There are three things in the world that deserve no mercy – hypocrisy, fraud, and tyranny. - Frederick William Robertson, British Theologian.
While Robertson may have been speaking from a 19th-century theological lens, his observations are as true today in the 21st. Fraud as an activity has assumed gigantic proportions in the digital era, with technically-savvy fraudsters employing a panoply of tools and stratagems to defraud people and organisations.
The term Business Intelligence (BI) first appeared in 1865 in the writings of Richard Millar Devens, and was later redefined in a technological context by IBM researcher Hans Peter Luhn in 1958. Many decades later, the term remains relevant today, though its meaning has undergone multiple transformations. From early decision support systems that generated static reports to the era of Big Data, real-time analytics, and now AI-driven intelligence, BI has continuously evolved alongside technological advances.
Traditional BI often operated through multiple interfaces, with different stakeholders glimpsing at different dashboards. Additionally, BI was often a standalone entity that provided the requisite insights, which would then need to be implemented within the respective Enterprise Resource Planning (ERP) workflows. In its blog ‘The Key To Insights-Driven Decisions Is Curiosity Velocity’, which discusses themes from its research on data culture, Forrester notes that 61% of organisations still use four or more BI platforms. It further states that analysts and insights professionals potentially lose up to 40% of their productivity due to constant task and context switching. This fragmentation creates a critical gap between insight generation and implementation. In an era where agility defines success, organisations increasingly seek ways to embed BI into their ERP workflows, so that the stakeholders can gain the necessary visibility and effect necessary changes in real-time.
Embedded analytics addresses this need by integrating all dashboards, portals, reports, and other data visualisations into business applications. By embedding intelligence directly into the workflows, it almost makes BI invisible and far more impactful. It continuously monitors business processes and provides timely insights and actionable suggestions that can be implemented immediately, increasingly anticipating business needs. Whether predicting possible supply chain disruptions for a logistics team, enabling real-time margin analysis for dynamic pricing decisions, or helping operations managers optimise downtime, embedded analytics transforms BI into a seamless and strategic business enabler.
Organisations utilising embedded analytics undergo a paradigm shift from consuming passive analytics to actively orchestrating decisions. BI is evolving from a reporting capability into an always-on intelligence layer embedded directly into business processes, and a potential revenue enabler, enabling organisations to sustain their competitive edge.
Some of the key benefits organisations gain by embedding analytics in their business applications include enhancements in decision-making, customer experience, and productivity. However, one of its most profound and transformative benefits is the democratisation of data. Let’s delve into this aspect further to understand why it is a key differentiator.
The democratisation of data
Traditionally, only data analysts and specialists worked with insights, making it a specialised domain. However, with embedded analytics, even non-technical users can engage with insights directly within the applications they already use. It breaks down data silos, enabling every role to access contextual insights intuitively, cultivating a more data-literate workforce in the long run.
This shift towards democratised data access is also highlighted by Forrester in its blog ‘Bring Data To The Other 80% Of Business Intelligence Users’, which notes that BI must evolve beyond the traditional 20% of specialist users to empower the wider business workforce. Embedded analytics solutions align with this direction by delivering insights directly within operational applications, making analytics accessible at the point of decision-making. Further, cross-functional teams collaborate more effectively to derive collective value that maximises business impact.
Contextual insights reach the right user proactively, further enhanced by natural language processing, enabling conversational queries and instant visualised responses. The aforementioned Forrester blog notes that such approaches cover additional business users, with embedded or ambient analytics as a key approach to deliver insights directly to users within their existing workflows. Here, analytics evolves into what could be termed as decision infrastructure, enabling each user to make timely and informed decisions. Deloitte’s ‘Technology, Media and Telecommunications Predictions 2026’ notes that more people will use Gen AI when it is embedded inside existing applications than as a standalone tool, with up to 300% higher daily usage predicted in search-related use cases.
This could explain the higher adoption of self-service embedded analytics in recent years, being implemented through options such as drag-and-drop report builders and low-code or no-code platforms. The safety and security of the data are maintained through role-based access, which ensures every role only sees what they should. Most modern embedded analytics solutions provide enterprise security capabilities that support compliance requirements, along with robust audit trail functionality.
The future: composable, invisible, and continuous intelligence
According to Fortune Business Insights, the global embedded analytics market is expected to grow from USD 22.93 billion in 2025 to USD 86.2 billion by 2034. One of the key growth factors mentioned is the growing demand for customised analytics solutions. The trend is industry-specific embedded analytics solutions powered by AI that are composable, invisible, and provide continuous intelligence to enable decision agility. The future of BI will be defined by how seamlessly intelligence integrates into business processes, enabling real-time decision-making.
How Infosys BPM can help
Infosys BPM’s embedded analytics services are powered by our proprietary model, Process Progression Model™. We integrate embedded analytics into existing business processes seamlessly to provide our clients with real-time visibility into multi-domain performance. Our sub-offering suite covers analytics tailored for a variety of CXOs, including those in finance, marketing, procurement, and human resources. Our solutions are designed to drive metrics across existing BPM operations, to maximise the potential of BI.
