Industries

4 min read

Industries

Coverage across the sectors and cross-industry decisions where AI is changing how work gets done. We report the shift, not the sales pitch.

Industry Contents organises its reporting around six industries where AI adoption is moving fastest and where the gap between vendor claims and daily operating reality is widest. Each beat is run the same way: we start from a specific claim, a product feature, a regulatory requirement, a vendor benchmark, and test it against what practitioners in that industry actually experience. Browse by industry below, or see everything recent across all six beats further down this page.

Legal

Contract review, e-discovery, copyright and how legal teams adopt AI without losing control of risk. We ask vendors for clause level accuracy, not a blended score.

Explore Legal » 02

Marketing

Attribution, brand safety and the new economics of winning a customer when every competitor has the same tools. Where automation helps, and where it quietly burns budget.

Explore Marketing » 03

Finance

Forecasting, reconciliation, risk and research tooling, and what survives an audit. We separate systems that read a filing from products that imply they can predict one.

Explore Finance » 04

E-commerce

Counterfeits, marketplace enforcement, personalisation and inventory. The operational detail that decides seller margins across Amazon, eBay and the EU marketplaces.

Explore E-commerce » 05

AI Tools

The tools businesses actually run, tested for what they deliver past the demo. Token costs, usage limits, and what breaks when real traffic arrives.

Explore AI Tools » 06

Industry Intelligence

Cross sector analysis for people who need the view across entire markets rather than one vendor category, including where the hype outruns the results.

Explore Industry Intelligence »

Why we split coverage across industries this way

Most AI coverage treats the technology as one story: a model gets better, a company ships a feature, adoption climbs. That framing misses what actually determines whether AI works in a given business, which is the operating environment it lands in. The same underlying model behaves very differently drafting a marketing email than reviewing a supplier contract, because the cost of a wrong answer, the regulatory scrutiny, and the definition of a good outcome are different across industries. Splitting coverage this way lets us track adoption where it is genuinely happening, rather than where the press releases are loudest, in line with how the OECD’s AI policy observatory tracks sector specific deployment rather than treating AI adoption as a single national statistic.

Some industries move faster than others. Marketing and ecommerce tend to adopt AI tools earliest because the cost of experimentation is low and results show up quickly in conversion data. Legal and finance move more cautiously, constrained by regulatory requirements and the higher cost of an error reaching a client or a filing. Our reporting reflects that pace difference rather than forcing every industry into the same adoption timeline.

Legal

Marketing

Finance

E-commerce

AI Tools

Industry Intelligence

Why we split coverage across industries this way

Recent across industries

Rezolve Ai Shows Why Enterprise Sales Still Needs Middlemen

The Missing Data Keeping AI Shopping Agents From Knowing You

Inside Europe’s New Market for Shadow AI Monitoring

European ESG Software Was Built on Regulation. Now AI Must Sell It

How AI Is Repricing Nordic SaaS

What Video Commerce Must Deliver to Pay for Itself

Why Online Retail Still Needs a Confidence Layer

Why Payment Checks Still Miss Identity Fraud