Transport for London (TfL) hopes chatbots can help it reduce pressure on its contact centres – and is going to market in September for technology suppliers that could help it stand up a programme to deliver them.
TfL has started early market engagement as it seeks to understand supplier capabilities around “self-service chatbots” – a tender this week studiously avoids using the term “AI” and suggests that TfL is thinking more expansively about how it modernises its customer services.
TfL manages a bus fleet of around 9,300 vehicles operating across 675 routes, and over 19,000 bus stops; 11 tube lines covering 402 kilometres and serving 272 stations; the driverless, computerised Docklands Light Railway; and eight piers along the Thames, among other responsibilities.
In 2022-2023 its passenger income was £4.2 billion but it is aiming to drive down costs across its estate and is targeting savings of £600 million from 2022/23 to 2025/26, its last annual report (September 2023) shows.
A March 7 notice highlights its focus on “reducing the demand coming into our contact centres; maximising the use of current and new data to produce strategic insights on TfL customers… [improving] our customer's experience as well as the experience of contact centre advisors.”
AI chatbots come with challenges…
TfL’s digital leaders may need to be warned however: Every organisation out there freshly looking to use generative AI to deliver customer-facing chatbots is finding it a more thorny experience than they realised.
Speaking at a financial services event this week attended by The Stack, for example, Vladislavs Mironovs (Chief Strategy & Business Development Officer at Latvia’s Citadele bankas) emphasised that he had a strong data science team and a “great database of customer decision trees” to start.
“Placing these all into genAI seems like a good starting moment, but brings a lot of issues…” he explained on March 7 at moneyLIVE.
“On-premises model deployments were spitting out lots of “deviations”; the generative AI “could not recognise” payments data and the “tone of voice was harsh” amongst other earlier challenges, he told the audience
(After a lot of wrenching and a decision to use GPT-4 Turbo that has now been improved and a beta chatbot is now live and able to handle 70% of requests, he said – a bold claim given it had only launched that same day.)
See also: Can £160 million and the cloud fix the DWP’s dismal contact centres?
TfL, meanwhile, said it wants to hear from suppliers if they have “solutions based on the following five capabilities:
1: Self-service Chatbots: A first point of contact to resolve TfL customer issues through self-serving our customers, where possible
2: Omni-channel / New Channels: A capability offering new and diverse methods of communication for TfL customers, such as WhatsApp, as well as the ability to collect and analyse data from across multiple channels
3: Agent Assist: A capability to augment and improve the contact centre advisors' ability to respond to customers as well as improve their productivity
4: Case Management: A capability that utilises automation to triage and manage cases
TfL is, it added, “also interested in any capabilities related to technology in contact centres that go beyond these five capabilities...”
