Global advertising crossed a threshold in 2025 that few could have predicted a decade ago. For the first time in history, total worldwide ad expenditure surpassed $1 trillion in a single year. That milestone, while significant on its own, is not what defines the current moment in paid search. What defines it is the tension underneath — between platforms that are automating everything and practitioners who are finding those automations increasingly difficult to control, measure, and trust.
The State of PPC 2026 Global Report is the most comprehensive survey of paid media professionals ever published. Drawing on responses from 1,306 PPC professionals across North America, Continental Europe, the UK, and beyond, it captures what is actually happening inside campaigns, agencies, in-house teams, and boardrooms. Not predictions. Not projections. Real data from the people running real budgets.
This post breaks down every major finding from that report. It is written for PPC managers, marketing directors, agency owners, CMOs, and anyone responsible for allocating digital advertising spend in 2026. The picture it paints is not uniformly positive — but it is honest, and the numbers are specific enough to act on.
Who Responded and Why the Data Matters
Before drawing conclusions from any industry survey, methodology matters. The 1,306 respondents in this report represent a global, experienced cohort. Continental Europe accounts for 45.8% of respondents, North America for 29.4%, and the UK and Ireland for 12.8%. The remaining share spans Asia-Pacific, the Middle East, Africa, and Latin America.
Experience levels skew senior. The majority of those managing accounts above $3 million per month have 10 or more years in the industry. This is not a survey of newcomers forming first impressions — it is a snapshot of institutional knowledge.
Respondents span agency-side professionals, in-house marketers, and independent consultants or freelancers. Pure-play e-commerce and retail make up 29% of advertiser respondents, with the remainder spread across lead generation, B2B, SaaS, financial services, and other verticals. The breadth matters because PPC behaves differently in each of these categories — what works for an e-commerce brand running Performance Max shopping campaigns is not automatically applicable to a B2B software company running LinkedIn lead gen.
The $1 Trillion Market and Its Three-Platform Concentration Problem
The headline figure — $1 trillion in global ad spend — tells one story. The concentration of that spend tells another.
Of all digital advertising dollars spent in 2025, 89% flowed to just three platforms: Google, Meta, and Amazon. That is not a market with healthy competition. It is an oligopoly, and every year the concentration intensifies rather than relaxes.
Google alone commands 94% of the global search advertising market, generating approximately $225 billion in search revenue. Microsoft, through Bing and its associated properties, holds the remaining 6% — worth roughly $14 billion. The gap between first and second place in search advertising is not a gap. It is a chasm.
Meta brought in an estimated $196 billion in advertising revenue in 2025, reflecting an 18% compound annual growth rate (CAGR) over the preceding five years. Amazon’s advertising arm reached $69 billion — notable because Amazon entered the advertising business relatively recently, and its 28% CAGR from 2020 to 2025 is the fastest of any established platform.
The growth story everyone is watching most closely is TikTok. The platform does not publish official advertising revenue, but estimates place its 2025 total at $32 billion — driven by a jaw-dropping 74% CAGR from 2020 to 2025. Reddit is the second-fastest growing platform by revenue with a 60% CAGR, suggesting that community-driven, intent-based advertising is finding its footing among mainstream advertisers.
At the other end of the spectrum, X (formerly Twitter) has declined. Its estimated 2025 advertising revenue of $2.3 billion reflects a -6% CAGR since 2020, making it the only major platform in the report with a sustained negative revenue trajectory. That figure matters for media planners because it is not just a revenue story for the platform — it signals reduced audience engagement, reduced advertiser confidence, and reduced ad inventory quality.
These numbers frame the rest of every decision in this report. When Google, Meta, and Amazon together absorb nearly nine out of every ten digital advertising dollars, every discussion about budgets, algorithms, and creative strategy starts inside those three walls.
53% Say It Is Harder Than It Was Two Years Ago
If platform growth tells one story, practitioner sentiment tells another.
More than half — 53% — of PPC professionals surveyed say that managing paid search and paid media campaigns is harder today than it was two years ago. Only 16% report finding it easier. The remaining 31% say it is roughly the same.
This data point is particularly significant because the 2024 version of the same survey showed rising difficulty as well. The percentage of individual contributors (as opposed to managers or executives) who say the job is getting harder is the highest across all experience and role levels. Senior practitioners and executives are more likely to report stability, partly because their work is increasingly strategic rather than hands-on inside the ad interfaces.
What is making PPC harder? The report asks that question directly. The top answers are:
Black-box platform technology — cited by 65% of those who say the work is getting harder. This refers to the increasing opacity inside automated systems like Performance Max, broad match keywords with AI-driven expansion, and automated bidding strategies that make decisions without surfacing their logic. Practitioners are expected to trust outcomes they cannot fully audit.
Signal loss due to privacy changes — cited by 50%. The deprecation of third-party cookies, tightening regulations across the EU and California, Apple’s App Tracking Transparency framework, and the phaseout of cross-platform tracking have all degraded the data signals that once powered precise targeting and reliable attribution.
Increased competition — cited by 43%. As more advertisers shift budget from traditional channels to paid digital, auction density increases, CPCs rise, and the cost of being competitive in any given keyword vertical goes up.
These are structural challenges. They are not going away. The platforms are not going to suddenly become transparent, data privacy laws are not going to loosen, and competition for digital attention is not going to decrease. The practitioners who are finding ways to manage within these constraints — through first-party data, strong creative testing, and operational efficiency — are the ones reporting greater stability.
AI in PPC: What Professionals Are Actually Doing (and What They Are Not)
The narrative around AI and PPC has been running ahead of reality for two years. The State of PPC 2026 report corrects that gap with specifics.
AI dropped from the #1 practitioner priority in 2024 to #3 in 2026. Only 43% of respondents list AI-related goals as a top priority. By contrast, 68% name “improving campaign efficiency and profitability” as their #1 priority, and 59% prioritize generating more conversions and leads. AI is a tool in service of these goals, not the goal itself — and the profession has apparently recognized that distinction.
ChatGPT remains the dominant large language model among PPC professionals, used by 59% for ad copy tasks, 39% for keyword research, and 34% for script writing. Gemini and Claude trail ChatGPT in adoption, though both are growing. Notably, 66% of PPC specialists now use LLMs as a primary resource for solving challenges and troubleshooting — second only to traditional web search.
The time savings from AI are real but modest. Most practitioners — across both agency and in-house teams — report saving one to five hours per week through AI-assisted workflows. Agency teams managing more than $1 million per month have become 20% more efficient compared to two years ago, measured by team size relative to spend managed. That efficiency is largely attributed to automation of repetitive tasks like reporting, feed management, and copy iteration.
“Vibe coding” — the practice of using AI tools to build custom no-code or low-code applications without traditional software engineering — has reached 22% adoption among PPC professionals. This includes building custom dashboards, automated alert systems, budget trackers, and reporting tools. The average Google Ads account now has 5.4 scripts running simultaneously, which is a meaningful increase from previous years and reflects a broader push toward custom automation.
Yet there are clear ceilings. AI agents — autonomous systems capable of executing multi-step workflows without continuous human input — have been adopted by only 21% of practitioners overall, rising to 28% among those managing accounts above $3 million per month. The barriers are not primarily technical. They are quality and accuracy concerns, cited by 58% of respondents, followed by reliability and trust, cited by 43%. Practitioners want AI to handle more, but they have had enough bad outputs to be cautious about how much autonomy they extend.
One data point that should give industry observers pause: 50% of respondents still track budgets manually using Google Sheets or Excel. In an industry managing hundreds of millions of dollars per month, half the market is using spreadsheets as their primary budget management tool. This is not a criticism — it reflects both the flexibility of those tools and the absence of a platform-native solution that practitioners find sufficient. But it also indicates a significant gap in operational infrastructure that no amount of AI-generated ad copy can fill.
The expert community around the report frames the AI shift in measured terms. Frederick Vallaeys, one of the original Google AdWords engineers and a longtime practitioner, offered a perspective widely shared in the report’s commentary: “AI won’t replace you. But someone who knows how to use AI better than you might.” That framing — AI as a competitive differentiator between practitioners, rather than a replacement for practitioners — reflects the consensus position in the field as of 2026.
Platform Adoption and Satisfaction: Where the Money Goes and Why
Platform adoption data in the report is based on what respondents actually use, not what they think they should use. The numbers are instructive.
Google Ads holds near-universal adoption at 98%. This figure has been stable for years and is unlikely to change meaningfully in the near term — Google Search is still the dominant intent-capture mechanism in digital advertising, and no credible alternative has emerged.
Meta (Facebook and Instagram advertising) is used by 84% of respondents — a figure that remains high despite persistent complaints about data quality, audience accuracy post-iOS 14.5, and diminishing returns in certain verticals. Meta’s advertising system has adapted to privacy constraints faster than many expected, and its conversion modeling has proven sufficiently reliable for most direct-response advertisers.
Microsoft Advertising (Bing) is used by 60% — a number that has been more stable than Microsoft’s overall search market share would suggest, largely because the demographics of Bing users over-index for B2B decision-makers and higher-income consumers in certain categories.
YouTube comes in at 59%, with Connected TV and OTT placements reaching 14% adoption. The Connected TV figure is worth watching — it represents a category that barely registered in previous surveys and is now entering the mainstream conversation for performance-focused video buyers.
TikTok adoption has climbed steadily, driven by its ad revenue growth rate even as regulatory uncertainty in some markets has created hesitation among larger advertisers. Reddit, with its 60% CAGR, has moved from an experimental channel to a legitimate line item in diversified media plans, particularly for B2B and community-driven consumer categories.
Looking at planned budget changes for 2026: 43% of advertisers plan to increase spending on Performance Max, and 31% plan to increase Meta budgets. On the negative side, more than 25% of advertisers plan to cut spending on both X (Twitter) and Snapchat — two platforms that have struggled to articulate a clear value proposition for performance-focused advertisers.
Performance Max: Widely Used, Widely Questioned
No single campaign type has generated more discussion — or more frustration — in the PPC industry than Performance Max. The data confirms both the adoption and the tension.
50% of respondents use Performance Max often or always. That is a majority adoption rate for a campaign type that did not exist until 2021. By any measure of platform rollout success, that number represents Google achieving significant uptake in a short period.
But the satisfaction data tells a different story. The top three frustrations among PMax users are:
Black-box targeting, cited by 56% — meaning practitioners cannot see which audience segments, placements, or creative combinations are driving results within a PMax campaign. The system optimizes toward a conversion goal but does not surface enough of its decision logic to allow meaningful human intervention.
Opaque attribution, cited by 41% — meaning the campaign’s reported conversion numbers cannot be reliably connected to the specific inputs (search terms, audiences, assets) that drove them. This makes it difficult to iterate intelligently or to defend PMax spend to stakeholders who want accountability.
Cannibalization of existing search campaigns, cited by 32% — a concern that PMax siphons traffic from existing brand campaigns and exact-match keywords, inflating reported conversions while actually poaching traffic that would have converted anyway at lower cost.
Standard Shopping campaigns, which many expected PMax to fully replace, have shown surprising resilience at 38% regular usage. This persistence is partly practical — feed-only PMax (without creative assets) functions similarly to Standard Shopping for many e-commerce advertisers — and partly a preference for the greater control and transparency that Standard Shopping offers despite its older architecture.
In terms of keyword targeting, exact match remains the most used option at 78% and simultaneously has the highest satisfaction rate at 77% — by a significant margin over phrase match and broad match. Despite Google’s years-long push to encourage broad match adoption through improved AI matching, practitioners who have run comparative tests continue to return to exact match as their most trusted, most legible, and most controllable targeting method.
The expert commentary in the report is direct about PMax. Ed Leake, a seasoned PPC practitioner and industry commentator, noted that the core issue is that “control has reduced, visibility has reduced” — a sentiment that 53% of the industry appears to share when they report that the work is getting harder.
The Agency Model Under Pressure
The relationship between PPC agencies and their clients is shifting at a pace that is generating real anxiety on both sides of that relationship.
The most significant data point: 73% of in-house marketing teams now say they are committed to keeping PPC management fully internal — up from 44% just two years ago. That 29-percentage-point increase in two years is not a trend. It is a structural reorientation.
Several forces are driving this. First, AI tools have lowered the skill and time requirements for campaign management to a degree that makes pure outsourcing harder to justify on cost grounds. Second, first-party data — increasingly the most valuable input in any campaign — lives inside the advertiser’s own systems. Agencies that cannot access, enrich, or activate that data are at a structural disadvantage. Third, the scrutiny on agency fees has intensified as CFOs look more closely at marketing spend efficiency.
The report quantifies a specific agency revenue challenge: agencies using billable hours as their pricing model lose revenue as AI makes their teams more efficient. As Wijnand Meijer, a respected figure in the European PPC community, observed in the report’s commentary: “You’ve just given yourself a 20% pay cut for getting better at your job.” That is a pricing model problem that the industry has not solved, and it is creating pressure on agency margins even as productivity improves.
20% of clients say they are actively considering replacing some portion of agency work with AI tools — not switching to a different agency, but substituting agency work with automated systems. This figure has risen sharply and is likely to continue rising as AI platforms mature.
The agencies that are adapting are those repositioning from execution-focused services toward strategic advisory roles — managing the logic of campaigns rather than the mechanics, advising on data infrastructure, and building proprietary automation tooling. The agencies most at risk are those still competing primarily on execution speed and platform certification.
On pricing structure, 25% of European agencies still bill by the hour, compared to only 12% of North American agencies. North American agencies have adopted performance-based, retainer, and percentage-of-spend models at higher rates — a structural difference that may partly explain why the in-housing trend is somewhat less pronounced in that market.
Measurement: The Problem That Ties Everything Together
Attribution, measurement, and data accuracy are not just tactical concerns in the State of PPC 2026 report. They surface as the underlying issue connecting most of the other major challenges.
53% of practitioners who say PPC is getting harder specifically cite less accurate measurement as a primary driver. Privacy changes — including the ongoing deprecation of third-party tracking, iOS tracking restrictions, and the gradual implementation of Google’s Privacy Sandbox — have degraded the data signals that attribution models depend on.
The result is a measurement environment where the numbers in ad platform dashboards are increasingly modeled rather than measured. Conversion modeling, enhanced conversions, and server-side tagging are all legitimate responses to signal loss, but they require technical implementation that many advertisers have not yet completed. Until first-party data infrastructure is properly configured, the gap between reported performance and actual performance remains significant.
Reporting tools in this environment show interesting patterns. Looker Studio and Google Sheets are tied at 51% each as primary reporting solutions. More advanced business intelligence platforms — Power BI, Tableau, and others — are used by a minority of teams, largely those with larger budgets and dedicated analytics resources.
Competitive intelligence is another area where the data reveals practical gaps. Semrush leads among paid competitive analysis tools, used by more than 40% of those using paid solutions. But a significant portion of practitioners rely on free tools or platform-native insights, which offer limited competitive visibility.
Click fraud remains an underaddressed risk. 71% of respondents report using no dedicated click fraud prevention software. For campaigns running in competitive verticals with high CPCs, this represents a meaningful exposure — fraudulent clicks consuming budget without conversion potential. The low adoption of prevention tools does not mean fraud is not happening. It means it is mostly going unmeasured.
Hiring, Team Size, and the Efficiency Question
The data on PPC teams and hiring reflects a labor market in transition, though not the dramatic disruption some observers predicted.
Finding PPC talent remains the single biggest operational challenge for both agencies and in-house teams. 9 in 10 in-house teams report difficulty finding qualified candidates — a figure that has not improved meaningfully year over year despite the proliferation of training resources, certifications, and online learning platforms.
The reason may be structural. The skills required for modern PPC management have changed substantially. Running Google Ads in 2026 requires proficiency in data analysis, first-party data activation, creative testing strategy, attribution modeling, and increasingly, prompt engineering and script writing. This is a different profile from the keyword-bidding specialist of five years ago, and the candidate pool has not fully replenished to match it.
27% of practitioners believe AI will negatively affect PPC hiring over the next 12 months, meaning fewer roles will be filled because automation is absorbing some of the work. The majority — 46% — remain neutral on this question, neither expecting significant job losses nor job growth as a direct result of AI. The dominant view is that team composition will change before team size changes dramatically.
In-house teams remain compact: 88% of in-house PPC teams have five or fewer people, while 50% of agency teams have six or more. Agency teams managing above $1 million per month monthly ad spend have become 20% more efficient over two years — meaning they are managing more spend with the same or smaller headcount. This efficiency gain is real, but it has not yet translated into reduced pricing for clients or materially reduced workloads per practitioner. It has largely been absorbed into agency profitability.
Retention is a concern, particularly at the individual contributor level. Only 17% of individual contributors expect to remain in their current role for five or more years. Executive and senior-level practitioners show far stronger retention intent at 62% expecting to stay five or more years. This gap creates knowledge transfer risks for agencies whose institutional expertise lives in senior staff while campaign execution depends on a rotating pool of junior talent.
What PPC Professionals Are Prioritizing in 2026
When respondents named their top three priorities for 2026, the rankings provided a clear picture of where the profession is placing its energy.
Improving campaign efficiency and profitability is the top priority at 68%. This is a response to the pressure on budgets, the rising cost of competition, and the need to demonstrate clear ROI in environments where CFO scrutiny of marketing spend has intensified.
Generating more conversions and leads comes second at 59%, which reflects the enduring primacy of performance-based goals in paid search. Despite all the changes in platforms, measurement, and AI tooling, the fundamental brief — deliver more customers at a sustainable cost — has not changed.
AI adoption ranks third at 43% — significant, but having dropped from first place in the previous year’s survey. The shift suggests the industry has moved from an exploratory phase (where AI was new, exciting, and the focus of attention) to an integration phase (where AI is a tool being woven into existing workflows toward existing goals).
Beyond the top three: first-party data strategy, creative testing and optimization, and audience targeting refinement all rank prominently, reflecting the measurement challenges discussed above and the growing importance of owned data as third-party signals continue to erode.
Platform Scores: Exact Match Wins, Automation Has Trust Issues
The report also asked practitioners to evaluate specific ad platform features. The results offer a granular view of what tools practitioners actually trust and use.
Exact match keywords earned both the highest usage rate (78%) and the highest satisfaction score (77%) of any targeting option. This is notable because Google has spent years reducing the precision of exact match (officially, exact match now allows “close variants”) and has promoted broad match as the AI-powered future of keyword targeting. Practitioners have observed the results of both approaches and continue to prefer the more controlled option by a significant margin.
Broad match shows lower satisfaction despite Google’s encouragement. The disconnect between platform recommendation and practitioner preference on this topic has persisted for several years and shows no sign of resolving.
Scripts usage has grown to a median of 5.4 scripts per account. Common uses include automated budget pacing, bid adjustment rules, quality score monitoring, and custom anomaly detection. The growth in scripts reflects practitioners building the transparency and control layer that automated platform features do not provide natively.
Looker Studio and Google Sheets share first place as reporting tools at 51% each — a combination that tells its own story about the state of PPC infrastructure. The majority of the industry is either building reports in a free Google product or using a spreadsheet. This is functional but fragile, and it represents an opportunity for better tooling.
Detailed FAQ: The State of PPC in 2026
Q: What is the State of PPC 2026 Global Report?
The State of PPC 2026 Global Report is the largest survey of paid media professionals ever published, drawing on responses from 1,306 PPC practitioners across North America, Europe, the UK, and other regions. It covers platform adoption, AI usage, budget trends, team structures, measurement practices, and practitioner sentiment. The data is sourced directly from professionals managing real budgets and real campaigns across a range of industries and company types.
Q: How much is the global PPC market worth in 2026?
Global digital advertising expenditure surpassed $1 trillion in 2025 for the first time. Within that, the global PPC market is projected at approximately $218.3 billion in 2026, growing at roughly 8.5% annually. Google alone accounts for $225 billion in search advertising revenue, representing 94% of global search ad spend. The Big Three — Google, Meta, and Amazon — collectively capture 89% of all global digital ad spend.
Q: Is PPC getting harder or easier in 2026?
According to the report, 53% of PPC professionals say their work is harder today than it was two years ago. Only 16% say it has gotten easier. The primary drivers of increased difficulty are black-box platform automation (cited by 65%), less accurate measurement due to privacy changes (50%), and increased competition (43%). Individual contributors report greater difficulty than senior practitioners or executives, who are more insulated from day-to-day platform friction.
Q: Has AI replaced PPC professionals?
No. The data does not support the narrative of widespread AI-driven job displacement in PPC. While 27% of respondents believe AI will negatively affect hiring over the next 12 months, 46% are neutral and a small minority report any personal job security concern. AI is currently functioning as a productivity tool — saving most practitioners one to five hours per week — rather than as a replacement for strategic judgment, creative direction, or account oversight. The consensus in the industry is that AI competency is becoming a differentiator between practitioners rather than a substitute for them.
Q: What AI tools are PPC professionals using in 2026?
ChatGPT is the most widely used large language model, applied by 59% of respondents for ad copy tasks, 39% for keyword research, and 34% for script writing. Gemini and Claude are also in use, with ChatGPT holding the lead across all company types. Beyond LLMs, 22% of practitioners have adopted “vibe coding” — using AI to build custom no-code tools — and the average account now runs 5.4 automated scripts. Only 21% use autonomous AI agents for campaign management, with quality and accuracy concerns cited as the primary barrier.
Q: What is Performance Max and how satisfied are advertisers with it?
Performance Max (PMax) is a Google Ads campaign type that uses machine learning to serve ads across all Google properties — Search, Display, YouTube, Gmail, Maps, and Discover — from a single campaign. It was introduced in 2021 and has reached 50% regular adoption among the survey respondents. Despite this adoption, satisfaction is mixed. The top frustrations are black-box targeting (56%), opaque attribution (41%), and cannibalization of existing search keywords (32%). Standard Shopping campaigns have remained in use by 38% of respondents, suggesting that many advertisers have not fully transitioned even after several years of Google encouraging PMax adoption.
Q: Why are in-house teams bringing PPC management in-house?
The share of in-house teams committed to keeping PPC fully internal has jumped from 44% two years ago to 73% today. Several factors are driving this shift. AI tools have lowered the skill barrier for campaign management, making it easier for smaller in-house teams to handle more. First-party data — increasingly the most valuable advertising input — lives inside the advertiser’s systems, giving in-house teams a structural data advantage. Additionally, greater budget scrutiny has prompted cost comparisons between agency fees and internal resource costs that increasingly favor the latter for certain account types.
Q: What is happening to the agency model in PPC?
The agency model is facing genuine pressure from multiple directions simultaneously. In-housing rates have risen sharply, from 44% to 73% among in-house teams in two years. 20% of clients report considering replacing some agency work with AI tools. Agencies using billable-hour pricing face a structural problem: as AI makes their teams more efficient, they earn less per unit of work delivered. The agencies most likely to retain clients and revenue are those transitioning toward strategic advisory roles — managing first-party data strategy, automation architecture, and attribution modeling — rather than competing on execution volume.
Q: Which PPC platforms are growing fastest and which are declining?
By revenue CAGR from 2020 to 2025: TikTok leads at 74%, Reddit at 60%, Amazon at 28%, Meta at 18%, Google at 17%, and Microsoft at 9%. X (formerly Twitter) is the notable declining platform at -6% CAGR. In terms of advertiser spending intent for 2026, Performance Max and Meta show the highest planned budget increases, while X and Snapchat face planned cuts from more than 25% of advertisers.
Q: What does “black box” mean in PPC, and why is it a problem?
The term “black box” in PPC refers to automated platform features that optimize toward a goal without surfacing the inputs, logic, or decisions that produced the outcome. Performance Max is the most commonly cited example — it serves ads across multiple Google properties using machine learning, but does not reveal which placements, audiences, or creative combinations drove conversions. The problem is twofold: practitioners cannot iterate intelligently when they cannot see what is working, and they cannot defend spend decisions to stakeholders when they cannot attribute results to specific inputs. Black-box technology is cited by 65% of those who say PPC is getting harder as a primary cause.
Q: What measurement challenges are PPC practitioners facing in 2026?
The primary measurement challenge is signal loss driven by privacy changes — iOS tracking restrictions, third-party cookie deprecation, and the evolving Privacy Sandbox framework. These changes have degraded the data inputs that attribution models depend on, making reported conversion numbers increasingly modeled rather than directly measured. Enhanced conversions, server-side tagging, and first-party data enrichment are the leading responses, but implementation gaps are widespread. 50% of practitioners still track budgets manually in Google Sheets or Excel, and only 21% use AI agents that could automate reporting and anomaly detection.
Q: How do PPC teams handle competitive intelligence?
Semrush leads the paid competitive intelligence category, used by more than 40% of those using paid solutions. A significant share of practitioners rely on free tools or platform-native data, which provides limited competitive visibility. Competitive intelligence spending tends to increase with account size and is more common among agency teams than in-house teams, which often have fewer dedicated tools in their stack.
Q: What is “vibe coding” and why are PPC professionals doing it?
Vibe coding is the practice of using AI tools — typically large language models like ChatGPT — to generate functional code or applications without traditional programming expertise. In a PPC context, this means building custom budget trackers, automated alert systems, reporting dashboards, and data transformation tools without needing to hire a developer. 22% of PPC professionals reported adopting this practice, and the trend is accelerating as LLMs improve at code generation. It represents a significant expansion of the practical toolkit available to practitioners who are not software engineers.
Q: Are click fraud prevention tools being used?
Not widely. 71% of respondents do not use any dedicated click fraud prevention software. This is notable given how significant invalid traffic can be in competitive, high-CPC verticals. The low adoption likely reflects a combination of factors: many advertisers rely on Google’s built-in invalid click filtering, click fraud prevention tools add cost, and the impact can be difficult to quantify until a formal audit is conducted. For advertisers in sectors with known fraud exposure — legal, financial services, home services — this represents a meaningful gap in campaign protection.
Q: What are the top PPC priorities for 2026?
The top three practitioner priorities for 2026 are: improving campaign efficiency and profitability (68%), generating more conversions and leads (59%), and AI adoption (43%). AI dropped from the #1 priority it held in 2024 surveys to third place, reflecting a maturation of expectations. Below the top three, first-party data strategy, creative optimization, and audience refinement are widely cited as operational focuses.
Q: How are PPC professionals using LLMs beyond just content generation?
Beyond ad copy (59%) and keyword research (39%), LLMs are being used for email drafting (39%), script writing (34%), troubleshooting campaign issues (66% use LLMs as a primary problem-solving resource), and building custom automation tools via vibe coding (22%). The practical use of LLMs for technical problem-solving — debugging Google Ads scripts, interpreting API documentation, analyzing campaign data — has grown substantially and is perhaps the less-publicized but more transformative shift in how the profession operates day-to-day.
Q: What does the data say about PPC budget management practices?
Budget management practice in PPC remains surprisingly manual. 50% of practitioners report using Google Sheets or Excel as their primary budget tracking method. Dedicated budget management tools and platform-native pacing features are used by a minority. This gap is partly a product of inadequate native platform tooling and partly institutional inertia — spreadsheets are flexible, customizable, and universally understood. However, as account complexity increases and multi-platform budgets become the norm, manual tracking creates a growing risk of allocation errors and missed optimization opportunities.
The Road Ahead for Paid Media
The State of PPC 2026 Global Report does not describe a profession in crisis. It describes a profession in sustained adaptation. The $1 trillion global ad market is real, the demand for skilled campaign management is real, and the performance gap between sophisticated advertisers and average ones is arguably wider than it has ever been. Practitioners who understand attribution well enough to defend it, who use first-party data effectively enough to outperform platform defaults, and who can build or deploy automation intelligently enough to manage complexity without losing control — those practitioners have more leverage in 2026 than their counterparts had five years ago.
The platforms are not going to become more transparent. The privacy constraints are not going to loosen. Competition is not going to decrease. What can change is the capability and strategy of the teams running inside those conditions. The data in this report points consistently in the same direction: the gap between the median outcome and the best achievable outcome in paid search is determined by decisions made before, around, and after the campaign — in data infrastructure, measurement architecture, team capability, and strategic prioritization — not primarily by which buttons get clicked inside the ad interface.
The agencies and in-house teams that understand this are already repositioning. The ones that have not started that repositioning are the ones at greatest risk from the trends this report documents.
About ALM Corp
ALM Corp is a full-service digital marketing agency that has generated over $7 billion in client sales and launched more than 5,700 websites across a global client base. The data documented in the State of PPC 2026 report sits at the center of what ALM Corp does every day — managing paid media and performance marketing campaigns that translate ad spend into measurable revenue.
As the PPC landscape consolidates around Google, Meta, and Amazon, and as platform automation pushes more optimization decisions into black-box systems, ALM Corp’s approach is deliberately anchored in the practices the 2026 data identifies as high-impact: first-party data strategy, rigorous measurement and attribution modeling, creative testing at scale, and the kind of strategic oversight that automated bidding cannot provide. The firm’s Data and Analytics Solutions practice is specifically built to close the measurement gaps that 53% of practitioners in this report identify as a primary difficulty — converting modeled platform data into decisions that hold up to CFO scrutiny.
For businesses navigating the shift toward AI-driven campaign management, increasing competitive density on Google and Meta, and the growing pressure to demonstrate clear return on ad spend, ALM Corp offers both the strategic and the technical capabilities to close the gap between what platforms report and what is actually working. Whether the challenge is maximizing Performance Max with the right asset mix and conversion data, building the first-party data infrastructure that outperforms third-party targeting, or transitioning from manual budget tracking to automated pacing at scale — these are the problems ALM Corp solves for its clients every day.
To explore how ALM Corp’s paid media practice can improve your campaign efficiency and profitability — the #1 priority in the State of PPC 2026 — visit almcorp.com.
