Influencer Marketing Forecast 2026

Key Findings

AI becomes the end-to-end operating system for influencer marketing.

83% of experts expect AI to power the full workflow—discovery, brief-writing, content generation, optimization, creator selection and performance forecasting—turning influencer operations into an automated, test-learn loop.

Human credibility outperforms AI Influencers.

39% say real creators will beat AI influencers as trust becomes the deciding variable. As synthetic content floods feeds, lived experience, proof of use and credible voices drive conversion.

Budget growth arrives with hard-outcome governance.

28% predict larger influencer budgets will be paired with procurement scrutiny, performance guardrails and ROI targets. Fees, scopes and renewals hinge on sales, sign-ups and brand-lift, not vanity metrics.

Radical transparency becomes non-negotiable.

24% see disclosure, product truth and values alignment as table stakes. Clear rights, usage and licensing terms move from “nice to have” to mandatory for brand safety and renewals.

Post-TikTok risk management drives channel diversification.

21% expect spend to rebalance across YouTube, Instagram, retail media and CTV to hedge platform and regulatory risk while protecting reach, searchability and commerce.

Fewer, deeper, longer partnerships compound results.

20% believe brands will shift from one-offs to ambassadorships. Always-on creator layers build memory, lower effective CPLs and produce stronger multi-touch attribution over time.

Creator assets become the core of 360° omni-channel execution.

18% expect creator content to be repurposed systematically into paid social, retail media, CRM, landing pages, TV/CTV, OOH and events, creating one consistent story across the funnel.

Featured Expert Contributors

Most Referenced Influencer Marketing Predictions

Most Referenced Influencer Marketing Predictions
Think these predictions as a collective map of that future: not “trends” in a deck, but the 17 pressure points where AI, creators, and brands are quietly renegotiating what marketing even is, and where getting it wrong doesn’t just cost you a campaign, it costs you your relevance in the market.

1. AI will become the end-to-end operating system for influencer marketing
   AI will power every stage of the workflow – from discovery and brief-writing to content production, optimization, creator selection, and performance forecasting.

2. Authentic human creators will consistently outperform synthetic and AI influencers
   As AI content and avatars proliferate, audiences and brands will default to real people with lived experience and credibility. AI influencers will remain mostly experimental and niche.

3. Lo-fi, native, niche, community-centric creator content will beat polished brand ads
   Native, UGC-style content from hyper-relevant niche creators with tight communities will outperform glossy brand productions and broad, shallow reach.

4. Brands will prioritise fewer, deeper, long-term creator relationships
   Attention fragmentation and rising noise will push brands to build ambassadorships and always-on partnerships instead of one-off campaigns with large rosters.

5. Creators will act as full-funnel partners, from discovery to support
   Influencers will not only drive awareness and conversion, but also handle onboarding, tutorials, education, and ongoing Q&A as trusted voices across the customer journey.

6. Creator content will become the core asset for 360, omni-channel marketing
   Creator assets will be systematically repurposed into paid ads, CRM, landing pages, TV, OOH, events, and internal content as standard practice.

7. Creators will be embedded into brand teams and product development
   Social and influencer functions will converge, with creators hired in-house or tightly embedded, contributing to product and campaign design—not just last-mile promotion.

8. Influencer budgets will grow under strict performance and procurement scrutiny
   Overall investment in influencer marketing will increase, but every deal will be judged on hard outcomes like sales, sign-ups, and brand lift rather than vanity metrics.

9. Shared-upside deal structures will become the norm
   Flat fees will increasingly be paired with affiliate and revenue-share models, plus more equity, royalties, and licensing structures, especially for high-value creators and co-branded products.

10. Social and AI search will redefine how people discover products and creators
    Platforms like TikTok and AI-driven search will act as primary discovery layers, forcing brands to design creator content that is searchable—not just optimised for feeds.

11. Brands will diversify beyond TikTok to manage platform and regulatory risk
    Even as TikTok remains central—especially as a “search engine” for younger users—brands will spread spend across more stable and emerging platforms as bans and regulation loom.

12. Global and emerging-market creator economies will scale rapidly
    Cross-border campaigns will normalise, with fast-growing regions and new creator markets attracting disproportionate global brand spend as infrastructure matures.

13. Influencer marketing will mature into a governed, professional discipline
    Stricter regulation, clearer disclosure rules, and growth in regulated sectors like finance and health will drive more robust governance, frameworks, and senior ownership.

14. B2B influencer marketing will gain serious traction and sophistication
    Subject-matter experts on LinkedIn and niche platforms will drive thought leadership, demand generation, and trust in complex B2B buying journeys.

15. Live commerce in Western markets will only scale where real operational skills exist
    To make live shopping perform, Western brands and creators will need dedicated playbooks, training, and systems—live commerce won’t work as a one-off “test campaign.”

16. Creator-led brands and products will multiply
    More creators will launch their own brands, collaborations, and product lines, shifting from pure sponsorship to ownership and long-term value creation.

17. Authenticity and transparency will be non-negotiable in brand–creator partnerships
    Values alignment, real product usage, and clear disclosure will be critical to trust, influencing which creators brands choose and how partnerships are structured.

Social SEO: New Performance Layer of Influencer Marketing

For a growing share of Millennials and Gen Z, the first step in buying is no longer “Google it”, it’s “check TikTok”, “search on Instagram”, or “see what YouTube says”. Product discovery is migrating from traditional search engines to social platforms that feel more human, more visual, and more embedded in everyday life.

Search is still huge, but it’s no longer “Google-only”.

35% of consumers discover new products via social.

86% of Gen Z use TikTok search weekly – up 40% year-on-year.

2.5x faster growing - Gen Z social search is growing faster than AI search (48% vs 19%).

Social platforms are quietly becoming search engines that better match the informational needs of younger consumers:

Social Proof as the Search Requirement
People want to see what people like them think, use, and recommend.

Lived Evidence, Not Blue Links
They deliver visual, in-context proof: before vs after, unboxings and reviews compress pages of search results into one lived example.

From Scroll to Checkout in One Flow
You now can have an closed loop commerce experience from search to checkout within social media apps.

In this environment, influencer content is no longer a “nice-to-have” brand asset – it becomes discovery infrastructure. Social SEO is the performance discipline behind it: architecting creator and UGC assets (hooks, formats, metadata, captions) so they capture high-intent demand on social search surfaces like TikTok, Instagram and YouTube, the same way classic SEO did on Google.

Social Algorithms Now Rank Intent, Not Followers

“What you used to have was who you followed, was who you saw… Now, if I follow an influencer that posts about travel, I’m going to see more content about travel… more interest-led content rather than people-led content.”

Mark Dandy, Strategic Consultant, Influencer Marketing

Mark’s description points to a clear structural shift in how social platforms work.
Algorithms are now optimised around intent signals – watch time, searches, saves, clicks – rather than simply who follows whom.
Audience behaviour is moving from passive feed scrolling to active social search, especially on TikTok. People don’t just wait for content to appear; they type queries and expect answers.
Internally, he estimates that around 15% of all product discovery now happens on TikTok – and that share is rising as users start their journey in-app instead of defaulting to Google.
Data from Dreaminfluence makes this concrete: over the last 12 months, roughly half of their traffic has come from TikTok Search and only a small fraction from followers, a strong signal that in this environment, discoverability and intent-fit beat follower count.

Across platforms, Mikkel’s doctrine is blunt:

Discovery beats follower count.
It’s search-driven distribution, not static audience size, that determines reach.

Algorithms reward relevance and intent-fit.
Watch time, format and how well a post answers a real query matter more than vanity metrics.

Small, sharp creators often win.
Micro-creators with well-designed, searchable content consistently outperform larger accounts running weak formats.

Social SEO Is Rewriting Influencer Economics

As discovery shifts from feeds to search, the optimal “influencer mix” changes with it.
Instead of putting most of the budget into 5–10 macro creators, brands that want to win in Social SEO will need portfolios of 50–100 niche creators around a category.

The logic is simple: each creator gives you another indexed asset against a different “best X for Y” query, use case, or language variant. One strategist we spoke to expects this volume-based model to become the default for brands that want to shape social search results rather than just rent one-off reach.

At the same time, influencer content stops being a “campaign add-on” and becomes a multi-channel discovery asset. As TikTok and Instagram content starts to rank in social search, and Instagram posts are indexed into Google results, a single creator video can now: show up in TikTok search, live in Reels, be promoted as paid, and appear in web SERPs months later. That pushes brands to treat creator output as part of the core media mix, supporting TV, OOH, retail and marketplace strategies, rather than as a separate, purely “social” line item.

“Instagram posts are now showing up on Google Search… Influencer posts can now: appear in organic search results, reach people outside social feeds, boost brand visibility long after the post goes live… The line between SEO and influencer marketing is starting to blur. And honestly, I love it.”

Mikkel Malesa, Founder & CCO, Dreaminfluence

How leading brands are operationalizing Social SEO

The most advanced teams treat Social SEO as a design problem across briefs, content formats and operations – not as a hashtag trick.

Search-informed briefing

Social SEO starts with demand, not campaign ideas. First, mine real behaviour: use TikTok Studio / Creator Tools and IG insights to see “how viewers found you”, which keywords you’re discovered by, and which videos keep compounding views. Treat comment sections as live keyword research – every repeated question, objection or “is X worth it?” becomes a new piece of content. Then layer classic SEO and market tools on top: TikTok Creative Center for trending phrases, Google Keyword Planner / SEMrush and social listening to see high-intent queries and the language people actually use. Recycle your historic SEO winners too; what people search for hasn’t changed, only where they search.

Cluster those queries by intent (“best X for Y”, “how to…”, reviews, itineraries) and map them to native formats: unboxings, comparisons, timelines, “5 things to know”, honest walkthroughs. Build a creator pyramid where a few authority profiles anchor key terms and a wide base of nano/micros gives you volume, localisation and long-tail coverage. Finally, turn queries into briefs: hook = the search, body = the answer, with long-tail phrases baked into hook, captions and on-screen text, without killing the creator’s own voice.

Designing for search-native formats

“We look at things in terms of what might get ranked on social search or even AI search… and we’ll use that within the prompts of the brief: think about this unboxing or ‘five things to do X’… People love a comparison and review and unboxing… or a timeline… initial reaction, then what they think a week later.”

Joe Adsett, Managing Director UK & US, Refluenced

High-performing Social SEO programmes standardise a small set of search-native building blocks:

These formats map cleanly to how users search and evaluate – and how algorithms detect and categorise intent.

Treating creators as distributed, human search results

“Why do brands still require a minimum follower count when choosing influencers? I see creators with 3,000 followers reaching more people than profiles with 50,000… because their content is more discoverable.”

Mikkel Malesa, Founder & CCO, Dreaminfluence

Reposts on Instagram mean: good content gets two lives… The creator’s original audience and brand-new audiences when reposted… The key question becomes: ‘Would someone share this?’”

Social SEO is not only about initial ranking – it’s about redistribution signals: reposts, saves, shares and stitches that give great content “two lives” and compound reach over time. Creators who naturally design for shareability become force multipliers in this system.

Using AI to scale the boring, not replace the human

“We’re definitely going to use AI to better identify the right influencers and optimise campaigns… AI is going to help free agencies from a lot of hours… scouting, segmentation, reporting… but this allows more time for strategy, relationships, and creative thinking. You cannot just fully rely on AI for a full-fledged influencer campaign.”

Iñigo Rivero, Managing Director, House of Marketers

What winning organisations are deploying AI to

In 2026, Social SEO will be the line between influencer programmes that look busy and those that actually move revenue. As product discovery migrates into TikTok, Instagram and YouTube search, “buying reach and followers” becomes an increasingly expensive way to rent attention while algorithms reward relevance, intent-fit and creator content that answers real queries.
Brands that do not re-architect around search will see two things happen in parallel: CPMs continue to rise, and their share of visible answers in social and AI search quietly shrinks. Their competitors will be the ones appearing in “best X for Y” and “how to” results, shaping consideration long before a user ever touches their website.
The winners will treat influencer marketing as search infrastructure: they will brief from live demand signals, deploy scaled portfolios of micro-creators against specific query clusters, and use AI to scan creator pools, cluster content and close the loop between search behaviour and commercial outcomes. Those organisations will not just “do influencer”; they will own the new front door to their category.

Influencer marketing: The Next Primary Channel in B2B Marketing

B2B influencer marketing has crossed an inflection point. For most of the last decade, creators in B2B were a side bet, run next to “real” demand gen. In 2025, that changed. Across 260+ expert interviews, 170 surveys and multiple SaaS/AI case studies, a consistent pattern emerges: creator-led systems are becoming a primary growth layer, not a campaign tactic.

What the data shows

CMOs are all-in.

93% of B2B CMOs plan to increase creator / influencer investment; 75% of B2B marketers already work with creators in some form.

Always-on beats one-off.

58% of active B2B teams now run an always-on creator layer; 99% of those rate it effective, with mature programs reporting 420% ROI at 12 months.

Creator programs accelerate ARR.

Influencer-led SaaS firms (e.g. Gamma, Lovable, Cursor, Fyxer) add roughly $4.3M in new ARR per month, up to ~3x faster than peers relying on traditional PLG/performance alone.

Supply is underpriced.

Roughly 90% of B2B-relevant creators have never had a paid sponsorship. Demand is rising faster than pricing and market infrastructure, creating a short-term advantage for early movers.

From Funnels to Distributed Trust Networks

Our case studies point to a structural shift in B2B growth: from linear funnels to distributed trust networks – small constellations of founders, operators and specialists who shape the narrative in feeds, podcasts and communities long before a sales deck arrives.

“Our case studies point to a structural shift in B2B growth: from linear funnels to distributed trust networks – small constellations of founders, operators and specialists who shape the narrative in feeds, podcasts and communities long before a sales deck arrives.”

Alicia Teltz, Founder, The Hype Department

Practitioners describe the same pattern from different angles:

“It’s not about activating as many influencers as possible. It’s carefully identifying a small group who are genuinely relevant to your niche and can elevate awareness, consideration and trust with the exact buying audience you care about.”

Tom Augenthaler, B2B Influence Strategist

“With Salesforce, we picked a very specific group of influencers, then built a long-term programme around them. The relationship piece – involving them in events, tours, takeovers – was the most interesting part, and it’s exactly where the industry is heading now.”

Luke Brynley-Jones, Founder & CEO, OST

The takeaway: in high-growth B2B, the real unit of competition is no longer your product or ad account – it’s the network of credible humans who teach the market how to think.

Why the B2B Buying Environment Favors Creators

Today’s buyers don’t start with vendors – they start with people.
Decision-makers self-educate in networks, feeds and group chats long before they fill in a demo form.

• Around 70% report little or no early interaction with sales.

• Roughly 2 in 3 use creator or expert content during consideration, and almost 50% at the point of purchase.

• After seeing strong expert content, more than 80% say they are more open to outreach and more likely to shortlist a provider.

In other words, creator content now sits in the middle of the B2B learning loop: operators show their real stacks, workflows and results in public – and buying committees use that to validate who they should trust.

At the same time, B2B brands are under pressure to show more human faces, not just logos


“I think business creators, as B2B tries to become more human, need to adopt the same strategies that consumer brands have been in terms of talking to people.
 B2B marketing has been very lacklustre in the past. So suddenly they’re embracing the idea of working with creators. We’re seeing this big growth in business creators.”

Raf McDonell, Founder & Managing Director, Talent & Brands

Net effect: creator-led GTM doesn’t replace performance; it primes it. It puts your product into peer-driven discovery and discussion before your SDRs ever send an email.

High-Performing B2B Creator Systems

The highest-growth B2B teams we analyzed (e.g., Instantly.ai, Gamma, Modash) aren’t “doing influencer marketing”; they’re running a repeatable content-and-distribution machine that produces qualified demand. Four patterns show up consistently—and they’re simple enough to copy.

Format discipline beats “random thought leadership”

Outcome-first case studies

Headlines that carry the business result, not the backstory: e.g., “6,200 leads and $1.74M closed,” “102 opportunities from 4.6K sends.”

Contrarian POVs

Clear, teachable reframes that dismantle common assumptions: “Cold outbound doesn’t work anymore… here’s why it does if you change the system.”

System explainers

Short, concrete breakdowns of how the stack and workflow actually work “in the wild.”

Gamma is explicit about the method: go broad with many creators, test hard, then codify the 10% of formats that drive 90% of reach with training, bonuses and paid amplification. The takeaway: fewer formats, more iterations.

Long term, Always on, is winning.

“For decades, the best tech companies quietly ran sophisticated influencer programmes – think IBM and Microsoft. What’s new is a generation of AI-driven companies winning with always-on creator systems, often without huge budgets. The mistake is judging creators on one quarter and one announcement. If you stretch the time horizon to two years, always-on creators consistently outperform every other channel on ROI.”

Djanan Kasumovic, Co-founder, Influencer Strategists

Buyers see the same credible specialists, internal operators and a few external creators, week in, week out. In Instantly’s LinkedIn library, 65% of ads run as Thought Leader Ads from creator/employee handles.

Instantly Campaign Insights

The top five voices account for a disproportionate share of creator ads, teaching outcomes, workflows, and stacks repeatedly.

Always-On Creator Engines: How the Best Teams Actually Run Them

From one-off influencer bursts to relationship-driven creator systems that push buyers through the funnel.

“We’ve moved away from one-off influencer bursts. The programmes that work best are relationship-driven and always-on. We track them right through to conversion in CRM. Once you get micro-influencers running at scale, pulling people through the funnel, it becomes very effective.”

Luke Brynley-Jones, Founder & CEO, OST

Gamma applies the same logic at category level: 1,000+ creators, 31M+ organic views, one clear narrative repeated until it becomes the default mental model for “slides + AI”.

Start wide, then narrow.

Launch with many creator personas that map to different jobs-to-be-done, then double down on the ones that move pipeline.

Treat it like a real programme, not a test.

Commit meaningful budget and time (e.g. $10–20K/month for 6+ months) instead of “testing with crumbs”.

Let data, not politics, pick the winners.

Avoid over-selecting creators upfront; keep a broad pool and let performance decide who scales.

How to copy this in your own GTM

Map creator roles to buying jobs.

Define 6–10 creator archetypes (e.g. “slide design experts”, “ops hackers”, “meeting killers”) and, for each, outline audience (function, seniority, platforms) and the use-cases they already evangelise.

Standardise winning story formats.

For each archetype, pick 2–3 repeatable structures: “here’s my stack”, “live teardown”, “before/after result”, “demo + comparison”. Make these the default briefs.

Set simple scale rules.

Agree upfront on when to scale (e.g. cost per qualified lead, target in 7–10 days, or brand-lift proxy). When a creator crosses the line, move them from “test” to “always-on”.

How Top Teams Actually Use LinkedIn

A simple three-step system: test with creators, boost what works, then convert with events.

Creators and executives post from their own profiles to test talk tracks, demos and contrarian angles. The goal is to see what your buyers actually stop to watch, comment on and share.

Turn the best-performing posts into Thought Leader Ads from the creator’s own handle. You keep their face, voice and social proof – but add precise targeting into named accounts and ICP segments.

Use those same creators to host live sessions / AMAs / masterclasses that generate hand-raisers (MELs). Follow up with creator-framed emails and assets, so the journey feels consistent from ad to meeting.

“We run Thought Leader Ads from the creator’s handle, then look at influenced revenue: which companies saw impressions and are in our CRM, what’s the deal value. We don’t claim every deal ‘came from’ an ad – but those overlaps are a strong signal of where creator content is moving the market.”

Ryan Prior, Head of Marketing, Modash

B2B Creator Economics: Pricing Gaps and the 2026 Arbitrage Window

B2B creator work has moved past “experimental budget”. The money is real – but pricing, packaging and infrastructure are still immature, which creates a short-term advantage for operators who treat creators as part of GTM, not as one-off media buys.

No shared pricing language

There is still no clear grammar for “what a creator costs” across B2B. The same rate card is often used for small micro-creator activations and senior operators with C-suite reach. Fees for content, rights and distribution are frequently bundled into a single “price per post”, making it hard to compare value.

Good teams already price like media buyers

The more advanced programmes quietly run on internal CPM bands, by geo and sector. They separate:

• Creator fees (time, expertise, reputation)

• Production and ops

• Media, rights and reuse

This lets them benchmark creators against other channels instead of against generic B2C influencer rates.

On the supply side, the market is still under-monetised. The operators and experts who most shape B2B buying conversations on LinkedIn, podcasts and niche communities often have no sponsorship history at all. They sit on top of the demand, but pricing and contracts lag behind.

Three implications for 2026

Creator systems become core GTM, not garnish

In the fastest-growing SaaS and AI firms, creator-led loops now influence who enters the funnel, how qualified they are, and how quickly they move. Once measurement is wired into CRM, leadership stops asking “does B2B influencer work?” and starts asking “how many creator programmes can we afford to run?” Budget, org design and board-level attention follow.

The constraint is operating model, not belief

Most teams no longer need convincing – they need structure. The unlock is: a repeatable programme with clear formats, roles, contracts, rights, and measurement. When creators are run like a channel (with SLAs, learning cycles and owned IP), not like a string of campaigns, they start to look like an always-on demand engine rather than a nice-to-have brand layer.

There is a temporary arbitrage window

Demand for credible B2B creators is rising faster than pricing and market infrastructure. Today, brands can still:

• Lock in under-priced micro-experts on 6–12 month retainers

• Codify search- and community-driven formats together

• Wire revenue measurement into CRM before competitors do

As this professionalises, creator CPMs will converge with other high-intent media. The next 12–24 months are the window to build creator systems at a discount and let everyone else pay market rates later.

In that context, the real decision for leadership is precise:  will creator-led growth remain an occasional LinkedIn tactic, or will it be designed as a B2B Creator Operating System, complete with benchmarks, contracts, decision boards and a compounding library of human voices that move markets?

AI will significantly improve speed, scale and smarter decisions in influencer marketing

Across 267 predictions, AI is the single most mentioned force shaping influencer marketing. The consensus is clear: AI is not primarily about “AI influencers”. It is about compressing cycle times and raising the quality bar of every decision in the creator value chain.

So roughly one in two experts explicitly brings AI into their 2026 view. Across 267 expert predictions, one signal is impossible to ignore: AI is the single most referenced force reshaping influencer marketing. 136 respondents, just over half, mention AI explicitly. But what they describe is not a gimmick layer. It is a restructuring of how work gets done. The consensus is clear: AI is not primarily about “AI influencers”. It is about compressing cycle times and raising the quality bar of every decision in the creator value chain.

Where Experts See AI Shaping Influencer Marketing

Looking only at the 136 AI-related answers, the themes cluster as follows (with your “traction” bucket reframed into execution and scale):

71% answered they ran more campaigns, creators and test without linear headcount

59% Predictive selection, ROI, audience insight, sentiment, performance-driven optimisation

42% Joining siloed processes (discovery → briefing → approvals → reporting) into a connected flow

33% AI scripts, visuals, synthetic/virtual influencers, hyper-personalised content

35% Using AI to test formats, manage risk, refine portfolios, and govern complex programmes

The structural problem is an execution gap. Most organisations are still in AI exploration mode: pilots, tools, isolated experiments. The minority who are wiring AI into creator selection, content testing, optimisation and measurement are already competing on a different clock speed.

Over the next cycle, the divide will not simply be between brands that “use AI” and those that don’t. It will be between those who rebuild influencer and content workflows around AI for speed, scale and precision – and those still treating it as an add-on.

AI as the Speed & Scale Engine

The dominant pattern in your dataset: AI is how teams do more, faster – not how they replace humans.
Giovanni Spinelli ties it directly to day-to-day execution:

“I think a lot more technology through platforms like ours will develop a lot more AI tools to support the creators and really streamline the process for brands in terms of content approval, reporting, editing of content. I think AI is really going to facilitate and support our industry a lot as opposed to remove it completely.”

Karl Mapstone, Co-Founder & Head of Vamp Middle East

On the infrastructure side, Mike Newton is blunt about the structural impact:

AI becomes the speed layer of influencer marketing – the difference between teams that ship ten ideas a quarter and those that ship a hundred.

Automation as the End of Siloed Workflows

Our experts describe automation as connecting broken pipes.
Today’s reality in many programmes:

manual discovery → spreadsheet vetting → one-off briefs → email approvals → disconnected reports.
In our interviews, AI is consistently positioned as the glue that joins these steps:

Discovery & selection

“In 2026, the real breakaway advantage in influencer marketing will come from AI-driven, predictive influencer selection. Advanced data and AI will let brands systematically identify best-fit creators and engineer campaigns for hyper-relevant audience segments, instead of relying on guesswork and vanity metrics.”

Gordon Glenister, Co-founder, Influencer Strategists

Briefing & creative input

“We see a lot of time saving possible… we could leverage AI for efficiency, and at the same time leverage AI for the creativity – coming up with ideas for the campaign and for the brief, so influencers get more guidance when setting up an interesting campaign.”

Sherry Wu, Partner & Associate Director, Boston Consulting Group

What AI Automation will look like in 2026

Discovery, vetting, briefing, approvals and reporting start to behave like one connected workflow, not five separate projects.

Agencies and platforms that can join these steps coherently will out-execute those who keep them manual and siloed.

Automation, in this dataset, is not just about efficiency. It’s about building continuous, closed-loop processes instead of hand-offs between disconnected teams and tools.

AI Turns Measurement Into a Steering Wheel

The second-largest AI theme is measurement, data and performance: 79 of 136 AI answers (59%).
Here the shift is from “reporting what happened” to deciding what to do next.

AI-driven measurement, data and performance

AI will analyse behavioural data, sentiment and performance to predict which influencers will drive the highest ROI for specific campaigns.

AI-powered experimentation and data-driven creativity

AI tools enable rapid content iteration and A/B testing, driving a surge in data-driven creativity across the marketing ecosystem.

Continuous optimisation through AI personas

AI personas are continuously improved using real-time performance data so they stay aligned with audience preferences and brand objectives.

Jeremy Boissinot describes the goal for SaaS should be to give concrete answers with AI, instead of just churning out data

And Inigo Rivero joins measurement directly with selection and optimisation:

“We’re definitely going to use AI to better identify the right influencers and optimise campaigns… AI is going to help free agencies from a lot of hours of the day… scouting, segmentation, reporting.”

Iñigo Rivero, Managing Director, House of Marketers

AI-driven measurement for 2026

AI-driven measurement will decide which creators stay on the roster, which formats get scaled, and which markets deserve more budget.

Brands move away from one-dimensional “ER and CPM” thinking and toward multi-signal views: sentiment, audience quality, conversion, and pipeline impact.

A Clear Expert Consensus on AI

Putting the stats and quotes together, a Bain-style summary of your dataset would say:
This is less about shiny features, more about running larger, smarter programmes with the same or smaller teams. Measurement becomes predictive and allocative. AI is used to select creators, predict performance and steer budget, not just to tidy reports.

Experts see AI primarily as a speed, scale and integration engine

71% of AI mentions: faster execution & scalability

42% joining siloed workflows into connected processes

The practical stance for brands and agencies in 2026 looks like this:

• Treat AI as infrastructure and automation across the whole workflow, not just a content production engine.

• Use AI to speed up experimentation and scale (more creators, more markets, more tests) without losing control.

• Invest more, not less, in human creators, employees and customers as the faces of trust.

• Use AI-driven data to Use AI-driven data to decide which creators, formats and markets deserve long-term commitment.

• Experiment with AI influencers and synthetic media in contained, utility-driven roles, while keeping human credibility at the centre of the brand story.

AI Influencers Won’t Replace Humans

In 2024–2025, “AI influencers” became one of the noisiest topics in marketing discourse. Virtual models, synthetic brand ambassadors and AI‑generated creator content have all been hyped as the future of influencer marketing.

But when you look at what experienced practitioners actually say in our 2026 predictions dataset, a more restrained picture emerges.

Several experts explicitly push back on the idea that AI will replace human creators. Vito Strokov, former Global Director of Engineering at Snapchat , draws a parallel to over-confident self-driving car predictions:

“People keep asking: what about all those AI influencers? It’s like when Elon said we’d all be in full self-driving cars by 2020. Look at us – we’re still driving… The pace of innovation is huge, but as human beings, we’re not going anywhere. The biggest trend is not replacement, it’s leverage: AI empowering people who produce high-quality content to create work that really resonates.”


Vito Strokov, Co-founder, Halo AI

Humans still win trust, and that won't change. 

Experts consistently draw a line between AI as infrastructure and AI as the face of the brand.

Pierre Carssuto captures this dynamic clearly, pointing out that as AI saturates marketing, people will increasingly look to human influencers to cut through the noise:

"I think AI is gonna put us in a world where we're gonna be looking for content that is not AI. Meaning AI is gonna be helping us as interface with a lot of things, but we're not necessarily gonna trust AI's opinion on certain things”

— Pierre Cassuto, CMO, Humanz

Human authenticity becomes a premium in an AI-saturated feed

As content creation is increasingly AI-assisted, volume and baseline quality go up, but so does noise. Rafael Schwarz flags the inevitable counter-movement: as audiences become aware that much of what they see is machine-generated, verifiable human judgment and recommendation gain scarcity value. In other words, the more AI we get, the more premium “human” becomes. This aligns with our dataset’s broader signal: operator-creators, employees, and customers with real stakes in outcomes convert better than polished, generic creative.

“I think one of the great trends we all witness is the growth of AI content on social media… it’s so easy these days to develop pretty good content that I expect a flood over the next months—and the flip side is that real, authentic human recommendations are going to have a huge premium for brands.”

Rafael Schwarz, CMO, Territory Influence

Mike Newton links this to community and proof of actual influence:

• As AI answers generic FAQs and how-tos, creators become the go-to for niche, contextual decisions.

• Brands will demand evidence of “true influence over a group of people”, measured in relationships and the actions communities are willing to take – not just reach.

In that environment, operator-creators, employees, and customers with visible skin in the game outperform polished, synthetic personas. Human judgment, context, and lived experience become the scarce resource.

Where AI Influencers Actually Fit: Narrow, Utility-Led Roles

Raf McDonnell draws a useful boundary. “AI influencers” are not a universal replacement for human creators. Where they may fit is in specific service and utility contexts (e.g., FAQs, support, onboarding micro-tutorials) where entertainment or brand warmth is secondary to consistency and availability.

Service & support layers

FAQ explainers, onboarding micro-tutorials, “always-on” assistants.
Situations where consistency, language coverage and availability matter more than warmth or relatability.

Utility and experimentation, not brand soul

Testbeds for visual concepts, scripted scenarios, or basic product demos.
Sandboxes for brands to learn how audiences react to AI personas without risking core brand equity.

Taken together, the AI-related predictions in our dataset suggest a clear operating stance for brands and agencies:

• Treat AI as infrastructure, not the hero.
Use AI to accelerate ideation, editing, personalization, and reporting.
Resist the urge to make AI personas the center of your brand narrative except in tightly controlled experiments.

• Invest in human creators, communities, and owned trust graphs.
Expect AI to flood feeds with “good enough” content; differentiate through operators with real POV, proof-of-work, and engaged communities.
Measure influence in actions and relationships, not just impressions: saves, forwards, community behaviour, pipeline signals.

• Use AI influencers sparingly, where utility beats warmth.
Service workflows, education, onboarding, and multilingual support are natural starting points.
Design guardrails for deepfakes, disclosure, and brand safety before scaling synthetic personas.

• Explore hybrid formats, but keep humans as the anchor of credibility.
Combine AI-generated elements (visuals, scripts, dynamic offers) with human hosts in live shopping, webinars, and shoppable video.
Test AI co-hosts or assistants inside creator ecosystems without displacing the human at the center.

Clear evidence, experts do not believe in the success of AI Influencers

Amongst our interviews, one of the clearest alignments is, that experts do not believe in AI Influencers becoming a trend in 2026, on the contrary, they dont believe in them at all currently.

9/10 of the interviewed experts believe, AI-generated content will become the default, and the real competitive edge will shift back to real people. Brands and consumers will start to prioritise real voices, real messages, and real testimonials in their feeds over polished AI output – driving a resurgence in true UGC and influencer content of all sizes and purposes.

“As AI-generated influencers, deepfake personalities, and synthetic content flood every channel, audiences will recalibrate toward what feels unmistakably human. The more automated the feed becomes, the more valuable genuinely human experiences, imperfections, and perspectives will be.”

Djanan Kasumovic, Co-founder, Influencer Strategists

Human Creator Content Will Become Premium

In 2025 and beyond, the only content that compounds brand value is content that could stand alone as entertainment, if it wouldn’t work without a logo, it won’t work at all. 

Attention has outpriced pure performance

Buying reach is more expensive and less effective; the “performance paradox” means you can’t just outbid your way into people’s brains anymore.

The brands that treat themselves as entertainers are growing faster

The “entertainment-first” brands over-index on humour, character, shock/attention and social-native content, and are the ones showing double-digit revenue growth.

Our expert interviews converge on a simple rule: you’ll win by earning intent, with formats that feel native, honest, entertaining and useful, then travel efficiently across paid, owned, and search surfaces.

Three forces define the new content frontier.

AI Powered Content Editing

AI as a production co-pilot: scripting, editing, localization, and versioning now happen in minutes, enabling 10× more tests without 10× more headcount.

Human creativity and authenticity

Human creativity and authenticity as the scarce asset: as feeds saturate with AI-perfect polish, audiences reward lo-fi credibility, sharp creative ideas, clear points of view, visible trade-offs, and real usage.

Content distribution

Distribution intelligence: content is designed to be found (social and LLM search), not just seen in a feed, and measured on actions (saves, replies, qualified traffic), not vanity.

Treat “content” as a decision system: brief for a human insight, manufacture variants with AI, route the winners through paid and CRM, and retire anything that doesn’t move a business metric. In short, make less noise, create more value.

Creativity and entertainment move from ‘nice-to-have’ to performance drivers

“Creativity is becoming the differentiator after AI commoditizes production. Sarah Greenberg captures the shift clearly:With shrinking attention spans, brands must embrace creativity to stand out. As the digital space grows more crowded, standing out creatively will be vital for successful influencer marketing in 2026. Entertainment will shift from a bonus to a core driver of recall and engagement, pushing brands to create emotionally resonant, innovative content that meets evolving audience expectations.”

Sarah Greenberg, Head of Influencer Marketing Strategy, Relatable

Ross Yellowlees, GM at Izea, pushes this further from “creative is important” to “creators run creative”:

“I think first and foremost… creators are gonna be the new creative direction. Up until this point, brands I believe have worked with creators in a lot of different ways, but predominantly it's, here's the plan that we've come up with our big fancy creative agency, here's a brief that's gonna tell you to do this, this, this, and this, and I think that's gonna change in a big way.”

— Ross Yellowlees, General Manager Emerging Markets, Izea

Karl Mapstone, Global Partnerships Director at Vamp, sees the same pattern when campaigns succeed:

If production is cheap and distribution is crowded, the only way to win is to move the people who understand culture and audience (creators) upstream into strategy and creative direction, not keep them as executional media placements.

Eric Dahan starts from the same premise (AI commoditizes content) but pushes it into a labour-market implication for UGC and creator roles:

“UGC is gonna start going away or working with just like purely UGC creators simply because again, like that's, you know, that's gonna be more commoditized. It might turn into the world where the UGC creators are kind of morphing into more art directors, which I think is, you know, creative directors, which I think makes the most sense, right? They're talented, they know how to direct the content. AI becomes a tool for them to do more of that. But I think ultimately it's gonna put a premium on connection.”

— Eric Dahan, Founder at Mighty Joy

For brands and influencer marketers, “creative edge” becomes operational, not just inspirational. The leaders will

Treat creators as co-writers

Let creators shape the format and story, not just the caption.

Institutionalize creativity

Build creative operating models: regular writers’ rooms, formats that can be iterated weekly, rapid test-and-learn loops, and a small “hit squad” responsible for pushing ideas beyond safe.

In 2026, media dollars without creative edge will behave like a tax, not an investment.
The brands that win will be the ones that treat creativity and entertainment as a core capability – not a line item in the marketing budget.

Lo-Fi Honesty as a Performance Lever

If creative edge is what gets you noticed, lo-fi honesty is what makes you trust.

“Authenticity, lo-fi and just being really relatable as a consumer… that’s the thing that really resonates the most with me… not having as much elaborate production, but truly just put your phone up and record your thoughts on this… Even when I know someone's an ambassador, they might talk about a product saying, hey, I don't love this, but I do love this… you can speak about the pros and cons.”

— Emily Lipsett, Solutions Architect, Upfluence

For a consumer scrolling a feed, a shaky front-camera video that sounds like a real person thinking out loud often feels more trustworthy than a perfectly lit, three-camera studio setup. High production now reads as “controlled”; lo-fi reads as “unfiltered.” The signal audiences are scanning for is:

• Does this sound like someone who could lose followers or social capital if they lied?

• Do I hear real trade-offs, not bullet-point benefits?

Highly polished content won't be necessary anymore in 2026. Low-fi works fine and works as credible product storytelling: short, lo-fi, opinionated, and honest enough to include what didn’t work.

Brit Starr at CreatorIQ shows what lo-fi honesty looks like at scale. Instead of buying one big glossy hero video, her client built a simple pop-up experience where kids and parents could play with the product and film it. The outcome wasn’t a single masterpiece, but hundreds of short, messy, genuine clips that performed like a media engine:

“We’re living in a content first world. So it is all about the content… They created these opportunities for content creation around their products… The store also provided a kind of a content canvas… so much content was created through this experiential event… to the tune of, I think, 15 million in reach with a 35% social engagement.

Brit Starr, Chief Marketing Officer, CreatorIQ

Authenticity Becomes the Only Real Currency in an AI-Flooded World

If Lo-Fi honesty is the front-end signal, authenticity is the underlying currency. As AI makes it trivial to churn out “good-looking” content, the real risk for brands shifts from fake followers to fake-feeling content and eroded trust.

Jeremy Boissinot, CEO of Favikon, spells out the shift clearly:

For marketers, that means “high-quality content” is no longer enough; you need to know whether audiences actually believe the person saying it. Authenticity moves from a soft brand value to a hard performance input.

From Follower Count to Comment Quality and Growth Signals

If authenticity is the currency, community quality is how you measure it. Boissinot argues that chasing follower count and raw engagement is now one of the fastest ways to burn budget, especially when AI makes growth-hacked, generic posts easy to manufacture.
He points brands toward two simple, non-vanity checks:

“Check two things. The first thing is the growth rate… If a creator is growing, a creator should be growing. And the second factor is the comment section, which… is really, really important because that's where you're going to see if there's a community that's qualitative or not.”

In practice, that means treating comments as a qualitative panel, not a KPI ornament: are people asking specific questions, debating, sharing their own use cases – or just posting “Love this” and “Thanks for sharing”? And is the creator’s audience steadily compounding, or flat-lining around manufactured spikes?

Story as the Last Defensible Edge

Once AI can replicate almost any format or aesthetic, the only thing it can’t fake convincingly is a real, specific life story. That’s where Jeremy draws the line between commodity content and premium creator content.
His internal guidance to his own team is blunt:

Social commerce as a core conversion channel

Social Commerce is a natural extension of influencer marketing into shoppable content and in‑app buying that the industry has been patiently waiting for. Social commerce is shifting from experiment to default. The big change is structural: we’re moving from open-loop commerce (influencer → click → website → maybe purchase) to closed-loop commerce, where discovery, evaluation, and transaction all happen inside the same platform.

Social commerce could become a $7 trillion industry by 2030

On TikTok Shop, for example, specialist agencies are already running fully in-platform funnels where creators don’t just “drive traffic” – they host the storefront and close the sale. The entire path to purchase stays inside TikTok’s ecosystem: content, product detail, cart, checkout, and confirmation.

Social Media as Marketplaces

TikTok, Instagram, YouTube, and regional players are all racing to keep the full transaction on-platform. That’s why multiple forecasts now expect social commerce to account for trillions in annual sales by 2030 – not as a side channel, but as a primary route to purchase.

End-to-end full funnel commerce experience

The same short-form video or live stream that introduces the product also carries the product detail, price, inventory signal, and “Buy” button. You’re no longer sending people from a content environment to a separate commerce environment – content is the shoppable surface.

ROI becomes measureable

When discovery, engagement signals, and checkout sit in one environment, attribution stops being a proxy game. Brands can see which creators, formats, and hooks actually drive revenue – not just views.

In that world, creators are not media inventory; they are the front of the store. The rest of this section unpacks how our interviewees see that playing out.

For example, one expert talks about “significantly more livestreaming, social commerce activity by consumers” with brands leaning into more organic and viral content opportunities, implying that shopping behaviors will be tightly interwoven with everyday social content.
Influencers as retail partners and storefronts
There is strong consensus that in a social commerce world, creators function as retail partners, not just media inventory. Quotes explicitly mention:

• Influencers driving in‑app purchases through TikTok, Instagram, Facebook, etc.

• Livestream shopping where creators combine entertainment, education, and direct calls‑to‑buy.

Sherry Wu, looking at China vs. West, treats Douyin as the “future state” reference model for everyone else:

“In 2021… I see the functionality on social commerce start to bloom within the Chinese Douyin platform… I see live streaming coming up. I see all the shopping carts coming up and how the consumers in China embrace that new behavior, the new customer journey that is super short. It's impulse buy. You see something you like, you place the order. If you don't like it, you return it.”

— Sherry Wu, Partner & Associate Director, Boston Consulting Group

Her conclusion is that Western markets are simply lagging on the curve, not on a different curve:

Creators as Retail Partners, Not Just Reach

In a social commerce environment, creators function as retail partners and storefronts, not just media inventory. They are the front-of-store; platforms are the payment and logistics layer.

Vinod Varma pushes the same idea from a D2C angle, treating influencers as the primary commerce rail:

“There are 3 tailwinds driving us towards a world where Influencers are the leading channel for D2C commerce, or social commerce… Those who purchased from social media in 2023 are doubling their spend via social commerce in 2024. These tailwinds lead us to believe that Influencers will be the leading channel to drive commerce for brands.”

Vinod Varma, CEO, Creator.co

At a macro level, even the channel mix numbers are already meaningful. Gordon Glenister underlines how far this has moved from “experimental”:

AI, Personalization and Performance Inside Social Checkout

Several respondents tie social commerce growth directly to AI-driven targeting and performance measurement. Social content becomes the storefront; AI decides who sees which shelf, and when.

Sarah Letts points to TikTok Shop and AI-driven e-commerce as the practical expression of this:

“Paid amplification and AI-driven e-commerce will drive reach and conversions, with many eager to test and learn from TikTok Shop’s launch in the Australian market… Social commerce will simplify in-app purchases, while creator-led brands will rise as influencers launch their own products.”

Sarah Fischer Letts, Head Of Creative, Hoozu

Sherry connects the dots from tooling to boardroom-level accountability:

“Brands will invest more heavily in influencer marketing, yet efficiency and scale execution remain challenges… AI will streamline influencer selection, briefing, and content review, while unified metrics like EMV will define performance. Social commerce will accelerate in the West, mirroring Asia’s maturity.”

Sherry Wu, Partner & Associate Director, Boston Consulting Group

The pattern: social commerce is not just “shopping in apps”; it’s AI-optimized, performance-measured commerce routed through creator-led content.

From “One Checkout” to Fragmented, Full-Funnel Commerce

The old model was linear: drive all traffic to a brand site, convert there, and call it a day. Multiple experts argue that social commerce blows this up into a multi-node, non-linear journey.

Eric Dahan describes this shift bluntly:

“The old digital world, 10 years ago or five years ago, was you drive all your traffic to your website, people purchase, that's it. Your website's your checkout. I think we're going to live in a world where you have to have your full funnel strategy from discovery to purchase on Instagram, on TikTok, on YouTube, on your e-tail partners or partner sites like Walmart.com or Amazon. …Customers might discover something on YouTube, go make that purchase on X, and maybe read or write a review about it somewhere else.”

— Eric Dahan, Founder at Mighty Joy

“Offline activations will surge again — audiences want to meet creators and brands physically. Creator-led events, pop-ups, and IRL experiences will blend with social commerce for multi-layered engagement. The future combines social drops, local meet-ups, and live commerce moments inside apps with almost zero friction from discovery to purchase.”

Alessandro Bogliari, The Influencer Marketing Factory

Live Commerce Is a Skill, Not a Campaign

Brands and agencies often come with the same mindset: let’s test this once, see what happens, and treat it like another line item in the media plan. They expect the logic of paid social: launch, optimise, tweak bids, blame “audience fatigue” when numbers drop.

Live doesn’t behave like that. One night a creator smashes revenue; the next night, with “everything the same”, numbers collapse and nobody knows why. That’s the chaos most teams are afraid of.

Yenan Wang, former Head of TikTok LIVE EU Central Agency, keeps bringing the conversation back to behaviour in the room. For her, performance is driven by tiny, constant decisions: how the host speaks, how quickly they move between segments, how they handle awkward silence, how they recover from a flat moment.

“What they didn't realize is that there’s small human behaviours in it. It’s about pacing, voice tone, how creators handle the situation… live streaming involves so many things, including a creator's confidence, how the operation rhythm has been created in the team and how quickly you can adapt in the moment.”

— Yenan Wang, Founder NextWave

She makes teams answer basic questions:

• What changes in the creator’s voice when the room heats up vs. when it goes flat?

• What is the host doing in the 20 seconds before people start adding to cart?

• What exactly happens in the minute before viewership drops?

She trains people to notice patterns: the moment when energy dies because the host lectures for too long; the throwaway line that reliably triggers questions; the way a confident reset can save a shaky segment. Suddenly “the algorithm” stops being the villain. The lever sits in the room.

Once that lens is in place, she moves from observation to design. The output is not a big strategy. It’s micro-rules creators can actually use:

• How to open so the first thirty seconds don’t leak half the traffic.

• How often to clearly restate the offer and the benefit.

• What to say when chat is quiet.

• How to park a difficult question without freezing or derailing the show.

Crucially, she doesn’t try to industrialise this with 50 creators at once. She starts with a handful of “showcase creators” and stays with them until they can perform consistently. That consistency is important – not because it’s perfect, but because it proves to the organisation that live can be stabilised. Once a few hosts can deliver predictable revenue across multiple sessions, “live” stops being a gamble and starts looking like a skill gap the company can close.

From there, she pushes teams to do the boring organisational work everyone skips:

• Create a simple onboarding and training path for live creators.

• Define the review rhythm and early-warning checks for when revenue drops.

• Clarify who actually owns live operations internally, so it’s not a side-hustle for someone in social.

This is where it becomes a system, not a heroic one-off. After working this way, the agencies she supports are no longer “trying lives”. They are supporting creators who earn real income from live shopping and they can explain – concretely – why last night worked and why tonight didn’t.

The move beyond content co-creation into commerce co-creation

If creators are the front of the store and platforms run checkout, the next logical step is letting creators own part of the shelf. Several of our interviewees hint at this, but Abed Agha (Sociata) makes it explicit: the real unlock is moving from content co-creation (“post about our product”) to commerce co-creation (“sell your version of our product inside social”).

In this model, brands keep the same product catalogue and supply chain – but invite creators, especially micro-creators, to assemble their own bundles and boxes: “Marie’s Box powered by [Brand].” To the consumer, they are no longer buying a generic SKU; they’re buying a creator’s configuration of that SKU. That shift does three things at once:

• Turns creators into co-merchants.


• Increases authenticity, because the creator is effectively selling “their” product.


• Reduces the need for heavy brand governance on every post.

Abed captures this transition clearly:

Brands will move from content co-creation to commerce co-creation: instead of just paying creators to talk about products, they’ll let them own bundles inside the catalogue. A beauty brand, for example, doesn’t need to manufacture a whole new line for a micro-creator. It can let her pick “my eyeliner, my mascara” from existing SKUs and package it as “Marie’s Box – powered by [Brand]”

Abed Agha, CEO, Sociata

Merger of the world of retail media and influencer marketing

Creators are the high-trust content substrate; retail media is the data-rich delivery rail. Marry the two, and let AI work backstage, to turn advocacy into measurable, scalable sales. The next growth curve appears when you pair creator content (trust) with retail-media data (intent + transaction) and push it through paid rails you control. That’s how inspiration finally closes the loop to purchase at scale.

“Distribution is still kind of one of the key games of marketing today. And the data that is available in retail media allows for much better optimization and targeting. Now social platforms have made it have made have turned influences into content creators… the reason we call them content creators is because they no longer own their own distribution. 
And, you know, they don't get as many views as before. And so what I really believe is that marketers who really want to optimize influencer marketing are going to have to combine the content they get from traders, that is beautiful content, converting content that is genuine, authentic, and gives a good review—advocacy content—with distribution via paid media on social channels, with targeting from retail media partners that eventually drives back to this retail media ecosystem. So I think we've got two of the pieces that are well defined right now. But I think whether it's Amazon and Amazon's data or other kind of retail media networks, you're gonna see much more integration of influences into retail media spaces and data from retail media allowing marketers to drive to those retail media spaces. Sephora just announced, for example, that they're launching influencer shops on their platform. And that's gonna power a whole lot of data that's gonna help marketers drive better sales in Sephora.”

— Pierre Cassuto, CMO, Humanz

Creators are at the core of omni-channel marketing strategy

Social reach is unpredictable. Even big creators cannot rely on the algorithm to deliver every post to their audience. At the same time, retail media networks like Amazon, Sephora, and the major grocery chains give marketers something social platforms do not: reliable targeting to in-market shoppers and clear sales attribution at the product level. So the smart move is to keep creators at the center for trust and relevance, but to deliver their content through paid placements that you control, guided by retail data. That way you reach the right people, at the right time, with proof that it worked.

How the merged model works in real life

1. Start with creator content people actually want.
Short product demos, try-ons, comparisons, “before and after,” and quick answers to common questions. Make several versions so you can reuse them on social, your website, retail product pages, connected TV, and digital billboards.

2. Use paid delivery to reach the right shoppers.
Boost the best creator clips on social to find likely buyers. Then lean on retail media partners to target category shoppers, brand switchers, and high-value segments, and send them to the right place to buy.

3. Keep the experience consistent everywher.e
The same creator who introduced the product on TikTok should appear on the product page, in your email, and on the digital billboard near your busiest store. People feel continuity, which builds confidence to buy

4. Close the loop and learn.
Connect exposure to sales through retail media reporting and clean-room style data where available. Let your tools learn which creator, which hook, and which offer work best for each audience. Update your creative and placements weekly based on what you learn.

Experts explains why the offline part matters:

Alessandro points to the momentum you can build:

“Creator-led events, pop-ups and live shopping will grow again. We will mix local meet-ups, social drops and live commerce inside apps so people can go from discovery to purchase with almost no friction.”

Alessandro Bogliari, The Influencer Marketing Factory

How a Creator-Led Omnichannel Campaign Really Works

One campaign, one creator story, many channels. The point isn’t “be everywhere” – it’s keep the same creator narrative following the buyer from awareness to checkout.

“The teams that win are the most integrated. TV, OOH, digital, paid social – all with the influencer at the heart. When shoppers clicked from Instagram to the product page, they saw the same creator content, not a generic model shot. We saw ~40% uplift in add-to-basket and ~27% in sales. That’s the value of creator continuity across the mix.”

Mark Dandy, Strategic Consultant, Influencer Marketing

TV / CTV – Build fame with the creator.

30–60s hero spot introduces the creator and core promise.

Social & Paid Social – Capture interest with the same clips.

Short cuts of the TV asset + native posts push curious buyers to click.

Website & Product Pages – Answer last-mile questions.

PDPs and landing pages reuse the creator explaining benefits, proof and FAQ.

Email / CRM – Nurture with creator-led value.

Flows repurpose the creator for how-to, comparison and offer reminders.

Retail Media & OOH – Close the loop.

Retail placements, in-store screens and OOH echo the same creator face and line.

Net effect: every touchpoint feels like one continuous story – not five disconnected campaigns.

What marketers need to understand about influencer marketing measurement

Attribute value at the cohort level (who saw what, when, and where). Track first purchase, repeat, and LTV of exposed cohorts vs. matched controls. ROAS becomes an output, not the steering wheel. Start with one country, one category, one creator set. Show lift on PDP conversion and branded search in four to six weeks. Then scale creators and placements without changing the core promise.

From last-click to cohort lift

Not every sale has a visible “creator → click → buy” path. A TV spot, a TikTok search result and a PDP video can all contribute to the same purchase. Measure uplift in conversion, AOV and repeat for exposed cohorts vs. matched controls, not just direct clicks.

From channel reports to journey views

Replace siloed reports (“how did TV do?”, “how did TikTok do?”) with stitched views: social listening for demand signals, search data for branded queries, site analytics for PDP engagement, retail media for assisted sales. The question becomes: where did creator exposure shorten the journey or increase conversion?

From vanity metrics to operating metrics

Likes and views are noise. Standardise on a small set of operating KPIs: cost per exposed ICP, incremental revenue per exposed cohort, uplift in branded search, PDP conversion and repeat rate. That is what “consistent reporting” looks like when creators sit at the centre of the media mix.

Community Is the New Currency of Influence

Fragmented feeds, rising CPMs, and AI-accelerated content abundance have collapsed the scarcity of attention. What remains scarce, and therefore valuable, is connection: durable, identity-anchored ties between people, creators, and brands that compound over time.

“In a world where reach is fragmented and trust is scarce, brands need strong community strategies. Take, a brand that wants to enter UAE, where you have 200+ nationalities. How do you run a campaign targeting 200+ nationalities, thousands of communities, without having people inside those communities translate your value? You can’t. Only influencers got those keys to those communities.”

Djanan Kasumovic, Co-founder, Influencer Strategists

Advertising treats attention as an open market good; community reframes attention as a club good with access rules, shared norms, and compounding trust. In economic terms, communities create excludable positive network effects: the value of belonging rises as participation deepens

“The future of brand is really community… brands were defined by manufacturing, then by broadcast reach, now by their ability to connect.
And now I think it's really their ability to connect, which is the era of community that we're in. And so I started with that, and they seem like a fantastic brand that actually really understood building long-term community at its essence.”

— Eric Dahan, Founder, Mighty Joy

Creators that build niche communities outperform algorithmic volume

Dan Evans from his work on Gordon Ramsay's campaigns articulated this shift: "We're long gone the age now of where you can sponsor someone for half a million pounds who has tens of millions of followers and tell them to buy X product."

Ian Shepherd adds a critical insight:

What's happening? We're witnessing the unbundling of audience from community.

• Audience = People who see your content

• Community = People who care about your existence

A New Framework for Understanding Value

Based on our analysis of these expert insights, I want to propose a new metric: The Community Coefficient.

It's not about how many people follow you. It's about:

1. Depth of Connection (Will they show up?)

2. Frequency of Engagement (How often do they interact?)

3. Value Exchange (What will they sacrifice for access?)

4. Advocacy Intensity (Will they recruit others?)

Abed Agha from Sociata described a campaign that perfectly illustrates this coefficient in action.

The Challenge

Unilever Food Solutions needed to reach certified chefs—a community of just 120,000 people across multiple markets. Tiny by influencer standards.

The Old Approach

Use the brand voice. Create polished content. Push it through paid media.

The Community Approach

• Identified chefs who were already creating content

• Let them speak in their own language

• As Abed put it: "When they're basically within their environment, their macho, they're, you know, they'll be like, you know, my knife is stronger than yours. They'll use language that the brand can never use."

The Result

"Within three months, we've had the majority of that market... around 80% of the target market was actually following these creator accounts."
But here's the critical insight Abed shared: "When you speak their language, when you let chefs speak a language only chefs can understand, it's so relatable, it's kind of inevitably creates higher engagement."

— Abed Agha, CEO, Sociata

Conclusion

This report takes influencer marketing out of the “campaign” era and into the “infrastructure” era. AI keeps the machine moving: finding the right creators, testing formats, optimising spend. Creators keep the market moving: they are the ones people watch, believe and buy from. The brands that win will be the ones who treat that combination like plumbing for growth – something that runs every day, with clear owners, rules and targets.
When you step back from all the quotes, charts and case studies, a few shifts are hard to unsee.
Creators have moved from the edge of the plan to the centre of how people decide.
People don’t experience you as “brand → media plan → ad”. They experience you as “someone I follow tried this… someone in my niche explained this… someone I trust said this changed their work or life”. The creator layer has become the filter the modern brain uses to decide who to listen to, what to believe, and what is worth their time and money.

Secondly, AI is changing the economics, not the need for humans. The work that used to swallow whole weeks – finding creators, checking audiences, writing versions, localising, reporting – is moving into the background. That doesn’t make creators or marketers less important; it forces us to prove our value somewhere else. Strategy, creative judgement, relationship building and community, the parts of the job that actually change minds – become the job, not whatever’s left after the admin.
Now in this world, connection has become the real currency.

In a feed full of AI-polished content, people look for things that feel like they could not have been written by a AI Agent: a shaky front camera, a specific story, a clear point of view, a creator who shows up week after week in the same niche. Our interviews make one thing very clear: followers are cheap, communities are not. The market is quietly repricing towards depth, not just reach.
Taken together, this points to a different way of running marketing:
Fewer one-off stunts, more always-on creator relationships.
Fewer bets on channels in isolation, more focus on the humans who carry your story across all of them.
Less obsession with last-click ROAS, more attention to how creator exposure compounds consideration, search, and sales over time.
You can call that a creator operating system if you want. Underneath the label, it’s simple: a repeatable way to plug trusted humans and smart machines into the core of how your brand earns attention, belief and revenue.
As analysts, we don’t pretend this report has all the answers. But it does close one chapter. The question is no longer “does influencer marketing work?” The data, the experts, and the case studies here say yes – across brand, performance and pipeline.
The real question is whether you’re willing to redesign your marketing around what this new creator economy actually looks like, where AI handles the heavy lifting, creators hold the trust, and your job is to build the system that lets both do their best work.

Report done in collaboration with NeoReach.