groups and a light governance rhythm so updates translate into process change.

Chapters

00:00 Harrison recap; AI in sales needs thoughtful application, not blind scale.

03:00 Brand presence in LLM answers: content + distribution over hacks.

10:00 Why LLM personalisation breaks classic rank tracking.

15:00 Anthropic: Haiku 4.5 and Claude Skills; SOPs for agentic work.

21:00 Claude ↔ Microsoft 365: the enterprise context advantage.

25:00 Google Veo 3.1 & Flow: creative control vs. “one-click” video.

34:00 Google AI Studio: unified playground; why marketers should tune temperature.

38:00 “Zero-to-magic” tease; what a no-code app path might mean.

40:00 UK “One Big Thing—AI for All”: literacy at scale; early gov use cases.

42:00 Good AI training design: baseline, then function-specific change.

55:00 Reality check: useful today, but still needs steering and review.

Practical guidance

• If you’re a marketer: Treat AI outputs as drafts. Edit for voice, accuracy, and distinctiveness. Measure distribution as much as production speed.

• If you’re a leader: Provide one sanctioned assistant (Copilot/Gemini/Claude), set guardrails, and fund a small “AI council” to turn releases into workflow changes.

• If you’re experimenting with video: Use Flow (or your editor) to storyboard, trim, and mix assets. Don’t ship raw generations.

Mentioned in this episode

• Anthropic: Haiku 4.5; Claude Skills; Microsoft 365 integrations

• Google: Veo 3.1; Flow storyboard editor; AI Studio updates

• UK Government: “One Big Thing 2025—AI for All” initiative

• Discussion: training that works vs. one-and-done workshops

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🎙️ Artificially Intelligent Marketing: Episode 47 – Harrison Wade on “Why AI is NOT the Easy Button”

Welcome back to Artificially Intelligent Marketing! In this episode, Paul Avery is joined by special guest Harrison Wade, co-founder of Succession Bio. Harrison brings hands-on experience from the life sciences sector, revealing how his team is redefining sales and marketing through AI innovation.

From Business to Science Harrison shares his journey from software sales to leading go-to-market strategies for life science firms—where tools common in SaaS are still a rarity. He explains how this gap creates both challenge and opportunity for innovation.

AI in Sales Enablement & Marketing Discover why sales teams often lag behind marketing in tech adoption, and why tech-fluent, AI-first team members are essential for orchestrating automated workflows that actually deliver results.

What Works—and What Doesn’t Harrison details how his team uses robust context, training, and tools like Clay to supercharge outreach—highlighting the danger of treating AI like an “easy button.” A 27-page context document? Essential, not overkill.

Real AI Workflows, Not Magic Forget AGI hype—this episode is packed with practical advice on using AI for prospect research, workflow automation, and creative outreach. Think personalised videos, Suno-generated songs, and campaigns that cut through the noise.

Building the Future: Micro-Apps & Vibe Coding Paul and Harrison explore how tools like Replit and Lovable let marketers build lead magnets and custom web apps without coding skills—ushering in a new era of “vibe coding.”

Human Creativity Still Wins AI can scale output, but human creativity drives connection. Harrison argues that empathy, emotion, and storytelling remain the ultimate differentiators in AI-driven marketing.

Arms Race or Open Water? Will personalised AI content saturate the market? Harrison says no—most teams lack the expertise or drive to execute at scale. There’s still huge opportunity for those willing to experiment.

Actionable Advice

• If you love tinkering, start small and iterate.
• If you want results, partner with builders who do.
• For life sciences growth, Succession Bio can help scale your top-of-funnel efforts.

Key Takeaways

• AI isn’t the easy button—human creativity and context win.
• Automation is messy—curiosity and patience pay off.
• Personalisation breaks through—even songs can sell.
• The emerging “conductor” role is key: orchestrating tools to outcomes.

Connect & Challenge Want to stand out? Combine creativity and AI—send us a Suno-generated song about this episode using the YouTube transcript!

Contact For top-of-funnel support or AI workflow advice, reach out to Harrison at Succession Bio.

Subscribe to Artificially Intelligent Marketing for stories, workflows, and insights on AI in marketing—new episodes every week.

In this episode of Artificially Intelligent Marketing, Martin Broadhurst and Paul Avery reunite to explore how AI has transformed marketing over the past 18 months. They cover reasoning models, agentic automation, Microsoft Copilot’s evolution, open vs closed-source AI, and the rise of AI-powered hardware—sharing real-world insights and examples from their work.

Major Evolutions in AI for Marketers

• Reflection on the rapid progress of AI tools and models
• Overview of major shifts since the last episode
• How marketers are adapting to new AI capabilities

AI Reasoning Models

• Difference between chain-of-thought prompting and modern reasoning models
• Improvements in accuracy and reduced hallucinations
• Trade-offs between speed and reasoning depth
• Groq CEO’s insights on the value of ultra-fast inference

AI Tools Adoption and Platform Maturity

• Microsoft Copilot’s leap from basic to highly capable
• Key tools: Researcher agent, Analyst tool, and Copilot Studio
• Integration across Microsoft 365 (SharePoint, OneDrive, Teams)
• Comparisons with Google and OpenAI’s platforms
• Ongoing confusion over pricing and value

Model Selection: The “Model Roundabout”

• Recent advances in GPT, Claude, Gemini, and open-source models
• Balancing reasoning and instant modes
• Common use cases: coding, summarisation, planning, and copywriting
• Quirks such as GPT-5’s writing tone and output style
• Tips for reducing hallucinations and improving reliability

Open vs Closed Source AI Debate

• Rise and stall of open models like DeepSeek and Llama 4
• Meta’s shift from open development to proprietary AGI
• Open source’s future in experimentation rather than frontier innovation
• Market consolidation, privacy, and trust concerns

AI-Integrated Hardware and the Attention Economy

• Growth of wearable AI, e.g. Meta’s Ray-Ban smart glasses
• Privacy and social implications of constant recording
• Adoption driven by convenience and content habits
• Meta’s competing aims: productivity vs attention monetisation

Agentic Progress: AI Agents and Automation

• “Agentic AI” explained: systems acting autonomously to complete goals
• From document retrieval to full workflow automation
• Tools like Make.com, Zapier, and N8N enabling marketers
• Claude Code as an advanced example of self-directed agents
• Use cases: automated slide decks, proposals, and scheduled reporting

MCP (Model Context Protocol) Connectors

• Overview of MCP for connecting LLMs to CRMs and cloud tools
• Martin’s experience linking Claude to HubSpot and Google Workspace
• Examples of AI updating pipelines and deal notes automatically
• Benefits balanced against setup complexity

Current State of AI for Marketers

• Honest look at AI-generated content and “work slop”
• AI as a speed and productivity enhancer, not a replacement for experts
• Advances in visual and video generation:
  • Faster, more consistent imagery (Midjourney, DALL·E 3, Nano Banana)
  • Real-world use in proposals, events, and social media
• Emerging video models (Veo 3, Sora 2, Kling) offering realism and sound
• Reflection on low-quality AI output and the lasting importance of trusted brands