In 2024, the landscape of digital public services is undergoing a transformative shift driven by technological advancements that promise to enhance efficiency, accessibility, and citizen engagement. As public sector regulators increasingly rely on digital solutions for regulatory case management, three prominent technological trends are poised to redefine how these services operate: Artificial Intelligence (AI), Geospatial Technologies, and Extended Reality (XR). Drawing insights from the latest survey conducted by Socitm, the Society for Innovation, Technology, and Modernisation, this article delves into how these trends shape the future of digital public services, particularly in regulatory case management systems.

Artificial Intelligence (AI) Revolutionizing Case Management

AI has emerged as a game-changer in digital public services, offering unprecedented capabilities to streamline processes, improve decision-making, and enhance regulatory compliance. According to the Socitm report, AI-powered algorithms are increasingly integrated into case management systems, enabling regulators to automate routine tasks, analyse vast datasets, and accurately identify patterns or anomalies.

Related: Is it time to adopt an automated workflow within your inspection management system?

  • Automation and Efficiency Gains: AI-driven automation revolutionises case management workflows, reduces manual intervention, and expedites regulatory processes. By leveraging machine learning algorithms, regulators can automate repetitive tasks such as data entry, document classification, and compliance checks, allowing staff to focus on high-value activities that require human judgment.
  • Predictive Analytics for Smarter Regulation: AI-powered analytics empower regulators to anticipate emerging trends, detect potential risks, and proactively enforce regulatory compliance. By analysing historical data and real-time inputs, AI algorithms can identify patterns of non-compliance, predict regulatory violations, and prescribe targeted interventions to mitigate risks effectively.
  •   Enhanced Decision Support: AI-enabled decision support systems are augmenting the capabilities of regulatory professionals, providing real-time insights, recommendations, and risk assessments to inform decision-making. Whether assessing the severity of a compliance breach or determining the appropriate enforcement action, AI algorithms enable regulators to make data-driven decisions with greater speed and precision.

    Case study: Why the phased approach of adopting an inspection management software is a good tactic?

    Read it to understand:

      • The advantages of modular digital transformation
      • The vital architectural practices and technologies that enable modular transformation
      • How a regulatory agency in the UK is benefitting from a modular approach with Canalix.

    Geospatial Technologies Revolutionizing Regulatory Oversight

    Geospatial technologies, encompassing Geographic Information Systems (GIS) and Location Intelligence, are pivotal in enhancing regulatory oversight, spatial analysis, and geospatial data management. Socitm’s survey highlights the increasing adoption of geospatial technologies within public sector regulators, leveraging spatial data to improve regulatory enforcement and decision-making.

  • Spatial Data Integration: Geospatial technologies enable regulators to integrate spatial data layers into their case management systems, enriching regulatory insights with location-based information. By overlaying regulatory data onto interactive maps, regulators gain a spatial perspective of compliance activities, enforcement actions, and regulatory risks across geographic regions.
  • Spatial Analysis for Risk Assessment: Geospatial analytics empower regulators to conduct spatial analysis and geospatial modelling to assess regulatory risks, identify non-compliance hotspots, and prioritise enforcement efforts. By visualising regulatory data in a spatial context, regulators can identify spatial patterns, correlations, and spatial relationships that inform targeted interventions and resource allocation strategies.
  • Mobile Field Operations: Geospatial technologies enable regulators to leverage mobile applications and location-based services for field operations, inspections, and compliance monitoring. Equipped with geospatially-enabled case management tools, regulatory inspectors can access real-time regulatory data, capture geotagged evidence, and conduct on-site inspections more efficiently and accurately.

Related: The Importance of Contextuality in Effective Regulatory Oversight

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As we navigate the complexities of a rapidly evolving digital landscape, the convergence of AI, geospatial technologies, and extended reality reshapes the future of digital public services and regulatory case management. By harnessing the transformative potential of these tech trends, public sector regulators can enhance operational efficiency, improve regulatory outcomes, and foster greater citizen engagement in 2024 and beyond.

“The robots will replace humans and there will be no jobs for people”. In the distant past the unknown was a source for imagining evil powers that threaten everything that humans created. Today the new technologies serve as the new unknown and we create myths about them too. The myths have always been here to help us invent villains. But with more knowledge at our hands, we also got better at debunking them.

AI technologies are making its way in all levels of governments and enterprises today. That’s why it’s more and more important for CIOs to understand the value of AI without making wrong assumptions, based on myths. Are you ready to bust a few myths about AI with us?

Let’s start with myth #1:

AI can replace human thinking?

Artificial intelligence is called artificial for a reason. It can replace human intelligence up to a point. AI can learn how to execute tasks, but if the conditions of this task change, then AI will fail. To say that AI will replace human thinking sounds more like a Terminator movie plot and less like reality.

AI can learn things independently of human touch

AI technologies do not learn on their own. They need human control. The AI needs updates, constant integration of new knowledge, etc. That’s why when choosing an AI boosted software service, CIOs must pay close to attention to the technological state of the product they will use.

Related: Guide for finding the best inspection management software

AI makes decisions independently of humans

AI is data & rules-driven technology. Rules are defined by human experts. While the AI can independently solve simple tasks, based on pre-defined rules, sometimes there is complexity that is far beyond the capacity of AI. This is where human involvement is needed. We have a perfect example for the way AI can transfer the decision-making to a human party:

Let’s imagine that a citizen is filing an appeal for review to a government agency that is governing the field inspections. While the citizen files the data of his appeal on the front-end of the Agency’s website, on the back-end an AI is trying to categorise the complexity of the case based on the gathered data.

With a well defined set of rules, the AI would be able to set a relevant complexity score. If the case is too complex (above certain score) it will be send for review by human. If the case is simple enough for automatic processing through the AI, then it will be automatically allocated to an inspector and the inspection scheduling and execution will happen in the most optimal way.

Related: Learn more about inspection management and AI complexity score

We worked so far so good, so we don’t need AI

AI is not a magic that will instantly improve the business outcomes within an organization. Whether your company needs or does not need AI, it should be a decision based on data. In other worlds, every CIO must be able to answer why his organization does or does not need AI.

Having visibility on technologies and knowing how they can or can’t help on the strategy of the organization is important. The business needs are ever evolving and the decisions that are made today may not apply for tomorrow’s technological landscape. That’s why no matter where a government agency or an enterprise may stand in terms of adopting AI, they must have their research done.

Debunking myths is easy. Staying always alert to how technologies evolve is hard. Do you want to follow what’s new with AI and inspection software? Sign up for our newsletter.

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It’s halfway through 2020 and so many things happened so far. With the rapid changes in the work culture all around the world, Lewis Carol’s famous quote from Alice, “we must run as fast as we can, just to stay in place” rings specially true. From the insights the many enterprises and governments around the world are giving, these new changes are here to stay. Or said otherwise: the new work models are here to stay. The sooner companies and organization come up with optimized solution for their new work routines, the better outcomes they may expect in case of a second wave of covid-19 outbreak.

Related: SaaS Inspection Platforms – The Solution for Regulators and Enterprises After Covid-19

The benefits of AI in compliance management are nothing new for big enterprises. In the past few months of dynamic changes enterprises started appreciating even more the value of AI in compliance management. But for conservative organizations like government agencies, the level of adoption of technologies like AI in the inspection model is not the same. With the growth of interest towards inspection software solutions, grows the number of questions that decision makers on digital transformation in government agencies are asking.  So here are 4 frequently asked questions that we prepared for them.

1. Why use AI in inspection management and not stick to the old manual way of inspections?

The old ways are the gold ways. But not always. When unprecedented changes happen outside the organization, the old ways may turn into annoying limitations. So is the case with the manual inspections. They require a human judgement for every step of the inspection process. It is great to have the resource to designate a human to make judgement on complex cases. But in a future where the work from home model is the new normal, the manual way is no longer an optimal way for inspections. That’s why it’s great to have technologies like AI that can turn even complex processes into faster and better version of themselves.

Related: The Complexity of Inspection Management Made Simple

2. How expensive it is to use AI in inspection management?

The use of AI in inspections is supposed to lower the costs of government agencies. There are two big reasons for that. The manual inspections require the time and efforts of multiple specialists with different level of competence. While AI can take over complex processes like the allocation of cases to the right inspectors and reduce the operational time from days to hours. And this is not the best of it. Thanks to a sophisticated complexity scoring mechanism, Canalix’ inspection management system is looking for the most optimal scenarios where resources like transportation expenses can be utilized more efficiently. So the only thing that AI in the inspection model can do to your company’s expenses is to lower them.

Related: How Can AI Transform Inspections?

3. Is it really a good idea to trust a machine with the inspection process?

Thanks to the popular culture, the collective conscious is constantly associating the archetype of robots that take over control over the humans with AI. However, when we talk about AI in inspections, we don’t talk about movie robots. We talk about smart technologies, build by other humans that are designed to make the work process smarter. Since inspection management is a complex matter, sometimes the human judgement is necessary. That’s why the AI of Canalix is build to be smart enough to send cases that are above certain complexity to humans.

4. How to get started with using AI in inspections and compliance management?

If you’re looking for inspection software that offers AI optimization, contact us now. We will tell you more about our product. You can even get to test it. Learn more about the importance of testing a demo of inspection software.

Artificial intelligence has been used in many industries for business optimization purposes, including the field of inspection management. The need to improve productivity and efficiency is very visible in this field. This is a conservative area where changes happen slow. However, the new reality of the post pandemic world is about to change that and make some changes happen faster than before.

On June 23rd took place the Virtual AI Summit of Microsoft where the main topic was “How AI can empower your organization?”. During the event Mitra Azizirad (Corporate VP of AI and Innovation Marketing in Microsft) talked about imagining a future where AI-driven automation is an everyday part of our business lives. This main topic and the fact that the event was entirely digital strengthen the message of the virtual event: that now is the time to get in line with the future that is being reshaped in front of our eyes.

How to build an AI-powered organization

We already talked about the growth in the use of cloud-based SaaS services as a result of the pandemic. Of course, it is a very general conclusion and if we look at different technologies, we will see more layered and complex transformation happening under the brand of Cloud-based solutions. The question that we will focus on in this article is how AI as a technology can help to improve efficiency in inspections?

Related: Cloud Inspection Solutions – The New Normal For Regulators and Enterprises After Covid-10

How can AI transform the inspections in your company?

During the event Azizirad mentioned that AI is transforming organizations in three major directions: operations, productivity and customer service. If we look at this notion through the prism of our inspection management tool Canalix, we can easily say that AI is transforming regulators and enterprises in the same directions:

  • Operations -> reducing the risk of mistakes in inspections
  • Productivity -> increasing the speed of communications and processes in inspections
  • Customer service -> providing government agencies and enterprises with self-service portals, which are great for gathering data and keeping social distance rules at the same time.

Related: The Complexity of Inspection Management Made Simple

Another point that Azizirad touched is the actual benefits that some businesses have measured after transforming their manual processes via data automation. Her figures showed that up to 25% increase in employee productivity is being brought with data-automation. This is a metric that’s hard to be measured, but when we talk about covering entire end-to-end process like inspection management, a projection that can be made in the very initial phase of testing the product.

Related: 5 Benefits of Using Inspection Management Software in 2020

“The ability to integrate AI into the fabric of your business is what is going to accelerate the value you get from the technology – and where we see the leaders differentiate from those that are struggling”, Azizirad.

Do you want to learn more about transforming your company with AI inspection? Contact us.

One of the first association one has when hearing about inspection planning is complexity. What comes to the imagination is a big complex structure with a lot of processes going on in the same time. To some it may looks scary and impossible for optimization. However, that is not entirely true. Canalix is a product that is dedicated to making inspection management simple. That’s why we wrote this article to explain how things really are working in an inspection management platform like ours.

What is inspection management?

Inspection management is series of operations that are more complex than business process management. They are more unpredictable because they involve cases, which very often have a complex structure and relationships with other cases and processes. While automating a simple business process is easy, because we have pre-defined steps, automating cases is the harder thing to do. It’s hard because if we automate case-based process (such as the inspection management), we need to automate possible scenarios involving human judgement. If it was a video game, automating business process will be level 1, while automating a case process will be the final level.

Related: Read more about the difference between case management and BPM

And so we come to the burning question:

How to automate inspection planning that usually need human judgement?

Let’s imagine that a citizen files a complaint to a state regulator via self-service web portal. After describing the issue, the citizen has to complete a quick questionnaire about the nature of his case. Depending on the answers, the case is being profiled within a category of complexity.

Related: Why Self-Service Portals in Government Agencies Matter?

Now let’s imagine that there are hundreds of other cases. Each with different complexity level and only dozen of inspectors that can do an inspection. If every inspector has a unique skill set, then the matching of cases with inspectors should be done very precisely. So how should we approach the inspection planning and allocation without making costly errors?

Precision takes time when done manually. By looking at this complex picture, one would think that it will take an eternity to finish each case. It is partly true. But not if inspection management platform like Canalix is processing this complex model of work.

Related: Five Benefits Of Using Inspection Management Software in 2020

Are cases allocated automatically after receiving data from self-service portal?

The short answer is yes. Thanks to a pre-defined set of rules, Canalix is scoring the complexity of each case. It means that once a citizen submits the data for his own case, the inspection platform starts moving the case through the inspection pipeline. This movement includes the matching of the case with relevant inspector. And this is not the best of it. By defining a priority score and using different options for constraints, the inspection scheduling and planning can be done in the most optimal way. It means not only that cases can be allocated to the right inspector without making a mistake, but also allocated in a way that is more optimized in terms of resource utilization (for example reducing the costs for transportation).

The power of artificial intelligence is making big difference by allowing us to work smarter than before. That’s why AI is one of the main technologies that stands behind our inspection management software. It is literally a technology that can replace the need of human judgement.

Related: The Benefits of AI in Inspection Software

Replacing entirely human judgement sounds scary and uncomfortable for more conservative business environments. This is where another perk of using inspection management solution like Canalix comes. When a case has a high complexity score, the inspection platform sends it for control by real human. In other words it means that the inspection software is smart enough to judge when a case needs to be processed manually by human.

Is specific technical knowledge needed to automate inspection planning?

The short answer is no. Simplifying complexity runs on every level in Canalix. It includes the usability of the software. With simple and minimalistic user experience everyone with general technical knowledge can use Canalix.

Related: How Inspection Scheduling Is Being Optimized With Canalix?

Describing how the complex structure of inspections can be automated is not always the best way to demonstrate how inspection optimization platform works. This is why you can book a live demo with us. Contact us here.

Do you want to know more about the benefits that inspection software like Canalix can bring to your organization?

• Up to 75% of submissions can be processed automatically and up to 60% reduction in process time
• Up to 50% reduction in inspection report writing time
• Up to 40% reduction in total travelled distance
• Planning of inspectors reduced from days to seconds
• No wasted time by wrongly skilled inspectors send on-site

Read more here.

If we look at the public sector as a regular business, we’ll see two sides – service providers and customers. So when we talk about business optimisation in government agencies, we talk about service providers – the public organisations that ensure regulatory compliance, and customers – the citizens and the entities subject to regulations. As in businesses, the optimisation path often goes through the workforce’s operations in regulatory agencies. It usually starts by updating the legacy case management system with purpose-built regulatory case management software.

What is case management?

Before we describe the regulatory case management module of Canalix, let’s go through Gartner’s definition of case management:

Case management solutions are applications designed to support a complex process requiring a combination of human tasks and electronic workflows, such as an incoming application, a submitted claim, a complaint, or a claim moving to litigation. These solutions support the workflow, management collaboration, storage of images and content, decisions, and processing of electronic files or cases.

RelatedCase management vs BPMS – what is the difference?

Canalix is an advanced inspection management software focused on delivering various digital transformation solutions to the public sector. One of our main objectives is to transform how the regulators’ workforce is operating. That is realised with the case management system of Canalix.

Canalix supports a fully self-sufficient government case management software by managing gathered data, documents, processes, and configurable rules on a single platform. The automated process allows fast and reliable scoring and categorising inspection cases, appeals and complaints. This digital infrastructure empowers the employees to improve their work and make better decisions.

AI optimisation can turn the decision-making process into a better version of itself. For example, by using Canalix, regulators can automatically match cases with inspectors based on:

  • Specialities
  • Complexity level
  • Distance
  • Availability
  • Preclusions

This AI optimised process eliminates the possibility of error by matching cases with a wrongfully skilled inspector. Using regulatory case management software can drastically improve the way regulators operate. The upgrades are measured in the efficiency of the workforce’s operations and by the reduced operational costs.

Read more about case management systems as part of the digital transformation in government agencies.


The traditional vs the modern is a conflict as old as the world. It has an obvious implication for the public sector’s inspection-driven enforcement activity. This conflict is formulated in the regulatory environment like digital inspection solutions vs old traditional inspection methods.

The regulatory bodies that use traditional inspection methods face an expensive and clumsy process. The nature of inspections is always, to some degree, risky for the success of the whole operation. This risk can increase the cost of the inspection process. For example, there could be a mistake in allocating cases, allowing wrongfully skilled inspectors to be sent on-site or another error that could impact the inspection cost.

We’ve already looked through various success stories of regulators that transformed their inspections with different levels of inspection automation. They are winners on the side of the modern and successful regulatory tech adopters. Inspection automation technologies are doing their magic on different levels simultaneously. We already talked about how data automation is a basic level of operation for the inspection software. In this article, we will look through automated AI inspection optimisation as another feature that is a game-changer for inspection driven regulatory enforcement.

Related: How real-time data can improve the inspection performance?

Case study: Reduce operational costs with inspection scheduling software

Read it to understand:

    • The advantages of modular digital transformation
    • The vital architectural practices and technologies that enable modular transformation
    • How a regulatory agency in the UK is benefitting from a modular approach with Canalix.

So, how is AI changing the game?

AI optimises the resource utilisation in inspections

Artificial Intelligence can design the most optimal ways for inspections. It can learn from the existing data and eliminate mistakes like sending wrongfully skilled inspectors on-site or planning routes nonoptimal ways. According to the user data of Canalix, AI optimisation can bring up to 40% better resource utilisation.

AI enables more efficient data flow

When the amount of data is managed intelligently, the business operations improve. Even if there are potential issues, they can be evaded before affecting the outcome. The bottom line is that AI can shrink the costs of inspection.

AI eases the decision-making process

The reduction of process time is like the elephant in the room when we talk about digital transformation. So it is with the AI-driven inspection platforms. The system’s intelligence can take into account different factors simultaneously and eliminate unnecessary work. This improves efficiency, and decisions are made faster at the end of the day. The benefit goes to one individual who is directly involved in the inspection process and the whole inspection ecosystem.

A good business optimisation tool will give regulators the digital infrastructure to do their job better. An excellent inspection platform will bring data automation and AI optimisation. Combine it with a great UX, and a regulator will have a disruptive technology in their hands.

Do you want to try how Canalix can optimise regulatory inspections? Contact us now.

Bonus definition of AI by Salesforce:

Artificial Intelligence is the concept of having machines “think like humans” — in other words, performing tasks like reasoning, planning, learning, and understanding language.

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