AI and Inspection Management: What Changes Now, in the Next Few Years, and Beyond

A maintenance planner at a mid-size processing plant is trying to work out why a critical vessel keeps failing inspection on the same recurring finding. The answer is probably sitting in three places at once: a stack of paper checklists in a site office, a supervisor’s memory of “the same issue two turnarounds ago,” and a spreadsheet nobody has updated since March. No system connects them. By the time the pattern is obvious, it has already cost a shutdown day.

This is the starting point for almost every conversation about AI and inspection right now, and it is also where most of the AI hype gets ahead of itself. Before any model can predict a failure, prioritise a risk, or draft a report, something much less glamorous has to happen first: the data has to exist, in a structured, retrievable form. That is the uncomfortable but urgent truth sitting underneath three recent pieces of industry analysis, from Industrial Equipment News, McKinsey, and Rystad Energy, each looking at a different sector but arriving at the same structural conclusion.

Why the AI layoff debate is asking the wrong question

Much of 2026’s AI commentary has fixated on headcount: which companies are cutting jobs and blaming AI for it. Writing in Industrial Equipment News, MaintainX CEO Chris Turlica argues this framing misses the more important pattern playing out in industrial sectors specifically. Industrial organisations aren’t adopting AI differently because they’re more enlightened. They’re doing it because the maths of their workforce demands it. American manufacturers alone are projected to need 3.8 million new workers by 2033, with roughly half those roles at risk of going unfilled, not through layoffs but through retirement. Decades of operational judgement, the kind that lets a senior technician diagnose a fault in minutes rather than hours, is walking out the door with no system to capture it.

The parallel Turlica draws is the Industrial Revolution: mechanisation didn’t just displace weavers, it made each remaining worker dramatically more productive. AI is following the same logic in industrial operations, but only where organisations have already done the unglamorous work of digitising the frontline. His observed pattern is consistent and instructive: organisations first digitise frontline workflows, using mobile tools that capture institutional knowledge and coordinate work in real time, and only then layer AI on top to surface patterns, flag anomalies, and support decisions at the point of action. Skip the first step, and there is nothing for the second step to learn from.

This matters directly for inspection management. Every inspection, every fault report, every corrective action closed out on paper is either raw material for tomorrow’s AI-assisted decision-making or a permanent gap in it. Human judgement remains essential throughout, and Turlica is careful to frame it that way: AI augments the technician’s diagnosis, it doesn’t replace the accountability that sits with a qualified person signing off on a safety-critical asset.

Now: data collection is the urgent, unglamorous priority

This is the part of the AI conversation that gets skipped in favour of more exciting claims about automation and prediction, and it is the single most important point for industrial teams to act on today.

Rystad Energy’s analysis of AI in upstream oil and gas puts it plainly: “AI accelerates what happens inside a digitally mature organisation; it does not necessarily accelerate the process of becoming one.” Rystad estimates digitalisation and AI will create close to USD 500 billion in cumulative value for exploration and production companies between 2026 and 2030, but the structural finding underneath that number is more important than the figure itself. AI, in general, does not raise the ceiling for the best-performing assets or teams. It lifts the rest of the organisation towards the performance level the best operator already achieves, and it can only do that if there is consistent, structured operational data to learn from. Where that data doesn’t exist yet, in trapped paper records, inconsistent spreadsheets, or tribal knowledge, AI has nothing to accelerate.

McKinsey’s analysis of the architecture, engineering, and construction (AEC) sector reaches an almost identical conclusion from a completely different industry. “Data becomes an advantage only when firms capture it at the point of creation, structure it so it can be reused, track its origins and meaning, and retain the rights to learn from it over time.” Most AEC firms already hold enormous archives of drawings, inspection reports, and close-out records, McKinsey notes, but most of that archive is unusable: paper-based, inconsistent, siloed across systems that don’t talk to each other.

For inspection and asset management teams specifically, this translates into a concrete, near-term task list rather than a wait-and-see posture:

• Move inspection capture off paper and out of static spreadsheets, into a structured system that enforces consistent fields, mandatory checks, and defect taxonomies from the first record onward.
• Capture context at the point of inspection, not after the fact, including photos, GPS location, nameplate data, and the technician’s own notes on why a decision was made, not just what the decision was.
• Centralise the equipment register so that inspection history, corrective actions, and asset criticality live against the same asset record instead of being reconstructed from memory and disparate sources during an audit.
• Treat every inspection as a future training example, not a one-off compliance box tick. A well-structured record captured today is what makes a useful AI-assisted recommendation possible in two years; a scanned PDF is not.

None of this requires AI to start. It requires discipline about data structure, and it is the precondition for everything that follows.

Nowadays, efficiency is not just a goal to strive for; it’s a necessity for modern businesses. Inspectivity, a cutting-edge digital inspection platform, is transforming how industries approach the critical task of asset management and inspection. By automating workflows, Inspectivity is setting new standards in operational efficiency, particularly for sectors like energy, utilities, and engineering.

Streamlining Inspection Processes

The cornerstone of Inspectivity’s offering is its robust suite of automation tools. Traditional inspection processes, often bogged down by manual data entry, paper-based records, and siloed information, are notoriously time-consuming and error-prone. Inspectivity’s platform seamlessly bridges these gaps, offering an integrated, cloud-based solution that accelerates and simplifies inspections.

One notable feature is the Platform’s Asset Hierarchy modelling capabilities. These features allow for the efficient organisation and categorisation of assets, ensuring that every piece of equipment is accurately tracked and easily accessible. This systematic approach not only saves time and enhances the precision of inspection processes but also aligns more closely with typical ERP implementations.

Empowering field inspectors with mobile integration

Inspectivity’s ‘Go’ mobile app revolutionises field inspections. Schedulers can spend less time on planning fieldwork campaigns, whilst inspectors can conduct inspections faster with all critical information at their fingertips and automated reporting outcomes.  Inspectivity’s mobile app integration ensures that data is captured accurately and promptly, enabling faster decision-making and compliance.

Data-driven decision-making

Beyond streamlining inspection workflows, Inspectivity empowers businesses with data-driven insights. The platform’s analytics tools help in harnessing inspection data for predictive maintenance, risk assessment, and compliance management. This approach not only improves the immediate efficiency of inspection tasks but also contributes to long-term strategic planning.

Global collaboration and customisation

In a global business environment, collaboration across different locations is vital. Inspectivity’s platform fosters global collaboration by enabling teams to work on the same dataset, irrespective of their geographical location. Moreover, the platform’s scalability and customisation options ensure that it can adapt to the specific needs of various industries, further enhancing its efficiency.

Take the next step with Inspectivity

Inspectivity is more than just a digital inspection tool. It’s a comprehensive solution that redefines the efficiency of inspection processes. By automating workflows, providing mobile integration, offering data-driven insights, and enabling global collaboration, Inspectivity is helping industries step into a future where efficiency and precision go hand in hand. For businesses looking to enhance their operational efficiency, Inspectivity presents an invaluable opportunity to leap ahead in their digital transformation journey.

Explore our plans and pricing or schedule a demo today.

For small businesses, especially in asset-intensive industries, the need for efficient and accurate inspection processes is great. Inspectivity, a powerful digital inspection platform, offers a transformative solution for streamlining reporting processes and gaining invaluable insights. This blog delves into how Inspectivity can help your business to streamline asset management through standardised workflows, customisable report templates, and intuitive dashboards.

Standardising inspection workflows

Streamlining operations can be a game-changer for small enterprises, particularly those managing substantial assets. Inspectivity stands at the forefront of this transformation by providing standardised workflows that simplify the reporting process. This pivot towards a structured approach ensures that every inspection adheres to the same standards, reducing errors and inconsistencies. By implementing Inspectivity’s standardised workflows, small businesses can guarantee uniformity in inspections, which is vital for maintaining quality control and meeting compliance requirements. This standardisation not only expedites the reporting process but also instils a level of discipline that can significantly enhance productivity and decision-making.

Tailoring reports to meet your business needs

One of Inspectivity’s most compelling features is its highly configurable inspection templates. Small businesses can tailor these templates to their specific needs, ensuring that reports are not only comprehensive but also fast to complete. This configuration extends to integrating photos, audio, and video, adding depth and clarity to the templates. The no-code platform aspect allows non-technical staff to easily adapt and modify templates, ensuring that they align perfectly with the business’s operational requirements and standards.

Making data accessible and understandable

Inspectivity’s intuitive data collection capabilities turn complex inspection data into easily digestible and searchable formats. Dashboards and real-time PDF reports provide a clear overview of the inspection outcomes, making it easier for stakeholders to understand and act upon the findings. These features are particularly beneficial for small businesses, where clear communication and quick information dissemination are essential.

Implementation tips for small businesses

For small businesses keen on harnessing the power of digital inspection, implementing Inspectivity is a strategic move that can drive efficiency and clarity in operations. Here’s a streamlined approach to optimising the platform for your business needs:

• Define clear objectives: Before diving in, outline what you aim to achieve with Inspectivity. Ask yourself the critical questions about how digital inspection will reinvent your workflows and affirm the core reasons for this digital shift.

• Involve key players: Collaboration is key. Identify and involve stakeholders from various departments such as IT, Legal, and Engineering to build a strong case for the transition and ensure a well-rounded implementation strategy.

• Pinpoint the implementation lead: Assign a point person for implementation. This individual will be pivotal in steering the project towards completion and will serve as a go-to for any queries or issues that arise.

• Timely implementation: Timing is everything. Start the digital inspection integration when kicking off new projects which can allow a seamless transition to operations.

• Flexibility and agility: Select a digital inspection system that offers flexibility. Begin with a single use case, implement it from start to finish, and iterate based on feedback. This agile approach will allow for continuous improvement and learning to refine future implementations.

To learn more, explore our plans and pricing or schedule a demo today.

In this Q&A article, we explain how digital inspection fits within the myriad of systems and processes supporting asset management for critical infrastructures. In particular, Enterprise Asset Management (EAM) and Asset Performance Management (APM).

EAM vs APM?

IBM describes Enterprise Asset Management (EAM) as “a combination of software, systems and services used to maintain and control operational assets and equipment. The aim is to optimise the quality and utilisation of assets throughout their lifecycle, increase productive uptime and reduce operational costs”. EAM is centred around the ERP or CMMS with functions for asset equipment registers, maintenance and task planning, work order management, and commercial and people/resource concepts. The EAM is the source of truth.

APM sits beside EAM to consume the transactional aspects of work order management, understanding changes to the asset hierarchy to provide predictive forecasting and reliability-centred maintenance schedules.

EAM is managing operational viability and compliance whilst APM is taking intelligent inputs to determine actionable insights for maintenance planning, feeding back to the EAM for execution in the field.

 

For the most part operators of critical assets are fairly mature in EAM implementation but now many are adding APM to their asset management landscape however it is still very early days with a much lower uptake. Deloitte estimated (2019) that about 5 per cent of companies have achieved an APM program. We expect that level of take up has accelerated further in the last 3 years.

What is the difference between EAM and CMMS?

Many see the EAM as part of the wider CMMS or ERP system which is responsible for centralising information to facilitate and automate maintenance management processes but the EAM has a more focused role. EAM is an asset lifecycle management approach that supports asset performance from acquisition to disposal.

EAM includes activities such as:

• Asset lifecycle management
• Work order management
• Inventory management
• Facility management
• Predictive maintenance
• Reporting and analytics

Why is EAM Important?

EAM is important for asset owners because it helps operators to understand asset condition, reliability and sustainability. It provides a set of systems and processes to analyse, assess and maintain assets. Critically EAM helps organisations to predict future reliability issues and to plan risk approaches to maintenance that are based on high-quality data inputs. The key drivers for implementing an EAM strategy are:

• Asset data – The CMMS is a key element of the EAM providing a central repository for all data relating to operational assets. A hierarchical structure provides the ability to see all information about the asset, understand key maintenance task frequency and manage the asset through enterprise workflows.
• Issue management – Maintaining equipment relies on a discrete understanding of issues/non-conformances/defects in order to plan preventive maintenance routines accordingly.
• Monitoring – EAM gathers vast amounts of data relating to assets, issues and maintenance workflows. Data collected is then catalogued and made accessible to engineering for continuous improvement and planning.
• Reliability and sustainability – EAM’s central goal is to ensure continuous operations where possible and to improve the longevity of assets. This is achieved through the collection of high-quality data from a variety of sources such as IoT and traditional inspection. This driver also addresses the need to extend the life of assets through risk assessment methodologies.
• Future complexity – The future for asset owners presents significant challenges and unknowns with regards to reputation, compliance, safety and environment. EAM practices and modern data collection can increase confidence in the inputs for risk decisions and improve the ability to meet and exceed corporate goals.
• Standardisation – EAM helps companies achieve consistent, repeatable and standardised asset management processes across any asset class.

What are the key features of EAM?

EAM is wide in scope and consists of both technical systems, well-defined business processes and expert engineering know-how. From a system point of view it has a number of critical aspects:

• A single of source of truth for all asset information and for the coordination of maintenance workflows such as work order creation and follow up work.
• A central repository of lifecycle documentation such as engineering specifications, drawings, certificates and OEM data.
• Maintenance management with a focus on more advanced management strategies such as condition-based or predictive rather than corrective maintenance and also ensuring that planning for inspection (ie. frequency) is based on high-quality data inputs.
• Supply change management to ensure parts and spares are maintained effectively. Also provides oversight of test equipment to ensure critical tools are calibrated, in service and in date.
• Change management processes to provide visibility to all stakeholders and support quality goals.
• Safety and environment stakeholders should be “linked” to field teams to allow real-time notifications and to ensure KPIs can be monitored by senior management.
• Fieldworker connectivity with mobile devices and smart data collection applications.
• Equipment tagging such as encoded human-readable labels (QR, 2D) or RFID tags, ensures a direct link between assets and systems.
• Monitoring via business intelligence systems and real-time visualisations. Dashboarding strategies for all levels of stakeholder and analysis.
• Engineering teams should have access to strongly typed data sets of asset condition information, inspection history, issue data, and media.
• Cloud deployment models to support dynamic infrastructure, modern security models and simpler integration of vendor applications (eg. AWS Landing Zones/Control Towers).

What does APM involve?

Gartner says Asset performance management (APM) encompasses the capabilities of data capture, integration, visualisation and analytics tied together for the explicit purpose of improving the reliability and availability of physical assets. APM includes the concepts of condition monitoring, risk assessment, predictive forecasting and reliability-centred maintenance (RCM).

An APM program starts with an evaluation of all required parameters to address reliability, integrity, corrosion, and performance for all mechanical equipment. It includes systems to model maintenance interventions at various frequencies based on intelligent algorithms and a wide range of high-quality data inputs. APM systems also have the ability to trigger work orders in the EAM based on asset health thresholds being reached.

Are there different maturities of APM implementation?

APM is not a recent concept. According to GE it has been actively used for more than 20 years but APM comes in different flavours or levels of maturity:

1. Reactive maintenance – Represents a lack of planning and a break-fix approach (corrective maintenance).
2. Preventative maintenance – Driven by engineering or compliance requirements.
3. Condition-based maintenance – Performed when monitoring indicates equipment operating characteristics have deviated from design.
4. Predictive maintenance – Essentially discovering maintenance options for the future through calculated asset health.

More advanced APM is taking shape in the manufacturing sector with Digital Prescriptive Maintenance and Collaborative Excellence (a collaboration between maintenance/operations/supply/safety). Essentially involves the diagnosis of events before they occur through a combination of IoT, Big Data and Dynamic Case Management. For a deeper dive read Pega’s Manufacturing Whitepaper.

Where does inspection participate in EAM and APM?

ERP/EAM systems provide a transactional platform to support the work management process. A significant proportion of the work is maintenance based inspection programs including operator rounds, compliance, safety, visual condition monitoring and much more. Through inspection the EAM is:

• Gathering vast amounts of data relating to assets and maintenance workflows.
• Maintaining critical mechanical equipment.
• Ensuring asset longevity by gathering discrete data about asset integrity issues (ie. corrosion, coating, structural).
• Supporting the integrity of inspection test equipment (ie. re-calibration).
• Collecting and cataloguing data, making it accessible to engineering for continuous improvement and planning.

Similar to EAM and integral to APM is the collection of a rich, strongly typed data set of asset condition information. Information collected by inspection plays an important role in the processing of complex rule algorithms that underpin asset performance management, providing predictions on “next inspection” frequency. The inputs or available data are typically from inspection programmes but also (as we look to the future) from more automated means such as IoT.

What are the benefits of digital inspection?

Digital inspection provides both quantitative and qualitative benefits.

Significant improvements in efficiency can be achieved by integrating work order management from the EAM with an asset-centric digital inspection platform. Man-hour savings of 50% or more are achievable across the lifecycle of an inspection:

• Preplanning for inspection is mostly a wasteful data-mining exercise to gather engineering data and previous inspection records. A digital system automates this process.
• Fieldwork is streamlined by ensuring all information and digital tools required by the inspector are available at their fingertips in a convenient viewport.
• Reporting with an integrated digital inspection platform means that as soon as the inspector completes the data capture in the field, the work order in the EAM is updated. Stakeholders can access real-time results and man-hours typically associated with report preparation can be re-allocated to more important value-adding tasks.

Even more important are the qualitative outcomes.

Before, we highlighted the EAM is harnessing inspection data to make it catalogued and accessible to engineering. In many EAM implementations asset condition data ends up in non-parseable flat files that are only loosely coupled with the original work order (ie. PDF inspection report). This is the reality for most EAM implementations. The data is hardly accessible.

Furthermore, paper-based approaches are non-standardised, they are typically a collection of subjective assessments with a value that is strongly aligned with seniority and experience. “Experience” that is extremely difficult to “resource” (in particular in a post-Covid marketplace). By standardising the process, less experienced field teams can benefit from the tribal knowledge that is quickly being lost as the more “qualified” hang up their inspection hats.

Integral to APM is the collection of a rich and strongly typed data set. It is through high-confidence data that accurate predictions can be achieved. Many APM systems provide first-class algorithms to predict future maintenance strategies however many are equally guilty of taking input from subjective manual inspection assessments. Digital inspections collect data with strongly typed forms that avoid the “garbage in, garbage out” scenario by removing subjective verbose assessments.

Digital inspection democratises data collected, providing a catalogued and accessible data set for all stakeholders, not just the inspection team. Downstream engineering, senior management, compliance, environmental, safety and statutory authorities can all leverage the data in real-time.

 

APM is focused on mechanical integrity whereas EAM has a much wider scope. A separate digital inspection platform provides the ability to simplify data collection and inspection management across a much wider range of maintenance activities and disciplines. With a single agnostic digital system you can achieve two important goals:

• Connect field inspection activities with work order management in the EAM; and
• Provide high-quality data inputs to APM rule engines

Finally, data collected by inspections is voluminous and this type of “digitally collected data set” can form the basis for future automation outside of the scope of current EAM and APM implementations. The potential for this data is significant and without collecting it we may lose significant future opportunities.

About Inspectivity

Inspectivity is an Australian SaaS company assisting operators, EPCs and service providers to collect rich asset condition data sets through digital inspection. The Inspectivity platform is a no-code software toolkit for the configuration of any asset-centric enterprise inspection use case. Combining modern web and mobile apps to connect global teams and supercharge inspection outcomes. Inspectivity’s approach to digital asset inspection provides a standardised, repeatable, and scalable inspection methodology to improve reliability, sustainability and quality control for critical assets. Delivering benefits across the full project lifecycle: design, construction, commissioning and operations. One solution for any project, phase of work, or inspection discipline.

If you would like to learn more about Inspectivity’s digital toolkit for the configuration and management of any asset-centric enterprise inspection use cases please contact us.

+61 (0) 8 6160 6060 sales@inspectivity.com