Human-and-Robot Influence Playbook
Create authoritative media that persuades people and earns citation by AI systems.
- Difficulty
- Advanced
- Time to result
- ~months to results
- Steps
- 6
- Confidence
- 94%
The Human-and-Robot Influence Playbook recognizes that content now reaches customers through two audiences: people and the AI systems that retrieve, summarize, and recommend information. Marketers identify high-value questions, then publish deep, expert-led assets supported by distinctive experience, evidence, or perspective. Those assets are distributed across formats such as video, podcasts, communities, newsletters, and web pages so both people and machines can discover them. Packaging must capture human attention while making the subject and authority clear enough for retrieval systems. Performance is assessed through direct engagement, AI referrals, citations, branded demand, and assisted conversions rather than clicks alone. The mechanism turns generative search from a pure traffic threat into another route through which authoritative media can influence decisions.
Origin
Extracted from Marketing Against The Grain after a HubSpot YouTube video cited by ChatGPT gained substantially more views.
Core principles
- 01Modern marketing influences both human audiences and machine intermediaries.
- 02Deep expertise is more defensible than broad commodity coverage.
- 03AI answers can suppress clicks while also creating new referral paths.
- 04Authoritative media in multiple formats increases discoverability.
- 05Influence must be evaluated beyond direct traffic attribution.
How to run it
- 1
Map Dual-Audience Questions
List the important questions buyers ask directly and the prompts they are likely to submit to AI assistants. Prioritize questions tied to high-fit customer needs.
Pro tip Compare conventional search queries with real sales, support, and community questions.
Watch out Do not optimize for artificial prompt variations that have no customer relevance.
- 2
Create Defensible Depth
Answer each priority question with expert reasoning, unique evidence, first-hand experience, or customer insight. Provide enough depth that an AI summary naturally points users toward the original source for more value.
Pro tip Use a credible practitioner as the visible source of interpretation.
Watch out Generic summaries give retrieval systems little reason to cite or recommend your asset.
- 3
Distribute Across Formats
Publish the expertise in formats suited to different contexts, including video, audio, community discussion, newsletters, and searchable pages. Connect the assets so authority compounds across the network.
Pro tip Adapt the substance to each format instead of copying the same asset verbatim.
Watch out Scattered content without a coherent topical focus weakens the authority signal.
- 4
Package for Discovery
Use precise titles, descriptions, thumbnails, structure, and context that clearly communicate what the asset answers. Make the presentation compelling to people and legible to retrieval systems.
Pro tip State the central question and distinctive value near the beginning.
Watch out Excellent substance can remain invisible when its packaging is vague.
- 5
Measure Expanded Influence
Track AI referrals, citations, branded searches, video views, direct engagement, and assisted demand alongside conventional clicks. Compare how assets perform across both human and machine-mediated journeys.
Pro tip Record unusual referral spikes when an AI result begins surfacing an asset.
Watch out Last-click attribution will understate influence that accumulates across repeated exposure.
- 6
Reinforce Earned Authority
Update and expand the subjects where the brand is repeatedly cited or trusted. Use audience feedback and new evidence to keep those assets current and differentiated.
Pro tip Turn successful expert content into a connected series rather than an isolated hit.
Watch out Stale expertise can quickly lose visibility in fast-changing topics.
In the wild
HubSpot published an expert-led YouTube explanation of DeepSeek. When ChatGPT surfaced the video in its search results, users who wanted more than the initial AI answer clicked through to hear the expert's full explanation. The hosts reported that this exposure tripled the video's views and helped make it one of the channel's most successful releases.
→ An AI assistant became a meaningful discovery channel for authoritative video rather than merely replacing a conventional search click.
A security company publishes a practitioner-led video, technical article, and community Q&A about a newly discovered attack. Each asset uses original test data and clearly explains who is affected. AI assistants cite the research in summaries, while users follow the citations to inspect the methodology and hear the practitioner's recommendations.
→ The brand earns both machine citations and human trust during a rapidly developing topic.
Common mistakes
Treating AI Only as a Threat
A team focuses solely on lost clicks and misses the possibility that AI systems can surface authoritative media and create qualified discovery.
Publishing Shallow Coverage
Broad, generic content is easy for AI to reproduce and offers neither machines nor people a compelling reason to prefer the original source.
Measuring Only Direct Clicks
Direct traffic metrics omit citations, repeated brand exposure, video discovery, and assisted demand created by machine-mediated journeys.
Is it for you?
Best for
It is best for expert-led brands whose buyers use both conventional search and AI assistants during research.
Not ideal for
It is not ideal for brands unwilling to publish substantive expertise or invest in authoritative content across multiple formats.
From the transcript
“now we're not just influencing humans we're influencing robots”
“you have to have this High influence High AI differentiated Playbook to succeed over the next three to five years”
From the episode
Did HubSpot Lose 80% of Blog Traffic? Here’s What Actually Happened