Data monetisation

Q: What have you learnt about using AI in data monetisation?

A: The opportunity for publishers in data monetisation is broader than many realise. So much data has real value that is left unrealised. Live data and exhaust data, properly mined and enriched, can power insights or entirely new products — and that’s just from what you already have within your workflows. Additionally, publishers have long had access to vast amounts of both proprietary and publicly available data, and AI offers new ways to harness and monetise both.

For proprietary data, publishers are increasingly leveraging AI to extract meaningful insights from unstructured content. This includes building structured knowledge bases, creating products that enable advanced querying, forecasting, visualisation, and even predictive analytics. AI also enables the repurposing of existing content into new formats like podcasts or interactive Q&A experiences, to reach fresh audiences. Additionally, licensing proprietary datasets to third-party large language models (LLMs) can offer a new revenue stream — something we see more publishers pursuing with significant success, following the lead of landmark agreements with OpenAI over the last 18 months.

Public data, enriched with AI-powered curation, is another valuable asset. Many column inches have been spent on the ‘moat’ that proprietary data can provide, but publicly available data can elevate your offering if weaved into the mix with skill. AI enables publishers to add context, structure, and meaning to otherwise fragmented or fast-evolving datasets. For example, by blending this data into a product with intuitive UX — even integrated directly into critical workflows or personalised to an individual level — to create something essential to your customer’s decision-making process.

Finally, publishers are deploying AI to maximise audience-based revenue with commercial tools that include dynamic paywalls, enhanced audience segmentation, and optimised ad placements. Through these, publishers can not only meet their readers’ needs more precisely but also drive revenue in innovative ways that align with user engagement trends.

Q: In which use-case has AI proved most effective?

A: One of the most powerful applications of AI in data monetisation is helping businesses navigate change and mitigate risk. Leading information providers, particularly those serving highly regulated sectors like chemicals, finance, and healthcare, are leveraging AI to support their customers in keeping pace with constantly evolving regulations. These industries experience frequent, high-impact changes that create enormous pressure on professionals in risk, strategy, and compliance roles, who must sift through fragmented, unstructured, and often overwhelming data. AI is transforming this challenge by organising, structuring and presenting critical information, empowering these professionals to act with confidence in a rapidly changing landscape.

For example, we work with publishers to implement AI-driven solutions to transform disjointed regulatory information into structured, actionable insights. Using AI, we identify relevant data sources, ingest and organise updates, and convert the unstructured information into structured regulatory guidelines. The result is a solution that not only provides trusted, up-to-date information but also equips users with practical tools like tailored checklists, visualisations and recommended actions. This moves the service up the value chain from a mere data aggregator to a must-have resource that saves clients significant time and effort and reduces business risk.

The impact is clear: by building high-value products that deliver not only data but actionable insights, publishers can drive recurring revenue and strengthen customer loyalty. The learnings from these implementations show that publishers have the opportunity to create indispensable tools that don’t just deliver data but deliver critical insights that are essential for decision making.

Three best practice top tips

1. Start with a clear understanding of what data and content you currently hold or have access to. This includes proprietary data, whether it is live or exhaust, as well as any partner or third-party data which could enrich your own dataset or provide additional context for your users. If you do not have this clear understanding, you may not see all the opportunities available to you which means you will likely leave money on the table.
2. Focus on your customers’ core challenges. To build impactful solutions, it’s essential to know what problems your customers are tackling every day. Go beyond assumptions held by internal teams and take the time to speak directly with your audience. This will provide valuable insights into their needs and help you design solutions that deliver real value.
3. Embrace AI as part of your toolkit — start today if you haven’t already. GenAI has rapidly moved from a disruptive technology to something many publishers are now rightly considering as just another essential tool, whether for internal efficiencies or creating new products. Those who haven’t yet made a start in any direction risk falling behind, as the pace of AI-driven innovation will only continue to accelerate. If you are reading this and thinking this is your company, the best way to move forward is to work with experts who can guide you through a process of identifying and prioritising opportunities, set against the context of your particular industry, ambitions and capabilities.

We are experienced technology and product experts working with specialist information publishers to grow the value of their businesses. We deliver a spectrum of consulting services, from strategic advisory to product discovery, development and engineering, to enhance the value of information businesses.

Email: jennifer.schivas@67bricks.com

Web: www.67bricks.com