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The AI Advantage: How Artificial Intelligence Is Revolutionising Parking Management – Finance Monthly

We live in an era that is increasingly becoming more and more defined by AI. it’s being utilised by almost every industry, making the way we do things and live our lives that bit easier. And one industry that isn’t missing out on this, is parking. In fact, artificial intelligence is revolutionising parking management in a big way.
Parking remains one of the most visible yet under-optimised city assets and constant pressure is placed on facility managers, councils and private operators to make car parks more efficient, have a greater level of customer satisfaction, but also cut costs. Which can feel like a bit of a minefield. Until now. AI technologies are helping in a myriad of ways, from dynamic pricing, to real-time space allocation, parking management systems and number-plate recognition.
It’s making it easier to generate revenue, to enhance customer experiences and measure improvements that are made. In this article we take a look at how AI is reshaping the future of parking management and what you can do as a B2B stakeholder to implement it as successfully as possible.
The core AI technologies powering smart parking
There are three main technologies at the foundations of AI-driven parking systems. These are machine learning, computer vision and predictive analysis. Each of them play their own key role in bringing parking into the future.
Machine learning models are trained using both live and historical parking data to spot patterns, trends and anomalies. Using this, they can learn peak and off-peak behaviours, identify if people have overstayed their parking allocation, automatically suggest changes to pricing and support fraud much more accurately. As the model ingests more and more data over time, it effectively ‘learns’ and its predictive accuracy and operational value increase.
Computer vision which is powered by an AI algorithm, enables images and video feeds to be analysed. Some ways this can happen is with automatic numberplate recognition (ANPR) for a much smoother entry and exit process (it can also negate the need for paper tickets, being better for the environment.) It can identify open and occupied bays, detect illegal parking and see vehicle classification, for example, identifying commercial or private vehicles.
The third, predictive analysis, does what the name suggests and forecasts future behaviour. It does this based on trends, seasonality and external variables such as the weather, events and traffic at certain times like rush hour. These predictive models can help you to optimise resource planning such as how many staff are needed, or when maintenance might be needed. It can also adjust dynamic pricing in real time, manage high-demand periods and inform long-term investment in EV bays or alternative transport hubs.
What are some real-world cases already being used?
If you are a driver, chances are you have already seen (or used) some of these systems though you might not have been aware. Dynamic space allocation is one of the main ones, for example AI can dynamically reassign EV bays based on expected usage, or delivery zones can expand or shrink based on parcel traffic. This can help to optimise the space utility and make it more useful for those that need it.
ALPR or automated licence plate recognition as mentioned already above, has been in use for a while now. Some of the main benefits of this include reduced entry/ exit congestion as vehicles don’t need to stop and put tickets into a machine, accurate time stamped evidence for enforcement, improved accessibility for disabled drivers who don’t need to reach ticket machines and seamless integration with payment platforms or mobile apps. In essence, it makes the process much more simple.
Demand forecasting and pricing strategy is another method that has also been used for a while and sees operators use historical data to forecast demand for certain time slots. They will then adjust pricing accordingly, for example reducing prices in off-peak hours and at weekends.
What are the key benefits for operators and facility managers?
Artificial intelligence-enabled parking solutions deliver considerable value in operational, financial, and customer-facing areas. Automating enforcement, monitoring space, and predictive maintenance frees up considerable manual overhead and improves operating efficiency. Financials are also optimised via dynamic pricing, increased occupancy rates, and enhanced enforcement success, while underutilised assets are uncovered through real-time analytics for monetisation. For customers themselves, AI enhances the experience by delivering barrier-less entry and exit, providing accurate space availability, and convenient wayfinding. This reduces stress and enhances satisfaction. Plus, smarter space use and idling reduction makes it more sustainable, so AI is a double win for performance and environmentally too.
Calculating ROI: A Simple Framework
When assessing the return on investment (ROI) of AI-powered parking systems, consider things like the occupancy rate and how AI can improve this, the revenue per space, per day, the enforcement success rate, manual patrol costs and how AI can reduce the dispute rate. Typical ROI horizon tends to be 12 to 18 months, depending on scale, pricing strategy, and infrastructure complexity.
3-Step Roadmap to Pilot an AI Parking Solution
For facility and operations leaders looking to adopt AI in parking, a structured pilot approach ensures minimal risk and measurable results.
Step 1: Identify Pilot Site(s)
- Select high-traffic or high-conflict locations
- Ensure data collection capabilities are in place (e.g. cameras, sensors, transaction logs)
- Define baseline KPIs: occupancy, revenue, dispute frequency, user feedback
Step 2: Select a Technology Partner
- Look for industry experience, system modularity, and integration readiness
- Ensure GDPR compliance and support for multi-vendor ecosystems
- Request pilot frameworks and real-world case studies
Step 3: Deploy, Evaluate, Scale
- Run a 60–90 day pilot with clearly defined KPIs
- Monitor performance weekly and collect user feedback
- Adjust pricing, rules, or system configurations iteratively
- Present results to stakeholders and secure budget for wider rollout
AI isn’t just something that’s far off in the future, it’s here now and it’s already solving problems when it comes to car parks. From boosting revenue to reducing congestion and enhancing customer experience, the business case for intelligent parking management is increasingly hard to ignore. Companies need to adapt to this technology or fall behind.
AI Research
‘AI Learning Day’ spotlights smart campus and ecosystem co-creation

When artificial intelligence (AI) can help you retrieve literature, support your research, and even act as a “super assistant”, university education is undergoing a profound transformation.
On 9 September, XJTLU’s Centre for Knowledge and Information (CKI) hosted its third AI Learning Day, themed “AI-Empowered, Ecosystem-Co-created”. The event showcased the latest milestones of the University’s “Education + AI” strategy and offered in-depth discussions on the role of AI in higher education.
In her opening remarks, Professor Qiuling Chao, Vice President of XJTLU, said: “AI offers us an opportunity to rethink education, helping us create a learning environment that is fairer, more efficient and more personalised. I hope today’s event will inspire everyone to explore how AI technologies can be applied in your own practice.”
Professor Qiuling Chao
In his keynote speech, Professor Youmin Xi, Executive President of XJTLU, elaborated on the University’s vision for future universities. He stressed that future universities would evolve into human-AI symbiotic ecosystems, where learning would be centred on project-based co-creation and human-AI collaboration. The role of educators, he noted, would shift from transmitters of knowledge to mentors for both learning and life.
Professor Youmin Xi
At the event, Professor Xi’s digital twin, created by the XJTLU Virtual Engineering Centre in collaboration with the team led by Qilei Sun from the Academy of Artificial Intelligence, delivered Teachers’ Day greetings to all staff.
(Teachers’ Day message from President Xi’s digital twin)
“Education + AI” in diverse scenarios
This event also highlighted four case studies from different areas of the University. Dr Ling Xia from the Global Cultures and Languages Hub suggested that in the AI era, curricula should undergo de-skilling (assigning repetitive tasks to AI), re-skilling, and up-skilling, thereby enabling students to focus on in-depth learning in critical thinking and research methodologies.
Dr Xiangyun Lu from International Business School Suzhou (IBSS) demonstrated how AI teaching assistants and the University’s Junmou AI platform can offer students a customised and highly interactive learning experience, particularly for those facing challenges such as information overload and language barriers.
Dr Juan Li from the School of Science shared the concept of the “AI amplifier” for research. She explained that the “double amplifier” effect works in two stages: AI first amplifies students’ efficiency by automating tasks like literature searches and coding. These empowered students then become the second amplifier, freeing mentors from routine work so they can focus on high-level strategy. This human-AI partnership allows a small research team to achieve the output of a much larger one.
Jing Wang, Deputy Director of the XJTLU Learning Mall, showed how AI agents are already being used to support scheduling, meeting bookings, news updates and other administrative and learning tasks. She also announced that from this semester, all students would have access to the XIPU AI Agent platform.
Students and teachers are having a discussion at one of the booths
AI education system co-created by staff and students
The event’s AI interactive zone also drew significant attention from students and staff. From the Junmou AI platform to the E
-Support chatbot, and from AI-assisted creative design to 3D printing, 10 exhibition booths demonstrated the integration of AI across campus life.
These innovative applications sparked lively discussions and thoughtful reflections among participants. In an interview, Thomas Durham from IBSS noted that, although he had rarely used AI before, the event was highly inspiring and motivated him to explore its use in both professional and personal life. He also shared his perspective on AI’s role in learning, stating: “My expectation for the future of AI in education is that it should help students think critically. My worry is that AI’s convenience and efficiency might make students’ understanding too superficial, since AI does much of the hard work for them. Hopefully, critical thinking will still be preserved.”
Year One student Zifei Xu was particularly inspired by the interdisciplinary collaboration on display at the event, remarking that it offered her a glimpse of a more holistic and future-focused education.
Dr Xin Bi, XJTLU’s Chief Officer of Data and Director of the CKI, noted that, supported by robust digital infrastructure such as the Junmou AI platform, more than 26,000 students and 2,400 staff are already using the University’s AI platforms. XJTLU’s digital transformation is advancing from informatisation and digitisation towards intelligentisation, with AI expected to empower teaching, research and administration, and to help staff and students leap from knowledge to wisdom.
Dr Xin Bi
“Looking ahead, we will continue to advance the deep integration of AI in education, research, administration and services, building a data-driven intelligent operations centre and fostering a sustainable AI learning ecosystem,” said Dr Xin Bi.
By Qinru Liu
Edited by Patricia Pieterse
Translated by Xiangyin Han
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Philippine businesses slow to adopt AI, study finds – People Matters Global

Philippine businesses slow to adopt AI, study finds People Matters Global
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Examining Tim Draper’s AI digital twin program – NBC Bay Area

Remember a hologram of Tupac Shakur that made headlines back at Coachella in 2012?
It was a digital creation made to sing along on stage.
Now imagine a similar hologram, but one that can use artificial intelligence to bring us all the experience and knowledge in someone’s life — in this case, a well-known Silicon Valley venture capitalist.
“It’s going to change the way we think about the world, and we’ll evolve with it,” venture capitalist Tim Draper said.
A digital twin has been created of Draper. The so-called twin is a hologram using AI to scan everything about Draper.
The twin can answer questions in multiple locations at once and Draper’s twins are currently installed at Kennedy Airport in New York and at a Midwestern University.
Still, the twins have some learning to do as they still get the occasional question wrong.
The box holding one of the twins is reportedly about $100,000 each.
Draper is so known and regarded in tech circles that he has his own university, where the Silicon Valley venture capitalist now mentors young entrepreneurs.
One of the many things Draper has invested in deeply is AI after making a splash with some other big name investments like Tesla and Robinhood.
“You’re seeing the excitement period of an industry being created,” Draper said. “We’re in that period of elation. Where wow, it’s blowing my mind.”
Draper is now offering some very simple advice to young techies to make sure they have the right skills to stay employed in the shifting Silicon Valley landscape.
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