Many types of AI capabilities are accelerating in recent months as analytical AI and generative AI (gen AI) techniques become more sophisticated.
The Different Types of AI
Analytical AI enables machines to analyse vast amounts of historical data to make predictions, whereas generative AI (gen AI) like ChatGPT for example, generates new outputs that are like human-generated content.
In its recent report – “The journey toward AI-enabled railway companies” – MicKinsey found that railway companies have already begun implementing various AI technologies for circa 20 use cases.
They also found that greater adoption could unlock an estimated $13 billion to $22 billion in annual global impact.
While the range of potential applications is substantial, AI is just an emerging trend in the rail industry.
Only a few rail OEMs and railway service providers (about 25%) have implemented multiple use cases at scale.
Another 35% have one or two use cases at scale, with other use cases still at the pilot stage.
Very few of these early adopters have implemented any kind of AI at scale with success.
Current efforts are mostly focused on a few analytical AI use cases targeted at their business priorities relating to KPIs of on-time performance, customer engagement, safety and operational performance.
SEE ALSO: The Essential Guide To Aftermarket Growth
Use Case Maturity
Just like other industries, adopting digital/AI technologies has been a challenge for the rail industry too due to issues with data availability/quality, industry regulations and a lack of agreed standards.
That said, for those looking to get ahead of their competitors, digital/AI transformation provides companies throughout the railway value chain with a golden opportunity to differentially enhance their customer service experience.
Use cases largely focus on non-safety critical functions and are usually advisory, with a human being involved with decision making…
1. Service Delivery and Travel Experience
This involves managing railway and train transportation services that are directly and indirectly related to delivering the travel experience.
The most mature analytical AI use cases involve train crew optimisation, shift planning and energy efficiency for train scheduling and planning, operating train stations and predictive maintenance of rolling stock.
Others in the pilot phase include use of semi-autonomous and driverless trains, onboard operations and services, safety improvements, crew training and traditional logistics areas like demand forecasting, inventory planning and procurement of aftermarket parts and equipment.
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2. Infrastructure Management
This encompasses planning, operation and maintenance of the physical infrastructural components of rail networks including tracks, stations and signalling systems.
The most mature use cases focus on network planning and optimisation, infrastructure crew and shift optimisation, network slot allocation, traffic management and predictive maintenance of rail network infrastructure.
Other good examples include advisory tools with the ability to detect and warn about animals that are on or near the track and remote condition monitoring of signalling equipment, track, etc. to prevent infrastructure failures.
3. Passenger Experience
This covers overall satisfaction and comfort of rail users such as service quality, convenience, amenities and customer interactions.
The most mature, at-scale use cases focus on providing real-time intermodal journey and passenger information.
Others include railway security and revenue management areas such as marketing and pricing, booking and ticketing services and in-station additional revenue.
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4. Improved Customer Service
Digital web and mobile AI solutions enable personalised recommendations to be offered to your customers.
This helps meet your increasing customer expectations for fast, transparent customer service, thereby building more trust.
Customers can also track their own orders/deliveries and communicate issues promptly.
Of course, AI chatbots provide instant self-service support around the clock, when people may not otherwise be available.
Which also avoids a reduction in customer satisfaction that can often occur when overseas call centres are used out of hours instead.
5. Dynamic Marketing
AI-driven dynamic pricing tools are able to analyse market conditions, competitor pricing and customer behaviour thus enabling real-time price revision at the point of sale.
This ensures your business remains competitive whilst improving your revenue and profitability.
Furthermore, AI can help design targeted promotions and discounts based on customer segments and purchasing patterns.
By offering personalised promotions, manufacturers can stimulate demand and drive sales to create a win-win situation for your business and its customers.
If you could offer dynamic personalised promotions, do you think your customers:
would pay more for your offerings?
would be more likely to recommend you to others?
would re-purchase more and/or more often?
would show more loyalty to your business?
Hence, improved customer service, dynamic marketing and personalised promotions are major benefits of digital/AI adoption.
6. New Business Models
Just like other automotive and transport industries, digital/AI transformation is spawning new business models for the rail industry too.
Autonomous, driverless trains is an obvious example, especially for freight use, where AI can help to navigate complex environments, detect obstacles and initiate emergency braking if required.
AI can also support traffic control by monitoring real-time train movements and optimising schedules to balance maintenance needs with limited impact on traffic flow.
Similarly AI can predict maintenance needs based on historical condition data to automate inspections and maintenance events and thereby reduce unplanned service disruptions.
Making It Happen In The Rail Sector
Delivering on the promise of AI is not easy for the rail industry, which explains why many railway companies are yet to deploy AI use cases at scale.
For those that are, successful deployments are characterised by investment in dedicated capabilities and people talent; and the definition of clear objectives aligned with business priorities.
While transformative, AI brings new risks to the rail industry, which must be addressed from the outset as part of your overall transformation approach.
If this all seems daunting, then it is worth remembering that you are not alone.
There is a wealth of experience, deep technical and business expertise available from other related transport industries, equipment sectors and partners like Servispart Consulting to support your journey!
Moving Into The AI World To Deliver The Railways of Tomorrow
Satisfying customers who demand lower costs, 100% service availability and a personalised service experience is challenging.
Digital transformation and AI have become a major opportunity (or problem) for manufacturing, aftermarket and 3rd Party Logistics (3PL) companies in all industries.
It is a major opportunity if you are embracing the new digital/AI technologies.
But it is a huge problem if you are still trying to run your business with outdated systems, processes, people skills and organisation solutions!
Isn’t it time you flipped that huge problem into an opportunity?
Success with AI requires rethinking, updating, reconfiguring and reintegrating your business processes, systems, people and service partners across your end to end, rail support chain.
So ask yourself:
To what extent are you using AI in your rail business today?
How big is your AI opportunity?
Is it time to embrace digital and AI more fully?
How Servispart Consulting Can Help
Our aftermarket growth service is called Aftermarket 360™ and is specifically designed to assess your aftermarket capability strengths and weaknesses to create an aftermarket growth strategy that delivers high impact results in minimum time.
This has always included the latest thinking on digital transformation but now includes the latest thinking on AI adoption too!
If you’d like an informal conversation about how you could develop your aftermarket strategy and improve your aftermarket growth with digital and AI, click here to get in touch.
Additional Resources
Aftermarket Growth Guide
10-Point Aftermarket Growth Checklist
More information on how to discover your aftermarket genius and grow your aftermarket business is available here.
How are you using AI in your Aftermarket business?
