Generative Engine Optimisation: How brands shape AI answers

Pead’s new service for Generative Engine Optimisation (GEO) marks a clear pivot in corporate communications: instead of chasing clicks and links, brands must now shape the sentences that AI systems hand to customers and stakeholders when asked about them. This Auckland-based agency’s offering — a mix of audits, workshops and advisory support — is one of the first purposive commercial answers to a subtle but fast-moving change in how discovery and decision-making work online.

Background​

Generative AI has changed the interface between people and information. Where search engines historically returned ranked lists of links, today’s generative systems synthesize answers in natural language — sometimes with citations, sometimes without. The result is a “zero‑click” environment where the first impression for many buyers or voters is the answer the model composes, not the source documents behind it.
This shift has spawned a set of practices variously called Generative Engine Optimisation (GEO), Answer Engine Optimisation (AEO), or simply AI‑aware content strategy. These disciplines extend longstanding SEO and reputation-management work into a new objective: being the content that AI systems select, summarise and attribute inside generated answers.
Pead’s announcement is significant because it packages GEO as a comms-led service: audits of owned channels, outreach and earned‑media strategies to influence third‑party sources, and hands‑on workshops to educate corporate teams. The agency positions SEO‑style tactics alongside classic PR levers — precisely the mix that many experts now recommend for AI visibility.

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Why this matters: the stakes for brands​

AI is no longer an experimental channel for early adopters. Research cited by the firm indicates that a substantial share of younger New Zealanders already rely on AI to research businesses and products. Where independent studies and industry analyses converge is this: AI systems increasingly shape perception and purchase intent. That makes the content they draw on — and the way they synthesize it — a material reputational and commercial risk.
Key reasons brands should care now:

• First impression is the answer: Users increasingly accept the model’s response as the primary, or even sole, source of truth.
• Unguarded third‑party influence: Generative systems often synthesise and cite external content; that content may be outside a brand’s direct control.
• Fewer clicks, more authority loss: Zero‑click answers reduce referral traffic yet can still shape brand perception positively or negatively.
• Regulatory and trust exposure: As AI outputs drive decisions, errors or biased summaries can lead to reputational harm and regulatory scrutiny.

These dynamics raise two practical imperatives: brands must both own the way their facts and claims are presented (owned channels) and influence the third‑party ecosystem that feeds AI answers (earned channels).

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What Pead announced — the practical offer​

Pead frames its GEO service around a hybrid skill set: public relations expertise tied to technical digital experience. The announced service components include:

• GEO / AEO audits of owned digital assets (website content structure, schema markup, factual clarity).
• Workshops to educate marketing and corporate affairs teams on how AI systems retrieve and use content.
• Advisory support to plan earned media, thought leadership and structured content tactics designed to raise a brand’s citation footprint inside AI outputs.
• A downloadable GEO guide aimed at senior marketing and business leaders.
• Partnership activity: Pead is working with the Trans‑Tasman Business Circle to form a Corporate Affairs Circle focused on reputation, risk and organisational leadership — the first session will address influencing AI.

Pead’s public materials and commentary say the approach combines owned assets (structured web content and schema) with earned coverage (media placements, industry platforms and social content). The firm highlights that much of the content AI cites comes from third‑party sources, which shifts the balance of effort away from only optimising brand sites.
Note: several numerical claims in Pead’s materials — including a cited rate of “nearly 90% of citations” coming from third‑party online resources, and a statistic that “48.4% of New Zealanders under 45 use AI tools when researching a business” — are drawn from the agency’s commissioned research and public materials. Those figures are plausible and consistent with industry patterns, but the detailed methodology for Pead’s study is not publicly available at the time of writing; readers should treat such figures as indicative rather than independently verified.

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GEO / AEO explained: what it is, and how it differs from SEO​

Definitions and distinctions​

• SEO (Search Engine Optimisation) optimises pages to rank in search results — the goal is clicks and traffic.
• AEO (Answer Engine Optimisation) focuses on structuring content so it can be returned as a direct answer in featured snippets, voice assistants and knowledge panels.
• GEO (Generative Engine Optimisation) targets AI engines that synthesise answers from multiple sources (LLM‑driven chat interfaces and AI Overviews). The goal is to be cited or quoted inside the generated response.

In practice, GEO/AEO overlap with SEO but redefine the metric of success: not position on a ranking page but presence inside an answer. That requires a shift in content design and distribution: shorter, extractable answer capsules; data and first‑party research; structured markup; and presence across authoritative third‑party sites.

Why generative systems change the game​

Generative engines use retrieval systems that prefer precise, authoritative snippets that can be stitched into a coherent narrative. They also value:

• Structured data and schema (highly extractable content).
• Clear entity signals (consistent names, E‑E‑A‑T cues).
• Freshness and first‑party data (original research and unique data points).
• Third‑party corroboration (multiple mentions across independent sites increase perceived authority).

Because many of these signals live outside brand control, PR and earned-media become essential weapons in the GEO toolkit.

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The technical levers brands must master​

Getting into AI answers is both a communications and a technical exercise. The most effective tactics include:

• Use schema markup and structured FAQ/HowTo content so that retrieval systems can extract clear answer units.
• Publish answer capsules: a short, 20–40‑word paragraph immediately following question‑style headings that succinctly answers the query.
• Produce original research and first‑party data — studies, surveys, benchmarks that provide unique, citable facts.
• Build co‑citation networks through partnerships, guest articles, and media placements to create semantic associations between brand and topic.
• Ensure entity verification: claim pages, Google Business information (where relevant), and clear author credentials that tie content to verified organisational identity.
• Adopt consistent naming and terminology to reduce ambiguity when models perform entity resolution.
• Monitor AI referral patterns and the domains most frequently cited by target engines; adjust outreach to those sources.
• Implement content stamping (clear dates, authorship, and structured assertions) so that retrieval models can evaluate freshness and authority.
• Coordinate PR and SEO teams to amplify trusted content across a broad set of authoritative outlets.

These technical levers are already moving from theoretical to routine in the marketing tech stack. Agencies that combine PR sophistication with technical SEO capabilities — the model Pead promotes — can more readily deploy them.

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Where earned media becomes decisive​

One of the central themes in the GEO conversation is that earned coverage matters more than ever. Several independent analyses of AI citation patterns show that models rely heavily on well‑structured, authoritative third‑party content — encyclopaedias, major news outlets, specialist industry platforms and sometimes even community forums.
Why that matters:

• AI systems prefer sources with editorial standards and cross‑citations. A strong mention in a reputable outlet increases the chance an AI will use that item as a citation.
• Third‑party corroboration reduces the perceived risk for a retrieval model. Multiple independent mentions of the same fact raise confidence.
• Community sites and forums can punch above their weight: even if rarely shown as explicit citations, such sources can influence an AI’s internal retrieval signals.

For brands, the implication is clear: SEO alone is insufficient. A deliberate earned‑media strategy — press releases written with structured facts, timely thought leadership pieces, industry reports and influencer‑led content — broadens the pool of citable references that feed AI answers.

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Ethical and reputational risks​

GEO is not just a toolset; it’s a set of levers that can be misused. Brands and agencies must navigate these risks:

• Gaming and manipulation: Intentionally seeding false or misleading content to influence AI answers is a reputational hazard and could trigger regulatory or platform penalties.
• Over‑optimisation: Creating content solely to be machine‑cited (thin answer capsules without real value) erodes user trust and may be deprioritised by models as they learn.
• Dependency on opaque systems: AI engines update frequently. Tactics that work today may stop working after a model change.
• Amplifying errors: If models synthesise incorrect assertions based on third‑party content, brands can be wrongly framed and may struggle to correct the record across the web quickly enough.
• Privacy and data ethics: Publishing datasets and first‑party research must comply with privacy and ethical guidelines; poor practice exposes organisations to legal risk.

Responsible GEO therefore requires a guardrail strategy: transparency, adherence to journalistic standards, and a readiness to correct and document claims publicly.

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Governance and measurement: how to know you’re winning​

Measuring GEO progress differs from classic SEO KPIs. Useful metrics include:

• Citation velocity — the rate at which target domains and AI engines cite your content in generated answers.
• Brand mention spread — the variety and authority of third‑party domains referencing your brand and key messages.
• Answer presence — instances where an AI-generated answer contains your brand’s data or phrasing (sampled and verified).
• Sentiment shift in AI responses — qualitative tracking of how AI systems characterise your brand over time.
• Referral change — even if clicks fall, track downstream conversions that originated from an AI‑generated answer (via surveys or UTM-tagged content where possible).

Practical monitoring tools blend traditional web‑listening, SEO tools, and new LLM‑centric tracking platforms that attempt to map which domains are most frequently cited by which AI systems. Establishing a control baseline — a snapshot of how AI currently represents your organisation — is the first measurable step.

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Practical roadmap for corporate teams (10 steps)​

• Run a GEO audit: map current content, structured data and third‑party mentions. Identify the short list of queries customers ask.
• Create answer capsules for priority queries on owned pages (concise, authoritative, data‑backed).
• Publish original research or case studies that provide unique, citable facts.
• Implement schema markup for FAQ, Product, Organization and Article entities.
• Build a media placement plan targeting authoritative outlets and specialised platforms that AI engines frequently cite.
• Coordinate PR and SEO workflows to ensure consistent messaging across owned and earned content.
• Verify business entities across directories and knowledge graph entries to strengthen entity signals.
• Launch monitoring for AI answer presence and citation patterns across major generative engines.
• Prepare rapid-response playbooks to correct misinformation and request updates where errors appear in AI outputs.
• Set governance: ethical standards, audit trails and disclosure policies for any content intended to influence AI answers.

This is a cyclical process: publish, measure, iterate, and scale the content and outreach that demonstrably increases the brand’s presence inside AI answers.

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The regulatory and trust dimension​

As AI systems assume stronger influence on consumer decisions, regulators and standards bodies are focusing on transparency and accountability. Two likely trends:

• Disclosure expectations: Users and regulators will expect clear signals about when an answer is AI‑generated and what sources were used, which places a premium on brands being both visible and verifiable in the citation trail.
• Auditability: Organisations may be required to demonstrate the provenance of claims used to influence public perception — a demand that favours documented, high‑quality sources over ephemeral content tactics.

Brands should pre‑empt these demands by maintaining clear documentation of sources, publishing methods for original research, and building an auditable trail of corrections and updates.

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A critical appraisal of Pead’s approach​

Pead’s GEO service represents a sensible, market‑responsive offering: it marries the communications muscle required to generate authoritative mentions with technical expertise to make owned content machine‑friendly. The strengths include:

• Integrated skill set: Combining PR and digital teams is essential; GEO is interdisciplinary.
• Actionable tactics: Audits, schema work and targeted outreach are the right building blocks.
• Emphasis on earned media: Recognises the leverage third‑party sources have over AI outputs.

But several caveats deserve emphasis:

• Evidence transparency: Pead’s promotional materials cite specific figures about AI usage and citation distribution. Those numbers appear to come from commissioned research or proprietary analyses. Without public methodology, the precise reliability and representativeness of those figures cannot be independently verified.
• Rapid platform change: AI retrieval and citation behaviours evolve rapidly. Tactics that succeed today may need retooling after model or policy changes from platform providers.
• Ethics and oversight: Agencies must avoid turning GEO into a licence to manipulate perceived facts. A responsible practice must insist on accuracy, proper disclosure and swift correction procedures.
• Measurement maturity: The tooling around GEO is nascent. Many monitoring vendors use small samples or opaque methods; marketing teams should be cautious about over‑interpreting early signals.

Overall, Pead’s service is a forward‑looking response. It will, however, need to adapt continually and be transparent about measurement to sustain client trust.

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For in‑house legal, communications and marketing leaders: what to ask an agency​

• Can you share the methodology behind any stated research or citation statistics?
• How do you measure AI answer presence and which engines do you monitor?
• What are the ethical guidelines you follow when influencing AI‑visible content?
• How will you coordinate with our SEO, legal and privacy teams when producing first‑party research or public statements?
• What contingency plans exist for correcting AI‑generated misinformation about our brand?
• How are results reported and what time horizon do you recommend for meaningful change?

Demanding answers to these questions will separate tactical vendors from strategic partners.

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Looking ahead: the next 24 months​

Expect three interlinked developments:

• Standardisation of GEO practices: Tactics like answer capsules, schema and entity verification will become mainstream operational vocabulary across marketing teams.
• Better measurement tools: Vendors will launch more robust, engine‑specific citation tracking and attribution models — albeit with imperfect coverage at first.
• Policy and platform guardrails: Platforms and regulators will push for clearer provenance and audit trails in AI outputs, favouring content with transparent sourcing and verifiable claims.

The firms that succeed will be those that combine disciplined content practices with ethical standards and measurement rigor. GEO is not a one‑off campaign; it’s an ongoing competency that needs people, process and technology.

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Conclusion​

Pead’s GEO service is an early, pragmatic answer to a real shift: generative AI now influences reputation and decision‑making in ways that demand new disciplines. The core lesson for brands is straightforward but profound — you can no longer treat search and discovery as a click journey alone. The sentences AI returns to users are the new battleground for attention and trust.
That battleground requires a hybrid approach: crisp, structured owned content and a broad, authoritative earned presence across third‑party outlets. It also needs ethical guardrails, transparent measurement and the organisational will to treat content as both an asset and a source of accountability.
For communications and corporate affairs leaders, the imperative is clear: begin the audit, align PR and SEO teams, and build a governance framework. The systems that make reputations are changing; preparedness now will determine who gets quoted — and how — when the next customer, journalist or regulator asks a generative AI about your brand.

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Source: ChannelLife New Zealand https://channellife.co.nz/story/pead-launches-geo-service-to-shape-ai-brand-answers/