First off, a very happy 2026 to all of you! We’re kicking off this year’s first edition a little differently. I scan through and read a large volume of articles every week, and have decided to run an analysis on a large sample of articles from 2025. I’ve managed to collect a dataset of close to 3,000 articles that went live between January - December 2025 and have looked at the various topics, themes and discussions that have shaped the year.

Before we get into the thick of it, I want to provide some pretext in the shape of two tables I've put together:

First, the table below visualises the segmentation of various topics and volume share across these articles, as well as what the topic represents in terms of coverage.

Table showing 2025 topic coverage, volume share, and what each topic represents

The second table provides us with an idea of the level of editorial quality (according to AI) for each outlet, as well as the volume and what the outlet tends to focus on in terms of topics.

Table showing outlets, article volume, editorial quality, and dominant topic focus

Utilising various AI tools, I've started to review the dataset covering 1,000+ different outlets and close to 3,000 articles and have created five key topics/themes that have dominated online media conversations in 2025. I've specifically omitted Unilever as a standalone theme, and have tied it to the existing themes - and have steered away from event-based topics such as the Super Bowl, Cannes, etc.

1️⃣Professionalisation of Influencer Marketing

Our dataset shows that 2025 marks a clear shift in how influencer marketing is discussed: coverage moves away from why influencer marketing works and toward how it is structured, measured, and governed. Influencer marketing is no longer framed as an experimental, creativity-led channel, but as a business discipline that must operate consistently and at scale.

Coverage increasingly treats influencer marketing like other core marketing functions: something that requires performance accountability, governance, and integration into existing systems.

The Unilever announcement of its increased influencer marketing efforts early in the year reinforces the idea that influencer marketing is no longer being tested at the margins, but rather becoming institutionalised at scale.

Signals from our dataset

Professionalisation in the dataset is driven by structural, not organisational, signals:

  • Always-on programs replacing one-off campaigns, indicating influencer marketing is no longer episodic but continuous
  • ROI and performance language becoming standard, with influencer activity evaluated alongside paid media and other measurable channels
  • Governance and compliance appearing alongside growth stories, reflecting increased scrutiny and risk at scale
  • Deeper platform integration into commerce and paid media stacks, tying creator output directly to revenue, amplification, and distribution systems

2️⃣Influencer Marketing as a Business Function

We're seeing that more and more articles are describing influencer marketing as something that:

  • runs continuously, not episodically
  • requires systems, workflows, and ownership
  • connects to commerce, paid media, and performance teams
  • breaks when it's not taken seriously / dealt with properly

Influencer marketing is no longer framed as a channel you "activate," but as a proper business function.

It surfaces in 2025 because brands reached a point where influencer marketing touches too many parts of the organisation (brand, growth, commerce, legal, platforms) to not be taken seriously.

Signals from our dataset

  • Always-on creator programs instead of campaign launches
  • Workflow language (process, systems, integration, tooling)
  • Platform features designed for ongoing creator management
  • Creator content reused across paid, owned, and commerce channels
  • Breakdowns and failures caused by scale (compliance, trust, cost)

3️⃣AI Becomes a Scaling Layer

AI shows up frequently in our dataset, but rarely as a standalone narrative about industry transformation. Instead, it appears embedded inside other stories: tooling, workflows, creator discovery, content production, reporting, and risk. That's the signal.

AI isn't necessarily framed as "the future of the creator economy" but instead positioned as the solution for scaling, as the operating costs of scaling through simply increasing headcount is becoming less viable and efficient.

Signals from our dataset

  • Automation of influencer workflows (discovery, briefing, reporting)
  • AI tools embedded in creator platforms, not standalone products
  • Synthetic or AI influencers framed through trust, risk, or governance
  • Efficiency language (speed, scale, cost reduction)
  • AI discussed alongside operational topics vs creativity

4️⃣Trust & Authenticity as a Baseline Requirement

Trust and authenticity are not necessarily dominant topics by volume, but they are structurally present when scale and risk are discussed. Trust surfaces most clearly at points of friction: regulation, enforcement, brand safety incidents, platform intervention, and debates around AI within influencer marketing infrastructure. Trust is no longer discussed as a way to improve influencer programmes, but as a minimum condition for operating at scale - a baseline requirement: if it is present, nothing special happens; if it is missing, your programme may not function properly.

Signals from our dataset

  • Disclosure rules, bans, and enforcement, often reported alongside creator growth or platform expansion
  • Brand safety concerns, particularly as creators become more commercially integrated and more publicly visible
  • Audience scepticism toward over-commercialised or AI-generated content, framed as backlash rather than preference
  • Regulatory and legal coverage, signalling that influencer marketing is now treated as consequential advertising activity
  • Big outlets remain critical of influencer economy, and individual incidents are used to diminish value of influencer marketing

5️⃣Continued Consolidation

Funding rounds, acquisitions, agency roll-ups, and platform buy-and-build stories are consistent in 2025.

The dataset shows that capital is moving into the creator economy, not to discover what's possible, but to scale what already works. Agencies are acquired to increase capability, platforms are buying tools to control workflows, and investors back infrastructure-like businesses rather than creator-led experiments.

Signals from our dataset

  • Acquisitions of influencer agencies or creator platforms
  • Holding companies integrating influencer capabilities
  • Funding rounds framed around scale, not novelty
  • Private equity and strategic buyers are entering the space
  • Language around "capability", "integration", and "expansion"

Bonus: what to expect in 2026

This has been a really interesting exercise, and a great way to use AI tools & Python to play around with large data sets. I've made a conscious effort to avoid making predictions, but I've put the dataset through a few AI models and asked it to identify what we can expect in 2026 in terms of topics.

One thing that I agree with - is that we're likely to see more and more conversations around infrastructure and ecosystems, as it matches the scaling and AI conversations that have become mainstream in 2025.

I've asked AI to come up with a few topics we may see in 2026:

  • Why Influencer Marketing Needs Infrastructure to Scale
  • Inside the Systems Powering Always-On Influencer Marketing
  • The Hidden Complexity Behind Always-On Creator Programmes
  • How Influencer Marketing Became a Core Marketing System
  • When Influencer Marketing Breaks: Lessons From Scale
  • Why Influencer Marketing Metrics Need Standardisation
  • From Vanity Metrics to Financial Accountability in Creator Marketing