Maximising the benefits of AI in transport


Tom Cummins and Viraf Avari, customer experience and operating model experts at PA Consulting, ask: How can transport organisations deliver excellent customer experience enabled by their operating model and AI?

Customer satisfaction is at an all-time low for many organisations. Some sectors have been impacted worse than others, with transport faring among the three worst performers in the UK, according to recent research.

Tom Cummins

Against this context, the growth of AI technologies poses opportunities for transport organisations to deliver improved reliability, safety and more personalised services to help improve satisfaction.

However, this will only be achieved if the customer outcome is positioned as a key priority. AI's adoption is inevitable but to realise its potential and maximise the impact, this must be aligned to the strategic outcomes of the organisation and designed with the customer in mind.

There are three steps transport organisations can take on their journey to becoming more customer-centric, ensuring AI helps enable an improved customer experience whilst having a focus on the right organisational capabilities to support it.

1. Understand how customers interact with AI across their end-to-end experience

Customers are having fewer person-to-person contacts through their experience with many organisations. At the same time, there is a growing appetite for more person-to-person interaction, with growing expectations on organisations to have ever greater understanding of their needs as a customer.

In response to this, a customer journey map that plots AI use cases applicable to each stage of the experience can help organisations understand where customers are interacting with AI and where they could in the future.

Equally, by understanding the possible applications of AI throughout each stage of the end-to-end journey, this new level of insight can help transport organisations deliver a more joined up experience and begin to consider the ‘art of the possible’, of what might be most valuable for both their customers and the organisation.

2. Use the AI customer journey assessment to unlock opportunities and mitigate risks

A recent survey identified that over half of customers are engaging a person after interactions with AI or a chatbot (UKCSI, 2024). While customer knowledge of how to get the best from AI technologies and the technologies themselves are both evolving, it can create a disjointed experience.

Viraf Avari

Whether engaging with AI, a chatbot, or a human customer service agent, customers desire quick, simple and personalised interactions that lead to a successful outcome.

By considering the end-to-end experience, organisations can build a further level of detail into the customer journey map to overlay the opportunities and risks of implementing AI from the perspective of the customer.

This approach, done with a sufficient level of detail, will give organisations a clearer understanding of customer pain points to mitigate, and customer gains to capitalise on.

This can help determine the optimal balance of where customers are open to interacting with AI to augment service levels and where actual person-to-person interaction is critical.

In so doing it is important to draw on the vast amount of data that is being gathering both from the customer and the infrastructure, with an increasing level of interaction with AI.

3. Align AI-enhanced customer experiences with an understanding of required organisational capabilities

Intelligent transport enterprises are seeking to combine technologies with deep human insight to create radical new futures. Investment in AI alone is not sufficient. To ensure the enterprise is truly customer-centric and set up to embrace AI, there is a renewed imperative to focus on the operating model and ensuring the change is underpinned by the right organisational capabilities.

This should include three key areas. Firstly, which resources – including the people and skills, technology, and infrastructure – required to deliver on the desired experience.

Secondly, how to organise across process, culture, leadership, and governance to successfully deliver AI opportunities through the customer experience.

Finally, consideration should be given to the right mix of sourcing, whether in-house, partners, and collaborators required to deliver most effectively.

Transport industry leaders who consider these three key aspects of their customer-centric operating model have the opportunity to ensure that their organisation can exceed the desired customer experience, whilst evolving it to effectively embrace AI.

AI and emerging technologies offer real opportunity to improve customer experience in the transport sector, but focus must be given to the value, opportunities, and risks.

Tom Cummins and Viraf Avari are customer experience and operating model experts at PA Consulting

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