The trend of Interactive AI involves artificial intelligence (AI) algorithms that can process human user input, like text and speech, and provide a reasonable response. Advanced forms of this technology can interpret various writing styles and accents, hold complex conversations, perform complex tasks beyond simple commands, and mimic a sense of empathy with human users.
Emerging from the overarching trend of AI, there are multiple types of interactive AI with varying applications ranging from geolocation and navigation, facial detection and recognition, chatbots, digital assistants, speech-to-text dictation, and e-payment, to name a few. Within logistics and the supply chain, this brings greater efficiency to operations, making the day-to-day activities of employees less manual while also delivering a more automated customer experience.
Considering the impact so far of AI on the logistics industry, we here at DHL expect further developments in the next 5 years for the subset Interactive AI trend. This will have a powerful impact on customer-centric business approaches for logistics companies, as use cases are being identified across a multitude of workflow processes at all transactional levels in the supply chain powerfully. Continuous adoption and scaling of interactive AI technology within warehouses and other operational environments as well as in back-office workflows demonstrates the opportunities for human-machine collaboration.
Chatbots are becoming useful tools for businesses when engaging with customers.
Relevance to the Future of Logistics
- Customer Experience Automation
- Chatbots In The Workplace
- AI-Assisted Sales & Marketing Employee Experience Automation
With customer experience at the core of business success in logistics, customer service departments are very important to logistics companies. These departments are the first touchpoint when issues arise. Chatbots can help logistics companies handle low to medium-volume call center queries about, for example, requesting deliveries, editing orders, shipment tracking, and responding to FAQs. Chatbots can also facilitate valuable analytics metrics, enabling the company to better understand customer needs and enhance the customer experience.
As a result, chatbots represent today’s fastest-growing brand communication channel with a handling rate of chat completion from start to finish at 68.9% in 2020 (an increase of 260% in end-to-end resolution over 2017), with the contribution to e-commerce transactions predicted to reach 112 billion USD by 2023.
With Interactive AI, customer service automation also extends to user input processing through other commonly used communication channels such as immediate email responses, automated phone services, and integration with most widespread used text messaging platforms. This extends the realms within which customers can obtain immediate and satisfactory responses to enquiries.
In the context of digital workplaces, chatbots are commonly used in just about all sectors, most significantly in the healthcare industry when Covid-19 hit, to handle the massive influx of questions from the public. In all sectors, AI chatbots can enable workers to access the information needed to complete their work.
According to Gartner, 70% of white-collar workers will interact with chatbot platforms daily by the end of 2022.3 Similar to customer service applications, these platforms can provide immediate information and answers to office workers, helping the organization disseminate details about change management, human resources, helpdesk support, general services, anomaly reporting, and organizing meetings.
For logistics operations, chatbots can streamline inventory handling and management, cargo tracking, and delivery schedules, as well as customer relationship management (CRM) and warehouse management system (WMS) updates. The adoption of interactive AI technology within the supply chain automates workflows and order management, freeing up operations employees to focus on more complex and value-adding tasks. In the event of a chatbot being unable to complete an enquiry, it assigns the task to a human for further action while notifying the requestor about this status.
Analytics of data captured on an interactive AI platform can provide valuable insights to the business. For example, companies may better understand customer pain points and consumer behavior patterns, enabling more effective marketing campaigns to attract potential leads. Data analytics can help with price optimization and – for retailers – better in-store and web-based layout mapping based on behavioral data. It can also help retailers and e-commerce businesses efficiently manage the supply chain while ensuring supply and demand are met at operational level.
Start-up vendors delivering sales and marketing intelligence as well as acceleration software tools like Groove and UpLead enable companies to reach their full potential through interactive AI. In recent years, we’ve all become familiar with AI assistants – for example, Amazon’s Alexa which provides consumers with an AI-powered cloud-based voice service accessing hundreds of millions of devices including third-party device manufacturers.
Data captured through Alexa and similar devices enables more individually targeted marketing, with algorithms to analyze consumer behavior. Meta’s chatbot BlenderBot accumulates user data to tailor its responses in accordance with the user’s history, tapping into the vast library of human thought on the internet. The device is trained on large language datasets, allowing it to generate with factual accuracy passably human responses to questions. In the long term, the purpose and goal of this chatbot is a virtual assistant capable of responding to a wide variety of topics with factual intelligence.
While we have seen developmental leaps in AI in recent years, it continues to generate interest and investment is predicted to grow in the long term in expanding interactive AI applications capable of driving significant economic value. The 3 key building blocks of more data, better algorithms, and stronger computing power indicate these use cases are likely to materialize and scale.
Logistics and the supply chain are integral to soaring AI adoption levels every year. The industry’s AI adoption rate is predicted at 42.9% CAGR, reaching a value of 6.5 billion USD by 2023. By adopting interactive AI technology, the logistics industry can respond effectively to the operational challenges of growing B2B and B2C demand for immediate goods delivery.
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- Multiple (2022): Top 15 Use Cases and Applications of AI in Logistics in 2022
- startupbonsai (2022): 25+ Top Chatbot Statistics For 2022: Usage, Demographics, Trends
- Beezy (2021): AI chatbots: The good, the bad, and the employee experience
- Locobuzz (2021): Importance Of Chatbots For Logistics And Supply-Chain
- Groove (2020): Groove sales productivity platform
- UpLead (2020): UpLead
- Multiple (2022): Future of AI according to top AI experts: In-Depth Guide for 2022
- Data Root Labs (2021): Artificial Intelligence in Logistics: Emerging Startups, Challenges and Use Cases