Asset intelligence is variously defined. For example, Deloitte's approach to it is that it integrates artificial intelligence, IOT data and predictive analytics to optimise asset lifecycle management, operational visibility and risk reduction.
The frameworks shift organisations from reactive maintenance, to proactive, data-driven intelligence across physical, digital and operational environments.
A simpler view of it would be that asset intelligence is a concept of inventory enriched with context and continuous awareness to provide easy access to relevant information. This in turn translates into the ability to secure and optimise that asset.
Were they the good old days?
Traditionally, security and other tools have acted as systems of discovery and protection, providing siloed records where each asset is managed in isolation by various teams in the organisation.
Today, in the always connected and AI-driven world, asset intelligence is critical to secure the business. Companies can no longer rely on static inventories or configuration management databases (CMDBs) to understand their environment.
As cloud infrastructure, SaaS applications, identities and AI agents become increasingly dynamic, organisations need continuous, real-time, asset intelligence that provides not just visibility, but context, relationships, ownership and historical insights.
The bottom line is companies can no longer rely on correlation and reporting.
Back in the day, information emanated from an array of teams, including systems and service management, plus security teams with resulting duplication of different data points required by the teams to perform their duties.
To compound the duplication of data issue, these systems and processes were built for relatively static and stable IT environments.
Today, the environment is increasingly dynamic and in order to protect the business there is a real need for continuous, real-time asset intelligence that provides context, relationship, ownership and historical insights. The bottom line is companies can no longer rely on correlation and reporting.
Stark reality of the digital world
Modern business environments, with their supporting infrastructure, are changing at machine speed. Records are updated in calendar time, leaving teams with significant blind spots when designing and managing robust architectures built for scale and reliability.
Assets and business services are instantly added, increasing the risk as new assets are not dynamically identified and prioritised.
Teams relied on data clumping of all information provided, if they were to ease their burden. However, aggregation does not solve the problem alone; pulling all the data into a single point is a good start but not the destination.
Clustered data needs to be consolidated into a usable context layer that deals with source authority, conflict resolution, confidence tracking and drift (otherwise known as slow uncontrolled changes that need to be detected over time) detection combined with ownership. Without this contextual layer, the aggregated view is only as strong as the least trustworthy source feeding into it and possibly scanning frequency overlaps.
If you were to consider that no one system of record is the single source of truth, how do you provide durable/usable context? To achieve this will require a dynamic reconciliation layer above numerous data sources.
It's important to note this is not a new or better CMDB, nor is it another network scanner, or a consolidation identity provider. It is rather a layer that connects to all the sources and allows you to intelligently aggregate the data so you could make informed decisions based on context and exposure.
Know your assets
The essence of knowing what the company has in order to manage or secure the asset, is not a new or novel idea; it is a practice that has to move from asset management to dynamic asset intelligence, the use of asset data to improve security posture and continued availability of business services.
There is a need to move from the position of simply asking what is in the inventory, to one that addresses the following:
- Who owns those assets?
- What business processes do they support?
- Are they managed and if yes, by how many tools?
- How do we know that all the security controls by the various domain owners are present on all the devices they need to be?
- What systems are they connected to and who is using them?
- What business risks do they represent and what is compromised if they are lost?
- How have they changed over time?
Essentially, companies need a record of the history of their assets.
In a nutshell, as businesses and infrastructure providers deploy more AI-enabled assets plus dynamic workload provisioning, security teams will not be able to enforce and deploy the correct controls.
This can only be achieved with asset intelligence correlation between business processes and infrastructure deployment.
Share
