AI: from nice to have, to necessity

AI technology is dominating conversations across the globe. In the last few months alone, we have seen industry-leading technology events like Gitex declare 2023 the โ€˜Year of AIโ€™; the Collins dictionary named โ€˜AIโ€™ as its โ€˜word of the yearโ€™; and we have celebrated ChatGPT turning one.

If 2023 was – as Gitexโ€™s theme suggested – โ€˜the year to imagine AI in everythingโ€™ – it certainly has been the year for AI investment. Early on this year, the UK government announced a ยฃ100 million fund to help the UK build and adopt AI, and according to the US International Trade Administration, the UK AI market is worth more than ยฃ17 billion and is expected to rise to ยฃ800 billion by 2035.

It is undeniable that the proliferation of artificial intelligence has exploded in enabled systems and software industries worldwide โ€“ and for businesses operating fleets of vehicles and equipment, this is no different. Across sectors including construction, logistics and deliveries, the benefits of AI are broad and multifaceted: AI promises to revolutionise operational efficiency, safety protocols and the overall sustainability of fleets across the globe.

But how can businesses in these industries gain their customerโ€™s trust in a technology that has had its fair share of mixed media commentary?

Realising the benefits of AI in fleet management

Imagine owning a crystal ball which offered granular insights into the journey you were about to make – from route planning and timing, right down to the last drop of fuel you would use. We are close to this reality, and managers of fleets operating multiple vehicles – such as delivery trucks, or construction equipment – are not far off realising just how beneficial AI can be.

By harnessing the power of AI-driven predictive analytics and machine learning algorithms, there are three major areas that could benefit the most:

Route optimisation: businesses are able to streamline their route planning processes, minimise delivery delays and optimise overall fleet performance. For example, AI-enabled predictive models can effectively anticipate traffic patterns, weather conditions, and other variables to provide real-time route recommendations, enabling companies to ensure timely deliveries, and ultimately, enhance customer and user satisfaction.

Fleet safety and security: AI presents unparalleled opportunities for enhancing fleet safety and security through the implementation of advanced driver monitoring systems and predictive maintenance protocols. By leveraging AI-powered sensor tech and data analytics, fleet managers can gain comprehensive insights into driver behaviour, vehicle performance, and maintenance requirements. This enables the fleet managers to proactively identify potential risks, minimise accidents, and optimise vehicle uptime. An example of this would be driver-facing AI cameras which detect high-risk or unusual behaviours, alerting both the driver and the fleet manager to potential driver fatigue or distractions which could result in an accident.

On top of this, AI-driven predictive maintenance systems can detect potential equipment failures and schedule timely maintenance, reducing vehicle downtime and ensuring the safety of drivers, assets, and cargo.

Promote sustainability: High on the C-level agenda is sustainability, and there’s a huge opportunity for AI-powered energy management and sustainability metrics in fleet management that promote eco-friendly operational practices. Organisations can identify energy-efficient routes, implement fuel-saving strategies, and adopt environmentally conscious supply chain practices. This will help to reduce carbon emissions and contribute to a more sustainable and environmentally responsible fleet management ecosystem.

Overcoming challenges in AI adoption

As with all new technologies and software, the integration of AI into fleet management systems follows a multi-stage process, and initial adoption can present certain challenges.
While the benefits of AI are extensive, it is important to acknowledge potential drawbacks. Ensuring the accuracy and reliability of AI-generated insights is critical. In the context of fleet management, where decisions impact operational efficiency and driver safety, the precision of AI-driven analytics is paramount. Fleet managers need to ensure the partners they are working with are dedicated to developing AI solutions that undergo rigorous testing and validation to ensure accurate insights are provided for their users.

Maintaining the privacy and integrity of sensitive information within the fleet management ecosystem should also be a top priority. Some software partners will have implemented robust security protocols and data encryption measures to safeguard the information of users and their fleets.

So, whatโ€™s next?

The benefits of AI within fleet management are far-reaching and have the potential to completely redefine the operational landscape. By embracing artificial intelligence, industries such as logistics, construction, and haulage amongst others, can unlock new avenues for operational optimisation, safety enhancement, and sustainability. This can help form the backbone of further innovation in fleet management.

Businesses that are either actively working on the implementation of AI or with an anticipated rollout of AI-driven functionalities in 2024, need to focus on delivering data protection and privacy as the foundation for building trustworthy and secure AI-driven fleet management systems. This commitment to exploring innovation whilst keeping employeesโ€™ and customersโ€™ security and safety as a top priority will foster confidence and peace of mind for all.

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Aliaksandr Kuushynau is the Head of Wialon at Gurtam, an international developer of Wialon, one of the worldโ€™s largest platforms for GPS tracking and IoT. Being a flexible and multifunctional system, Wialon helps deliver any telematics project of any scale and for any industry.

Aliaksandr joined Gurtam in 2009 as the Chief Marketing Officer. In his current role, Aliaksandr directs the entire Wialon division. He is responsible for building product development and commercial strategy, strategic and tactical planning, as well as coordination of all departments within the Wialon division and communication with key customers.

Over his career at Gurtam, Aliaksandr has built and managed a global high-performance team of software development, marketing, sales, and business development professionals. As an accomplished executive with 18 years of overall experience in management, Aliaksandr has ensured leadership for Wialon, Gurtam's flagship product, and pioneered the largest global community of telematics and IoT professionals.

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