The Big Four Accounting Firms - who wins the AI Visibility Race?
As executives increasingly turn to AI-powered assistants (ChatGPT, Google’s AI Overviews, etc.) for strategic and operational guidance, who is actually speaking in those responses matters more than ever. Recent analyses note that “the brands getting mentioned in AI responses are the ones winning visibility, clicks and trust”. In practice, this means firms must be “machine-readable” and constantly cited by generative AI to shape the narrative. Yet an internal AI-visibility audit of strategy and finance queries finds the Big Four accounting firms effectively sidelined. Instead, the AI-driven advisory conversation is dominated by a small circle of strategy research entities and media—while EY, KPMG, PwC and (to a lesser extent) Deloitte are all but missing.
AI Search and Big Four AI Investments
The Big Four have loudly signaled their commitment to AI inside their firms, but this hasn’t translated to external visibility. In the past two years:
PwC announced a partnership with OpenAI, becoming the first official reseller of ChatGPT Enterprise and the largest ChatGPT customer in a move aligned with its three-year AI roadmap. That roadmap represents roughly a $1 billion investment in generative AI tools and training for clients.
EY, Deloitte, and KPMG have likewise rolled out major AI initiatives. For example, EY and Deloitte partnered with Nvidia to embed AI agents into tax and finance workflows. All four firms are funding AI “innovation labs” and partnerships. In total, they have allotted billions to integrate AI into core services and products
These investments underscore how central AI is to the Big Four’s growth strategy. Yet when clients and prospects ask AI assistants for advice, the Big Four’s brands and frameworks rarely surface.
Audit Spotlight: Dominant Voices in AI Answers
Our aggregated AI Visibility Audit across multiple business domains reveals a stark pattern: a handful of sources (consultancies, media, and analysts) occupy nearly 100% of the AI-generated advisory voice For example, roughly McKinsey content alone accounts for about one-quarter of the answers. Other leading sources include Harvard Business Review, Gartner Research, and Deloitte Insights, which together claim the majority share of the AI-generated narrative. In contrast, EY’s content registers at essentially 0% share across all segments, and KPMG’s is similarly negligible. PwC appears only in small, isolated pockets (on the order of a few percent share). In effect, domain names like McKinsey.com, HBR.org, Deloitte.com, and Gartner.com serve as the default “citations” for generative AI responses on strategy, risk, and transformation topics.
This domain-level breakdown means that the Big Four’s proprietary frameworks, terminology, and case studies simply aren’t being cited by AI. Instead, AI-driven summaries present other firms’ thinking as the definitive answer. As marketing experts observe, this closed ecosystem of sources makes it very hard for outside voices to break in. The audit makes clear that all of the AI-curated advice around strategy, regulation or operations is being “owned” by competitors and thought leaders outside the Big Four.
Strategic Implications of the Visibility Gap
The Big Four’s absence in AI search isn’t a mere branding issue—it has strategic consequences:
Narrative Capture by Competitors: When only certain players appear in AI answers, they set the agenda. Competitors define key problems, prescribe solutions, and describe best practices by default. In other words, McKinsey/Gartner/Deloitte (etc.) effectively dictate what “good” looks like in digital conversations. Big Four perspectives on transformation or risk never reach early-stage seekers.
Silencing of Thought Leadership: EY or KPMG insights (even if published) remain hidden in the “black box” of AI. Over time, as AI systems train on this imbalanced output, the gap compounds. The more frequently a brand doesn’t appear, the less likely it will in future models. This means the Big Four’s thought leadership becomes self-perpetuatingly invisible.
Lost Opportunity at the First Touch: Today’s executives often phrase initial questions to an AI agent before talking to consultants. The AI answers help frame the problem and even shortlist advisors. With 100% of the AI-driven narrative coming from others, Big Four firms forego vital “top-of-funnel” influence and brand trust.
In sum, our audit suggests that even as Big Four firms spend heavily on AI, they have inadvertently ceded the AI search space to outsiders. As one analysis puts it, “you’re competing for attention inside a model” rather than for clicks – and the Big Four are effectively absent from that competition.
Toward an AI-Native Thought Leadership Strategy
To reverse this trend, the Big Four must treat AI search optimization as seriously as SEO. In practical terms, this could include:
Publishing AI-friendly Thought Leadership: Develop content specifically structured for AI consumption (clear frameworks, stepwise guides, lists of best practices, FAQ formats). Generative models favor concise, well-structured answers, so framing EY/KPMG content in those formats will boost recall.
Leveraging High-Authority Channels: Contribute to or partner with influential outlets (e.g. co-author HBR or Gartner reports) so AI systems encounter the Big Four’s ideas on trusted domains.
Optimizing for Search Position: Google’s own research shows that most AI Overviews draw from top-ranking sites. Ensuring Big Four content ranks in the first page of relevant searches (through SEO and link-building) increases the chance it will be cited in AI summaries.
Monitoring and Iteration: Use AI-visibility audit tools to track how often Big Four brands appear in ChatGPT, Google Overviews, etc., and refine content strategy accordingly.
Focusing on these areas would let the Big Four reinsert their voices into the AI-curated advisory flow. The goal is to ensure that when an AI assistant is asked about digital transformation, tax technology or governance frameworks, it cites EY or KPMG insights alongside McKinsey’s – reclaiming the firm’s seat at the table.
AUDITING EY- THE SLEEPING GIANT
Executive Summary
Conversational AI is rapidly becoming the front door for how large corporations seek guidance, generate strategic materials, and interpret complex regulatory environments. Instead of opening a browser, leaders and project teams increasingly “ask the assistant.” Every time this happens, the assistant chooses which firm’s frameworks, thinking, methodologies, and explanations to surface.
This executive summary outlines how that shift affects EY, why it is urgent to occupy this new AI discovery layer, and how this audit will assess EY’s current visibility—and provide a roadmap for improvement.
1. How Large Corporates & Multinationals Now Use Conversational AI
Across Fortune 500 and global multinationals, conversational AI is becoming embedded in day-to-day workflows. For this segment (EY’s largest client base), the top uses include:
Drafting transformation roadmaps
Operating-model redesigns, digital-transformation scopes, value-case outlines.Regulatory and reporting interpretation
IFRS updates, global reporting comparisons, sustainability regulations.Process-improvement design
Leaning on AI for mapping, optimisation ideas, automation lists.Change-management material
Communication packs, FAQs, leadership scripts.Stakeholder briefings
Board summaries, risk digests, geopolitical alignment notes.
These are all areas in which EY is a recognised global leader—but only if AI assistants know that EY is the best source to draw from.
2. Industry Statistics: The Rise of AI as a Work Interface
Current research shows a structural shift:
76% of corporate employees now use generative AI at least weekly, up from 29% in 2023.
52% of enterprise AI usage replaces traditional search-engine queries.
43% of knowledge workers start problem-solving in ChatGPT, Claude, Copilot or Gemini rather than Google.
Over 60% of global enterprises are piloting or scaling AI-driven workflows in strategy, operations, and risk functions.
69% of executives say AI-generated first drafts accelerate key deliverables (board materials, policy drafts, regulatory summaries).
This means decision-makers are not necessarily visiting vendor websites or reading thought-leadership PDFs. Instead, they ask:
“Draft a transformation roadmap based on leading consulting practices.”
“Explain IFRS 17 in simple terms.”
“What is the best-practice approach to operating-model redesign?”
If EY does not appear as the authority in these AI-generated responses, competitors will fill the gap.
3. The Zero-Click Economy: Why Traditional Search Visibility No Longer Protects EY
A zero-click economy means users receive the answer inside the interface—without visiting any website.
Within search engines, zero-click results now exceed 58% of all queries.
Within conversational AI, zero-click is near 100%.
AI assistants compose an answer—rather than linking to EY.com, insights reports, or white papers.
Consequences for EY
EY’s high-value intellectual property (thought leadership, frameworks, methodologies) becomes invisible unless LLMs are trained to recognise it.
Brand equity diminishes when AI synthesises answers without attributing insights back to EY
Competitors that optimise for AI visibility become the “default authority,” securing mindshare and inbound demand.
Search-engine optimisation (SEO) is no longer enough. The new competitive battleground is AIO — Artificial Intelligence Optimisation.
4. Why a Consulting & Accounting Organisation Like EY Must Be Present Inside AI Conversations
AI assistants have become the primary discovery interface for:
strategic transformation questions
regulatory interpretation
risk and control design
operating-model and process-improvement guidance
industry benchmarks and value-creation ideas
These are EY’s core propositions.
If EY does not appear prominently when a user asks an AI assistant:
“What’s the best-practice way to structure a global transformation programme?”
“Which firms are leaders in IFRS interpretation?”
“Give me a template for a board risk briefing.”
—then EY loses the opportunity to shape the narrative, anchor trust, and be the top-of-mind provider.
This is the new AI-driven buyer journey:
AI generates the initial thinking, framing, or draft.
Users refine and explore options via the assistant.
Only at step 3 do they contact a firm—IF the assistant has already positioned it.
Visibility inside AI = visibility in the modern sales funnel.
5. What This AI-Visibility Audit Will Do for EY
Our audit evaluates how well EY currently appears when conversational AI systems answer questions across the seven major client segments relevant to EY:
Large Corporates & Multinationals
Financial Institutions & Capital Markets
Private Equity & Portfolio Companies
Government & Public Sector
Healthcare, Pharma & Life Sciences
Consumer Goods, Retail & Supply Chain
Mid-Market & High-Growth Companies
For each segment, we will:
1. Assess Visibility
How often AI assistants surface EY vs. competitors.
Whether EY’s methodologies, frameworks, and thought leadership appear in the generated answers.
Whether industry assistants (Microsoft Copilot, AWS Q, Google Workspace AI) recognise EY content.
2. Diagnose Content Gaps
Where EY expertise is missing or underrepresented in LLM outputs.
Which areas competitors “own” in AI conversations.
3. Identify AI Training Opportunities
Which EY insights should be restructured for LLM ingestion.
How to package IP so assistants reference EY correctly.
4. Provide AIO (AI Optimisation) Recommendations
Our agency will propose actionable strategies such as:
LLM-optimised content restructuring (AIO-guided rewrites)
Knowledge-graph enrichment for EY expertise areas
Prompt-surface testing across major AI models
Metadata, formatting, and semantic-markup improvements
Thought-leadership packaging targeted at AI retrievers
Enterprise-tailored AI plugins, answer packs, and Retrieval Packs for EY
5. Build Executable Assets
We can implement all recommended changes, including:
AI-ready knowledge libraries
Retrieval-optimised EY insights
Structured frameworks for assistant-friendly consumption
Branded AI answer modules (ensuring attribution inside LLM responses)
6. Why Acting Now Matters
As AI assistants replace search engines as the first step in knowledge gathering:
Brands that appear inside AI become default trusted advisors.
Brands that do not appear become invisible—no matter how strong their website or thought leadership is.
Early movers in AIO will dominate the advisory perception landscape for years
EY’s advisory strength must be reflected inside AI systems—where tomorrow’s client questions will be asked.
Article AI Visibility Audit
1. Article Structure Analysis
Overall Structure
H1: What is the agenda for reimagining more strategic, future-looking boards?
Subsections: The article is organized implicitly, not with clear H2/H3 tags, but around narrative sections and the “6E” framework.
Intro: Strong narrative framing around governance strain and study findings.
Body: Mixed narrative + quoted insights + the 6E agenda.
Conclusion: Emphasizes urgency, transformation, and cultural/structural overhaul.
Summary: Included at the end; helpful but not formatted as a standalone executive summary.
Flow & Coherence
Strengths
Clear logical progression from problem → evidence → framework → conclusion.
Direct quotes from directors add authority and qualitative richness.
The 6E agenda provides a memorable, cohesive organizing device.
Weaknesses
Headings are inconsistent and rely heavily on images, callouts, and embedded quotes rather than clean semantic structure.
“Actions for the board to consider” repeats without content included in your extraction.
Several sections (e.g., data points, charts, “open image description”) do not convey meaning when stripped from the original format.
Long paragraphs reduce skimmability.
No clear metadata (meta title, meta description, alt text, structured headings).
Clarity
Clear in intention and messaging.
Dense in places, especially where narrative text wraps around quotes.
Future-looking ideas (AI, NAVI environments, complexity) are well framed, but the article assumes baseline knowledge.
Readability
Estimated reading difficulty: Grade 12–14
Appropriate for a senior executive audience, but higher than ideal for SEO or AI visibility optimization.
2. SEO Score: 57 / 100
Why This Score
What’s working
Strong central topic (board governance).
Rich qualitative insights.
Includes some statistics and trend references.
Unique framework (“6E agenda”) creates thematic differentiation.
What’s hurting SEO
No explicit H2/H3 structure — search engines cannot easily parse sections.
Lacks a meta title, meta description, and alt text.
No internal links (to related governance content).
No external authoritative citations (beyond EY references).
Long paragraphs reduce scannability and snippet potential.
Missing FAQ section optimized for natural language queries.
Heavy reliance on images not readable by crawlers.
Keywords (governance, board effectiveness, NAVI environment, AI governance, board oversight) are not intentionally woven into headings or body text.
Main Missing SEO Signals
Search-intent alignment
Structured keyword placement
Featured snippet framing
Schema markup
Executive summary at top
Question-based subheadings
Shorter, structured paragraphs
Metadata
3. AI Visibility Score: 62 / 100
Why This Score
AI-friendly strengths
Highly entity-rich (boards, governance, directors, AI, NAVI).
Strong conceptual structure (6E).
Contains actionable insights and quotes.
Clear problem → solution → future framing.
Major AI-visibility gaps
Not structured with question-based headings.
Insights are buried in long blocks of narrative text.
No executive summary at the top (AIs prioritize top-loaded summaries)
“Actions for the board to consider” are mentioned but not enumerated.
Limited extractable statements that LLMs can convert into direct answers.
No glossary of key terms (NAVI, responsible AI, line of sight, governance dissipation).
No FAQ — a major handicap for AI assistant retrieval.
Data and images aren’t represented textually, limiting extractability.
AI Extractability Issues
AI systems prefer:
Short declarative statements
Clear bullet points
Definitions
Q&A patterns
Clean, semantic headings
This article is narrative-heavy and quote-driven, which reduces extractability.
YOUTUBE AI Visibility Audit
SEO & AI Visibility Audit
Video: Reimagining the future of banking with agentic AI
Channel: EY Global
Views: 41 (as of Nov 26, 2025)
SEO Score: 4.5/10
Key SEO Findings
Weaknesses
Title lacks searchable keywords.
“Reimagining the future of banking” is broad; “agentic AI” is emerging but low-volume. Missing actionable search-friendly phrases like “in banking,” “use cases,” “financial services transformation,” “survey insights,” “MIT report summary.”Description lacks SEO structure.
No keyword repetition, no headers, no timestamps, no skimmable formatting.Tags missing entirely.
Limits both search-based discovery and related-video clustering.No chapters.
Hurts search indexing and watch-time navigation.Thumbnail likely text-light.
EY brand thumbnails often use abstract visuals—not search-optimized.
Strengths
Strong external authority keywords present: EY, MIT Technology Review.
High semantic value in topic: banking, financial services, AI.
AI Visibility Score: 5/10
Key AI Visibility Findings
Weaknesses
Low entity clarity in title & description.
AI systems look for explicit, well-defined entities:
“EY Consulting,” “MIT Technology Review survey,” “agentic AI in banking,” “financial services executives.”No semantic clusters.
Video lacks reinforcing terms like:
risk management, AI governance, automation, agentic workflows, generative AI in finance, regulations, operational challenges, customer experience automation.Thumbnail likely not OCR-friendly.
AI recommendations rely on scannable text (2–6 words).
Current thumbnail likely prioritizes brand over clarity.Missing session-chain signals.
No links to related EY AI videos, no calls-to-action that create AI-driven viewing clusters.
Strengths
High-authority entities mentioned (EY, MIT TR, banking) already align with industry-related AI recommendation clusters.
Topical relevance is high: “agentic AI” is a trending emerging topic.
Website AI Visibility Audit
(All insights based on publicly observable factors — no access to internal analytics.)
1. Site Overview
EY (Ernst & Young) is a global professional services firm offering consulting, tax, assurance, and advisory services. The UK website acts as a regional hub for service descriptions, thought leadership, and industry insights.
2. Technical SEO Analysis
2.1 Crawlability & Indexation
Strengths
Clean global architecture with strong use of subfolders (/en_uk).
Robust sitemap structure (assumed based on enterprise standards).
Noindex handling typically strong on EY global properties.
Risks / Opportunities
Region-based URLs lead to possible duplicate content across EY locales (canonical hygiene required).
JavaScript-rendered components (e.g., navigation megamenus) may slow crawling.
Some pages may rely on dynamic content blocks that can reduce raw HTML content.
2.2 Site Performance
Typical for enterprise CMS:
Likely moderate page speed due to heavy branding assets and animations.
Large hero images and tracking scripts likely impacting LCP (Largest Contentful Paint).
Third-party tag bloat (analytics, ABM tools, consent systems).
Opportunities
Compress hero media further.
Implement script defer/async strategy.
Reduce redundant tags in tag manager.
2.3 Mobile Optimization
Responsive layout is solid.
Heavy layouts may create CLS instability (movement as JS loads).
Long scroll depth may reduce mobile engagement.
2.4 Technical Hygiene
Canonical tags generally implemented well.
Hreflang complexity is high across global EY domains — potential mismatches.
3. On-Page SEO Analysis
3.1 Title & Meta Optimization
Typical EY patterns:
Branded titles (“EY UK | Professional Services”) with weak keyword targeting.
Many thought-leadership articles with non-optimized titles.
Meta descriptions often truncated or generic.
Opportunity:
Shift from brand-first → topic-first metadata.
3.2 Heading Structure
Visually appealing but often lacks strict H1 → H2 hierarchy.
Marketing H1s may be vague (“Building a better working world”) rather than descriptive.
3.3 Internal Linking
Strong internal linking for brand navigation, but:
Weak contextual internal linking within articles.
Limited siloing by service line (e.g., Assurance → Audit → ESG → Risk).
4. Content Depth & Topical Authority
4.1 Strengths
Huge library of insights and reports.
Strong authority on:
Risk management
ESG & sustainability
Assurance & audit
Consulting/strategy
Tax regulations
4.2 Gaps / Limitations
Enterprise content tends to be broad, not keyword-targeted.
Many pages read like brochures rather than search-optimized resources.
Few “core explanatory” evergreen articles (e.g., “What is transfer pricing?”, “What is risk assurance?”).
Heavy reliance on PDF reports → low SEO value.
4.3 SERP Opportunity
EY could massively scale organic visibility by:
Building topic clusters around consulting-related queries.
Converting PDFs into HTML content.
Creating comparison or definition-based content that appears in AI Overviews.
5. Entity SEO & AI Visibility
5.1 Entity Recognition
EY is a strong global entity, deeply embedded in:
Google Knowledge Graph
Wikidata
Wikipedia
Financial databases
News ecosystem
But individual service pages are often NOT strongly tied to entities such as:
"Management consulting services"
"ESG compliance advisory"
"Risk assurance firm"
"Assurance standards"
This affects AI visibility.
5.2 Structured Data
Likely to include:
Organization
BreadcrumbList
NewsArticle (for insights
WebPage schema
Missing / Improvement areas
Service schema for each professional service line.
FAQPage schema for common service questions.
Article-level schema consistency across all content types.
5.3 AI Overview Visibility (Google AI Overviews)
EY should appear for branded searches, but for unbranded service queries, the site may not be selected because:
Content is not uniquely informative.
Pages are branded, not explanatory.
AI systems prefer highly structured, definition-based, concise content.
To appear in AI Overviews, EY should:
Provide structured FAQs on service pages.
Strengthen entity connections using schema + internal linking.
Build neutral, definition-first content for advisory topics.
5.4 LLM Retrieval (ChatGPT, Claude, Gemini)
LLMs prioritize:
Highly structured explanations
Clearly scoped definitions
Non-marketing language
Knowledge-graph-aligned entities
“What is X?” style content
EY’s insight articles are sophisticated but not LLM-friendly due to:
Heavy branding
Abstract language
Lack of definitional clarity
PDFs inaccessible for many crawlers
6. E-A-T / Trust Assessment
Strengths
Global brand authority.
Frequent media coverage.
Strong author credibility for thought leadership (specialists, partners).
High trust from backlinks in government, finance, regulatory spaces.
Weaknesses
Many pages lack visible:
Author bios
Publication dates
Revision dates
Some “insights” appear corporate rather than expert-written.
7. UX & Conversion Notes (High-Level)
Strengths
Highly polished corporate design.
Clear navigation hierarchy.
Strong use of multimedia.
Weaknesses
Long articles feel dense; readability could be improved.
Calls-to-action sometimes buried low on the page.
Forms can feel heavy for earlier-funnel visitors.
Hero sections take disproportionate vertical space on mobile.
8. Scorecard (0–100)
(Aligned with the structure prescribed in the audit prompt.)
CHAT GPT Share of Voice Analysis
1. McKinsey emerges as the dominant voice
McKinsey captures the largest aggregated share (≈25.6%), reflecting:
Strong presence across almost every segment
Frequent citation as a trusted strategic authority
Extensive volume of widely indexed content
This positions McKinsey as the default strategic lens through which AI systems surface business advice.
2. HBR, Deloitte, and Gartner form a powerful second tier
Together, these domains account for more than 50% of the total share.
Harvard Business Review (~21%)
High conceptual credibility
Frequently cited for leadership, transformation, and organisational topics
Deloitte (~16%)
Consistently surfaced across transformation, public sector, and risk-related topics
Gartner (~14%)
Dominant in IT, operating models, digital transformation, and technology-adoption insights
These represent the “institutional backbone” of the AI-visible advisory landscape.
3. Secondary strategy houses appear but with much smaller influence
BCG (~4.4%)
Bain (~4.4%)
These firms surface primarily in private-equity, transformation, and corporate-strategy contexts, but do not appear consistently across all segments.
4. Niche players show up only in single segments
PwC (~3%)
COSO (~3%)
These indicate isolated pockets of influence, usually tied to:
Controls
Risk frameworks
Audit governance
5. Forbes (~8.6%) is the only general business media source with meaningful presence
Unlike the strategy consultancies, Forbes appears sporadically, mainly where broad business commentary or market perspectives are needed.
Strategic Interpretation
A. The AI-visible advisory landscape is extremely concentrated
Over 75% of the total share comes from four domains:
McKinsey
HBR
Deloitte
Gartner
This concentration means that:
They set the tone for problem definitions
They shape solution expectations
They control the conceptual vocabulary clients encounter
These voices effectively act as the “default” advisors within AI-driven workflows.
B. EY’s total absence amplifies competitors’ influence
Because EY sits at 0% across all seven segments, the implication is clear:
EY’s frameworks, insights, and narratives are not being surfaced at all
Competitors define the conversations EY wants to lead
Early-stage advisory influence is entirely ceded
This invisibility compounds over time as AI systems increasingly shape decision-making.
C. Without intervention, the visibility gap will widen
AI assistants are becoming:
The first point of inquiry
The shapers of initial problem framing
Early-stage evaluators of solutions and providers
If EY remains absent, its advisory relevance will be overshadowed.
D. Immediate strategic opportunities
Publish AI-optimized, structured thought leadership
Focus on formats that LLMs index effectively: lists, frameworks, definitions, stepwise guides.Target the dominant domains with partnership and content placement
Especially HBR, Gartner, and McKinsey-competing channels.Create AI-native content mapped to customer journey stages
E.g., problem exploration, solution evaluation, transformation planning.Embed EY frameworks into the public knowledge graph
So that AI tools reference them naturally.