AI and machine learning can provide many benefits to business – but it must be deployed with a plan to realise its potential, as Alastair Nestor, comms lead at PaperCut, explains.
We’re at an interesting inflection point when it comes to machine learning and cloud management platforms, including print management. On the one hand, artificial intelligence (AI) can certainly help with automation, efficiencies and cost cutting (hear that excited murmur from HR). On the other hand, the industry does have a certain dot-com-bubble-wild-west-gold-rush-cum-snake-oil feel to it, where every SaaS operator is slapping ‘AI’ onto their product, whether it’s adding value or not.
The trick, like anything, is doing your research. Going in with a plan. Organisations that want to use AI for AI’s sake will likely overspend for little return, but if you shop around with clear metrics, and do your full procurement due diligence, machine learning platforms can certainly supercharge your cloud environment.
So, here’s our view on how you can enhance your cloud print management with AI and machine learning.
Machine learning supports predictive maintenance for printers
If you buy a modern MFD, chances are good it’s connected to IoT edge devices, which means it’s got more data-collecting sensors than the Death Star. Models equipped with machine learning systems can use this data to analyse usage trends and make predictions on when certain machines will fail, when faults may occur, or when consumables will need to be topped up. That’s good news for fleet operators, customers and field service engineers.
Machine learning allows print job optimisation
There are a few sides to this one. Machine learning is good at spotting patterns, which means it can forecast future printing needs. By identifying peak printing periods, AI can even schedule less critical jobs during quieter times to avoid congestion. Then there’s dynamic prioritisation. With the right configurations, AI can dynamically prioritise print jobs based on urgency or user roles, even making real-time adjustments to the print queue. Neat, huh?
Enhance security with AI-based threat detection
AI is a weapon in your cyber arsenal – but not a magic bullet. Used correctly, it’s a fantastic aid for spotting anomalous networks or printing behaviour. This includes the obvious stuff like unauthorised server access, but also unusual print volumes, device locations or document types. Machine learning tools can also analyse print job data for signs of malware, including any embedded malicious code.
Automate print supply management
Imagine never having to make another printer procurement request ever again. With real-time consumables tracking and predictive analytics, machine learning algorithms can automate the entire print supply management process, right down to ordering and replenishment. By integrating with vendor APIs, AI can predict a shortage, procure supplies and have them delivered, without IT ever lifting a finger. All you have to do is physically top up the machine.
Machine learning can also remember personalised print settings
The more you print with machine learning switched on, the better it knows your printing preferences. This might include stuff like paper size, colour settings, duplex printing and document formatting.
AI models will incorporate user feedback into these systems over time, becoming more accurate and refined, eventually applying personalised print settings for every user. This has a few benefits: it speeds up the print flow, minimises misprints and formatting errors and improves the overall user experience.
AI print services mean reduced waste
You might notice a common theme running through these features: efficiency. Cost cutting. Removing or reducing unnecessary printing. Only ordering and using the consumables you actually need. This is great for the printing budget, but it also helps cut down on paper use and e-waste, both of which are major issues in the printing industry.
Stats on this are hard to come by – widespread adoption of printing AI is still in its infancy – but in 3D printing, for example, it’s been shown that AI-based optimisation allows for one ‘free’ print after every 6.67 prints – just from materials that were previously wasted.
Analysing print usage patterns with machine learning
Using machine learning to analyse print patterns is great for users on a granular level, but it’s also fantastic for fleet managers and sysadmins, who need to make sure they’re using their print resources efficiently – and cheaply. By optimising print queues, and implementing AI-guided load balancing, there will be fewer bottlenecks and performance issues.
High volume printing can automatically occur during ‘off-peak’ hours. You can even tweak AI to enforce cost-saving policies like duplex or greyscale printing, quickly identifying departments or users who generate the most waste.
Improve tracking and accountability
This brings us back to the final benefit: improved accountability. By tracking all print activity across a network in real time, machine learning platforms offer fantastically detailed reports and audit trails. They also consolidate print job data into a centralised logging system, giving sysadmins and IT managers a bird’s eye view of their print environment.
Automated audit procedures cut down on man hours and will automatically flag any outliers in terms of wastage, print errors or suspicious network activity. Think of it like having a robot detective, constantly monitoring print flow.
